{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,9]],"date-time":"2026-06-09T15:40:52Z","timestamp":1781019652342,"version":"3.54.1"},"reference-count":181,"publisher":"Association for Computing Machinery (ACM)","issue":"12","license":[{"start":{"date-parts":[[2023,3,2]],"date-time":"2023-03-02T00:00:00Z","timestamp":1677715200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"European Union\u2019s Horizon 2020 research and innovation programme","award":["825328"],"award-info":[{"award-number":["825328"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Comput. Surv."],"published-print":{"date-parts":[[2023,12,31]]},"abstract":"<jats:p>Machine learning (ML) techniques increase the effectiveness of software engineering (SE) lifecycle activities. We systematically collected, quality-assessed, summarized, and categorized 83 reviews in ML for SE published between 2009 and 2022, covering 6,117 primary studies. The SE areas most tackled with ML are software quality and testing, while human-centered areas appear more challenging for ML. We propose a number of ML for SE research challenges and actions, including conducting further empirical validation and industrial studies on ML, reconsidering deficient SE methods, documenting and automating data collection and pipeline processes, reexamining how industrial practitioners distribute their proprietary data, and implementing incremental ML approaches.<\/jats:p>","DOI":"10.1145\/3572905","type":"journal-article","created":{"date-parts":[[2022,11,30]],"date-time":"2022-11-30T13:05:25Z","timestamp":1669813525000},"page":"1-39","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":41,"title":["Machine Learning for Software Engineering: A Tertiary Study"],"prefix":"10.1145","volume":"55","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3816-9162","authenticated-orcid":false,"given":"Zoe","family":"Kotti","sequence":"first","affiliation":[{"name":"Athens University of Economics and Business, Athens, Greece"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5318-9017","authenticated-orcid":false,"given":"Rafaila","family":"Galanopoulou","sequence":"additional","affiliation":[{"name":"Athens University of Economics and Business, Athens, Greece"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4231-1897","authenticated-orcid":false,"given":"Diomidis","family":"Spinellis","sequence":"additional","affiliation":[{"name":"Athens University of Economics and Business, Athens, Greece"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2023,3,2]]},"reference":[{"issue":"3","key":"e_1_3_2_2_2","first-page":"e2320","article-title":"Software smell detection techniques: A systematic literature review","volume":"33","author":"AbuHassan Amjad","year":"2021","unstructured":"Amjad AbuHassan, Mohammad Alshayeb, and Lahouari Ghouti. 2021. Software smell detection techniques: A systematic literature review. J. Softw.: Evol. Process 33, 3 (2021), e2320. DOI:https:\/\/doi.org\/10.1002\/smr.2320","journal-title":"J. Softw.: Evol. Process"},{"key":"e_1_3_2_3_2","article-title":"A systematic literature review on using machine learning algorithms for software requirements identification on stack overflow","volume":"2020","author":"Ahmad Arshad","year":"2020","unstructured":"Arshad Ahmad, Chong Feng, Muzammil Khan, Asif Khan, Ayaz Ullah, Shah Nazir, Adnan Tahir, and Iqtadar Hussain. 2020. A systematic literature review on using machine learning algorithms for software requirements identification on stack overflow. Secur. Commun. Netw. 2020 (Jan.2020), 19. DOI:https:\/\/doi.org\/10.1155\/2020\/8830683","journal-title":"Secur. Commun. Netw."},{"key":"e_1_3_2_4_2","doi-asserted-by":"crossref","first-page":"25706","DOI":"10.1109\/ACCESS.2017.2771562","article-title":"Constrained interaction testing: A systematic literature study","volume":"5","author":"Ahmed Bestoun S.","year":"2017","unstructured":"Bestoun S. Ahmed, Kamal Z. Zamli, Wasif Afzal, and Miroslav Bures. 2017. Constrained interaction testing: A systematic literature study. IEEE Access 5 (2017), 25706\u201325730. DOI:https:\/\/doi.org\/10.1109\/ACCESS.2017.2771562","journal-title":"IEEE Access"},{"issue":"4","key":"e_1_3_2_5_2","doi-asserted-by":"crossref","first-page":"2341","DOI":"10.1007\/s13369-019-04311-w","article-title":"Bad smell detection using machine learning techniques: A systematic literature review","volume":"45","author":"Al-Shaaby Ahmed","year":"2020","unstructured":"Ahmed Al-Shaaby, Hamoud Aljamaan, and Mohammad Alshayeb. 2020. Bad smell detection using machine learning techniques: A systematic literature review. Arab. J. Sci. Eng. 45, 4 (Jan.2020), 2341\u20132369. DOI:https:\/\/doi.org\/10.1007\/s13369-019-04311-w","journal-title":"Arab. J. Sci. Eng."},{"issue":"10","key":"e_1_3_2_6_2","first-page":"e2211","article-title":"A systematic literature review of software effort prediction using machine learning methods","volume":"31","author":"Ali Asad","year":"2019","unstructured":"Asad Ali and Carmine Gravino. 2019. A systematic literature review of software effort prediction using machine learning methods. J. Softw.: Evol. Process 31, 10 (2019), e2211. DOI:https:\/\/doi.org\/10.1002\/smr.2211","journal-title":"J. Softw.: Evol. Process"},{"key":"e_1_3_2_7_2","volume-title":"Proceedings of the 45th Euromicro Conference on Software Engineering and Advanced Applications (SEAA\u201919)","author":"Ali Asad","year":"2019","unstructured":"Asad Ali and Carmine Gravino. 2019. Using bio-inspired features selection algorithms in software effort estimation: A systematic literature review. In Proceedings of the 45th Euromicro Conference on Software Engineering and Advanced Applications (SEAA\u201919). IEEE. DOI:https:\/\/doi.org\/10.1109\/seaa.2019.00043"},{"key":"e_1_3_2_8_2","volume-title":"Proceedings of the 14th International Conference on Open Source Systems and Technologies (ICOSST\u201920)","author":"Ali Asad","year":"2020","unstructured":"Asad Ali and Carmine Gravino. 2020. Bio-inspired algorithms in software fault prediction: A systematic literature review. In Proceedings of the 14th International Conference on Open Source Systems and Technologies (ICOSST\u201920). IEEE. DOI:https:\/\/doi.org\/10.1109\/icosst51357.2020.9332995"},{"issue":"4","key":"e_1_3_2_9_2","first-page":"e2332","article-title":"Social network sites and requirements engineering: A systematic literature review","volume":"33","author":"Ali Nazakat","year":"2021","unstructured":"Nazakat Ali, Jang-Eui Hong, and Lawrence Chung. 2021. Social network sites and requirements engineering: A systematic literature review. J. Softw.: Evol. Process 33, 4 (2021), e2332. DOI:https:\/\/doi.org\/10.1002\/smr.2332","journal-title":"J. Softw.: Evol. Process"},{"issue":"4","key":"e_1_3_2_10_2","first-page":"81","article-title":"A survey of machine learning for big code and naturalness","volume":"51","author":"Allamanis Miltiadis","year":"2018","unstructured":"Miltiadis Allamanis, Earl T. Barr, Premkumar Devanbu, and Charles Sutton. 2018. A survey of machine learning for big code and naturalness. Comput. Surveys 51, 4, Article 81 (July2018), 37 pages. DOI:https:\/\/doi.org\/10.1145\/3212695","journal-title":"Comput. Surveys"},{"key":"e_1_3_2_11_2","first-page":"55","volume-title":"Proceedings of the International Conference on Current Trends in Computer, Electrical, Electronics and Communication (CTCEEC\u201917)","author":"Alsalemi Ahmed M.","year":"2018","unstructured":"Ahmed M. Alsalemi and Eng-Thiam Yeoh. 2018. A systematic literature review of requirements volatility prediction. In Proceedings of the International Conference on Current Trends in Computer, Electrical, Electronics and Communication (CTCEEC\u201917). IEEE, 55\u201364. DOI:https:\/\/doi.org\/10.1109\/CTCEEC.2017.8455174"},{"key":"e_1_3_2_12_2","article-title":"A systematic review of feature selection techniques in software quality prediction","author":"Alsolai Hadeel","year":"2019","unstructured":"Hadeel Alsolai and Marc Roper. 2019. A systematic review of feature selection techniques in software quality prediction. Proceedings of the International Conference on Electrical and Computing Technologies and Applications. DOI:https:\/\/doi.org\/10.1109\/ICECTA48151.2019.8959566","journal-title":"Proceedings of the International Conference on Electrical and Computing Technologies and Applications"},{"key":"e_1_3_2_13_2","doi-asserted-by":"crossref","first-page":"201","DOI":"10.1016\/j.infsof.2018.10.006","article-title":"Identifying, categorizing and mitigating threats to validity in software engineering secondary studies","volume":"106","author":"Ampatzoglou Apostolos","year":"2019","unstructured":"Apostolos Ampatzoglou, Stamatia Bibi, Paris Avgeriou, Marijn Verbeek, and Alexander Chatzigeorgiou. 2019. Identifying, categorizing and mitigating threats to validity in software engineering secondary studies. Info. Softw. Technol. 106 (Feb.2019), 201\u2013230. DOI:https:\/\/doi.org\/10.1016\/j.infsof.2018.10.006","journal-title":"Info. Softw. Technol."},{"key":"e_1_3_2_14_2","doi-asserted-by":"crossref","first-page":"14","DOI":"10.1145\/3387904.3389251","volume-title":"Proceedings of the 28th International Conference on Program Comprehension","author":"Aung Thazin Win Win","year":"2020","unstructured":"Thazin Win Win Aung, Huan Huo, and Yulei Sui. 2020. A literature review of automatic traceability links recovery for software change impact analysis. In Proceedings of the 28th International Conference on Program Comprehension. ACM, New York, NY, 14\u201324. DOI:https:\/\/doi.org\/10.1145\/3387904.3389251"},{"issue":"2","key":"e_1_3_2_15_2","doi-asserted-by":"crossref","first-page":"38","DOI":"10.1145\/2894784.2894800","article-title":"Technical debt: Broadening perspectives report on the seventh workshop on managing technical debt","volume":"41","author":"Avgeriou Paris","year":"2016","unstructured":"Paris Avgeriou, Neil A. Ernst, Robert L. Nord, and Philippe Kruchten. 2016. Technical debt: Broadening perspectives report on the seventh workshop on managing technical debt. SIGSOFT Softw. Eng. Notes 41, 2 (May2016), 38\u201341. DOI:https:\/\/doi.org\/10.1145\/2894784.2894800","journal-title":"SIGSOFT Softw. Eng. Notes"},{"key":"e_1_3_2_16_2","volume-title":"Proceedings of the 50th Hawaii International Conference on System Sciences","author":"Aydin Ahmet","year":"2017","unstructured":"Ahmet Aydin and Ken Anderson. 2017. Batch to real-time: Incremental data collection & analytics platform. In Proceedings of the 50th Hawaii International Conference on System Sciences. Hawaii International Conference on System Sciences. DOI:https:\/\/doi.org\/10.24251\/hicss.2017.712"},{"key":"e_1_3_2_17_2","first-page":"1","volume-title":"Proceedings of the 7th ACM SIGPLAN-SIGSOFT Workshop on Program Analysis for Software Tools and Engineering","author":"Ayewah Nathaniel","year":"2007","unstructured":"Nathaniel Ayewah, William Pugh, J. David Morgenthaler, John Penix, and YuQian Zhou. 2007. Evaluating static analysis defect warnings on production software. In Proceedings of the 7th ACM SIGPLAN-SIGSOFT Workshop on Program Analysis for Software Tools and Engineering. ACM, 1\u20138. DOI:https:\/\/doi.org\/10.1145\/1251535.1251536"},{"key":"e_1_3_2_18_2","doi-asserted-by":"crossref","first-page":"115","DOI":"10.1016\/j.infsof.2018.12.009","article-title":"Machine learning techniques for code smell detection: A systematic literature review and meta-analysis","volume":"108","author":"Azeem Muhammad Ilyas","year":"2019","unstructured":"Muhammad Ilyas Azeem, Fabio Palomba, Lin Shi, and Qing Wang. 2019. Machine learning techniques for code smell detection: A systematic literature review and meta-analysis. Info. Softw. Technol. 108 (Apr.2019), 115\u2013138. DOI:https:\/\/doi.org\/10.1016\/j.infsof.2018.12.009","journal-title":"Info. Softw. Technol."},{"key":"e_1_3_2_19_2","doi-asserted-by":"crossref","first-page":"102596","DOI":"10.1016\/j.scico.2020.102596","article-title":"Predicting software effort from use case points: A systematic review","volume":"204","author":"Azzeh Mohammad","year":"2021","unstructured":"Mohammad Azzeh, Ali Bou Nassif, and Imtinan Basem Attili. 2021. Predicting software effort from use case points: A systematic review. Sci. Comput. Program. 204 (Apr.2021), 102596. DOI:https:\/\/doi.org\/10.1016\/j.scico.2020.102596","journal-title":"Sci. Comput. Program."},{"issue":"5","key":"e_1_3_2_20_2","doi-asserted-by":"crossref","first-page":"490","DOI":"10.3844\/jcssp.2021.490.510","article-title":"A systematic literature review of software defect prediction using deep learning","volume":"17","author":"Bahaa Ahmed","year":"2021","unstructured":"Ahmed Bahaa, Enas Mohamed Fathy, Ahmed Sharaf Eldin, Laila A. Abd-Elmegid, Ahmed Bahaa, and Ahmed Sharaf Eldin. 2021. A systematic literature review of software defect prediction using deep learning. J. Comput. Sci. 17, 5 (May2021), 490\u2013510. DOI:https:\/\/doi.org\/10.3844\/jcssp.2021.490.510","journal-title":"J. Comput. Sci."},{"key":"e_1_3_2_21_2","doi-asserted-by":"crossref","first-page":"132","DOI":"10.1016\/j.jss.2015.05.006","article-title":"Feature extraction approaches from natural language requirements for reuse in software product lines: A systematic literature review","volume":"106","author":"Bakar Noor H.","year":"2015","unstructured":"Noor H. Bakar, Zarinah M. Kasirun, and Norsaremah Salleh. 2015. Feature extraction approaches from natural language requirements for reuse in software product lines: A systematic literature review. J. Syst. Softw. 106, C (Aug.2015), 132\u2013149. DOI:https:\/\/doi.org\/10.1016\/j.jss.2015.05.006","journal-title":"J. Syst. Softw."},{"key":"e_1_3_2_22_2","volume-title":"Proceedings of the IEEE 4th International Workshop on Empirical Requirements Engineering (EmpiRE\u201914)","author":"Bano Muneera","year":"2014","unstructured":"Muneera Bano, Didar Zowghi, and Naveed Ikram. 2014. Systematic reviews in requirements engineering: A tertiary study. In Proceedings of the IEEE 4th International Workshop on Empirical Requirements Engineering (EmpiRE\u201914). IEEE. DOI:https:\/\/doi.org\/10.1109\/empire.2014.6890110"},{"issue":"3","key":"e_1_3_2_23_2","doi-asserted-by":"crossref","first-page":"501","DOI":"10.1017\/S0373463321000254","article-title":"A novel model blah blah blah","volume":"74","author":"Basiri Anahid","year":"2021","unstructured":"Anahid Basiri. 2021. A novel model blah blah blah. J. Navigat. 74, 3 (2021), 501\u2013504. DOI:https:\/\/doi.org\/10.1017\/S0373463321000254","journal-title":"J. Navigat."},{"key":"e_1_3_2_24_2","article-title":"Software fault prediction using data mining, machine learning and deep learning techniques: A systematic literature review","volume":"100","author":"Batool Iqra","year":"2022","unstructured":"Iqra Batool and Tamim Ahmed Khan. 2022. Software fault prediction using data mining, machine learning and deep learning techniques: A systematic literature review. Comput. Electr. Eng. 100, C (May2022), 20. DOI:https:\/\/doi.org\/10.1016\/j.compeleceng.2022.107886","journal-title":"Comput. Electr. Eng."},{"issue":"4","key":"e_1_3_2_25_2","doi-asserted-by":"crossref","first-page":"1081","DOI":"10.2337\/db14-1208","article-title":"The streetlight effect in type 1 diabetes","volume":"64","author":"Battaglia Manuela","year":"2015","unstructured":"Manuela Battaglia and Mark A. Atkinson. 2015. The streetlight effect in type 1 diabetes. Diabetes 64, 4 (2015), 1081\u20131090.","journal-title":"Diabetes"},{"issue":"6","key":"e_1_3_2_26_2","doi-asserted-by":"crossref","first-page":"1565","DOI":"10.1007\/s10664-013-9255-y","article-title":"Recovering from a decade: A systematic mapping of information retrieval approaches to software traceability","volume":"19","author":"Borg Markus","year":"2014","unstructured":"Markus Borg, Per Runeson, and Anders Ard\u00f6. 2014. Recovering from a decade: A systematic mapping of information retrieval approaches to software traceability. Empir. Softw. Eng. 19, 6 (Dec.2014), 1565\u20131616. DOI:https:\/\/doi.org\/10.1007\/s10664-013-9255-y","journal-title":"Empir. Softw. Eng."},{"key":"e_1_3_2_27_2","volume-title":"Guide to the Software Engineering Body of Knowledge, Version 3.0","author":"Bourque Pierre","year":"2014","unstructured":"Pierre Bourque and Richard E. Fairley (Eds.). 2014. Guide to the Software Engineering Body of Knowledge, Version 3.0. IEEE Computer Society. Retrieved from www.swebok.org."},{"issue":"4","key":"e_1_3_2_28_2","doi-asserted-by":"crossref","first-page":"571","DOI":"10.1016\/j.jss.2006.07.009","article-title":"Lessons from applying the systematic literature review process within the software engineering domain","volume":"80","author":"Brereton Pearl","year":"2007","unstructured":"Pearl Brereton, Barbara A. Kitchenham, David Budgen, Mark Turner, and Mohamed Khalil. 2007. Lessons from applying the systematic literature review process within the software engineering domain. J. Syst. Softw. 80, 4 (2007), 571\u2013583. DOI:https:\/\/doi.org\/10.1016\/j.jss.2006.07.009","journal-title":"J. Syst. Softw."},{"issue":"4","key":"e_1_3_2_29_2","doi-asserted-by":"crossref","first-page":"10","DOI":"10.1109\/MC.1987.1663532","article-title":"No silver bullet: Essence and accidents of software engineering","volume":"20","author":"Brooks Frederick P.","year":"1987","unstructured":"Frederick P. Brooks. 1987. No silver bullet: Essence and accidents of software engineering. Computer 20, 4 (Apr.1987), 10\u201319. DOI:https:\/\/doi.org\/10.1109\/MC.1987.1663532","journal-title":"Computer"},{"key":"e_1_3_2_30_2","volume-title":"The Mythical Man-Month (Anniversary Ed.)","author":"Brooks Frederick P.","year":"1995","unstructured":"Frederick P. Brooks. 1995. The Mythical Man-Month (Anniversary Ed.). Addison-Wesley Longman Publishing."},{"issue":"02","key":"e_1_3_2_31_2","doi-asserted-by":"crossref","first-page":"285","DOI":"10.1142\/S021819401950013X","article-title":"Machine learning techniques for code smells detection: A systematic mapping study","volume":"29","author":"Caram Frederico Luiz","year":"2019","unstructured":"Frederico Luiz Caram, Bruno Rafael De Oliveira Rodrigues, Amadeu Silveira Campanelli, and Fernando Silva Parreiras. 2019. Machine learning techniques for code smells detection: A systematic mapping study. Int. J. Softw. Eng. Knowl. Eng. 29, 02 (Feb.2019), 285\u2013316. DOI:https:\/\/doi.org\/10.1142\/s021819401950013x","journal-title":"Int. J. Softw. Eng. Knowl. Eng."},{"issue":"4","key":"e_1_3_2_32_2","doi-asserted-by":"crossref","first-page":"26","DOI":"10.1109\/MS.2020.2987666","article-title":"The AI effect: Working at the intersection of AI and SE","volume":"37","author":"Carleton Anita D.","year":"2020","unstructured":"Anita D. Carleton, Erin Harper, Tim Menzies, Tao Xie, Sigrid Eldh, and Michael R. Lyu. 2020. The AI effect: Working at the intersection of AI and SE. IEEE Softw. 37, 4 (2020), 26\u201335. DOI:https:\/\/doi.org\/10.1109\/MS.2020.2987666","journal-title":"IEEE Softw."},{"key":"e_1_3_2_33_2","volume-title":"Proceedings of the 46th Euromicro Conference on Software Engineering and Advanced Applications (SEAA\u201920)","author":"Carpio Alvaro Fernandez Del","year":"2020","unstructured":"Alvaro Fernandez Del Carpio and Leonardo Bermon Angarita. 2020. Trends in software engineering processes using deep learning: A systematic literature review. In Proceedings of the 46th Euromicro Conference on Software Engineering and Advanced Applications (SEAA\u201920). IEEE. DOI:https:\/\/doi.org\/10.1109\/seaa51224.2020.00077"},{"key":"e_1_3_2_34_2","volume-title":"Proceedings of the 46th Euromicro Conference on Software Engineering and Advanced Applications (SEAA\u201920)","author":"Caulo Maria","year":"2020","unstructured":"Maria Caulo and Giuseppe Scanniello. 2020. A taxonomy of metrics for software fault prediction. In Proceedings of the 46th Euromicro Conference on Software Engineering and Advanced Applications (SEAA\u201920). IEEE. DOI:https:\/\/doi.org\/10.1109\/seaa51224.2020.00075"},{"key":"e_1_3_2_35_2","volume-title":"Constructing Grounded Theory (2nd ed.)","author":"Charmaz Kathy","year":"2014","unstructured":"Kathy Charmaz. 2014. Constructing Grounded Theory (2nd ed.). SAGE Publications."},{"key":"e_1_3_2_36_2","first-page":"321","volume-title":"Proceedings of the 23rd International Systems and Software Product Line Conference\u2014Volume A (SPLC\u201919)","author":"Chavarriaga Jaime","year":"2019","unstructured":"Jaime Chavarriaga and Julio Ariel Hurtado. 2019. Second international workshop on experiences and empirical studies on software reuse (WEESR\u201919). In Proceedings of the 23rd International Systems and Software Product Line Conference\u2014Volume A (SPLC\u201919). ACM, New York, NY, 321. DOI:https:\/\/doi.org\/10.1145\/3336294.3342366"},{"key":"e_1_3_2_37_2","doi-asserted-by":"crossref","first-page":"1843","DOI":"10.1007\/s10664-015-9402-8","article-title":"A survey on the use of topic models when mining software repositories","volume":"21","author":"Chen Tse-Hsun","year":"2016","unstructured":"Tse-Hsun Chen, Stephen W. Thomas, and Ahmed E. Hassan. 2016. A survey on the use of topic models when mining software repositories. Empir. Softw. Eng. 21 (Oct.2016), 1843\u20131919. DOI:https:\/\/doi.org\/10.1007\/s10664-015-9402-8","journal-title":"Empir. Softw. Eng."},{"issue":"10","key":"e_1_3_2_38_2","doi-asserted-by":"crossref","first-page":"623","DOI":"10.1145\/2544173.2509552","article-title":"Guided GUI testing of android apps with minimal restart and approximate learning","volume":"48","author":"Choi Wontae","year":"2013","unstructured":"Wontae Choi, George Necula, and Koushik Sen. 2013. Guided GUI testing of android apps with minimal restart and approximate learning. SIGPLAN Not. 48, 10 (Oct.2013), 623\u2013640. DOI:https:\/\/doi.org\/10.1145\/2544173.2509552","journal-title":"SIGPLAN Not."},{"key":"e_1_3_2_39_2","first-page":"37","volume-title":"Proceedings of the 1st International Workshop on Realizing AI Synergies in Software Engineering (RAISE\u201912)","author":"Clifton David A.","year":"2012","unstructured":"David A. Clifton, Jeremy Gibbons, Jim Davies, and Lionel Tarassenko. 2012. Machine learning and software engineering in health informatics. In Proceedings of the 1st International Workshop on Realizing AI Synergies in Software Engineering (RAISE\u201912). 37\u201341. DOI:https:\/\/doi.org\/10.1109\/RAISE.2012.6227968"},{"issue":"1","key":"e_1_3_2_40_2","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1007\/BF00988593","article-title":"Grounded theory research: Procedures, canons, and evaluative criteria","volume":"13","author":"Corbin Juliet M.","year":"1990","unstructured":"Juliet M. Corbin and Anselm Strauss. 1990. Grounded theory research: Procedures, canons, and evaluative criteria. Qual. Sociol. 13, 1 (1990), 3\u201321.","journal-title":"Qual. Sociol."},{"key":"e_1_3_2_41_2","volume-title":"Proceedings of the IEEE International Conference on Software Maintenance and Evolution (ICSME\u201915)","author":"Corley Christopher S.","year":"2015","unstructured":"Christopher S. Corley, Kostadin Damevski, and Nicholas A. Kraft. 2015. Exploring the use of deep learning for feature location. In Proceedings of the IEEE International Conference on Software Maintenance and Evolution (ICSME\u201915). IEEE. DOI:https:\/\/doi.org\/10.1109\/icsm.2015.7332513"},{"key":"e_1_3_2_42_2","volume-title":"Proceedings of the 24th Iberoamerican Conference on Software Engineering (CIbSE\u201921)","author":"Costal Dolors","year":"2021","unstructured":"Dolors Costal, Carles Farr\u00e9, Xavier Franch, and Carme Quer. 2021. How tertiary studies perform quality assessment of secondary studies in software engineering. In Proceedings of the 24th Iberoamerican Conference on Software Engineering (CIbSE\u201921). Curran Associates, 14."},{"issue":"11","key":"e_1_3_2_43_2","doi-asserted-by":"crossref","first-page":"916","DOI":"10.7326\/0003-4819-110-11-916","article-title":"The box plot: A simple visual method to interpret data","volume":"110","author":"Williamson R. A. Parker D. F.","year":"1989","unstructured":"R. A. Parker D. F. Williamson and J. S. Kendrick. 1989. The box plot: A simple visual method to interpret data. Ann. Intern. Med. 110, 11 (June1989), 916. DOI:https:\/\/doi.org\/10.7326\/0003-4819-110-11-916","journal-title":"Ann. Intern. Med."},{"issue":"9","key":"e_1_3_2_44_2","doi-asserted-by":"crossref","first-page":"899","DOI":"10.1016\/j.infsof.2011.04.004","article-title":"Six years of systematic literature reviews in software engineering: An updated tertiary study","volume":"53","author":"Silva Fabio Q. B. da","year":"2011","unstructured":"Fabio Q. B. da Silva, Andr\u00e9 L. M. Santos, S\u00e9rgio Soares, A. C\u00e9sar C. Fran\u00e7a, Cleviton V. F. Monteiro, and Felipe Farias Maciel. 2011. Six years of systematic literature reviews in software engineering: An updated tertiary study. Info. Softw. Technol. 53, 9 (Sept.2011), 899\u2013913. DOI:https:\/\/doi.org\/10.1016\/j.infsof.2011.04.004","journal-title":"Info. Softw. Technol."},{"key":"e_1_3_2_45_2","first-page":"2005","volume-title":"Proceedings of the 35th Annual ACM Symposium on Applied Computing (SAC\u201920)","author":"Castro-Cabrera M. del Carmen de","year":"2020","unstructured":"M. del Carmen de Castro-Cabrera, Antonio Garc\u00eda-Dominguez, and Inmaculada Medina-Bulo. 2020. Trends in prioritization of test cases: 2017\u20132019. In Proceedings of the 35th Annual ACM Symposium on Applied Computing (SAC\u201920). ACM, New York, NY, 2005\u20132011. DOI:https:\/\/doi.org\/10.1145\/3341105.3374036"},{"issue":"4","key":"e_1_3_2_46_2","doi-asserted-by":"crossref","first-page":"461","DOI":"10.1007\/s00766-015-0225-3","article-title":"Bayesian networks for enhancement of requirements engineering: A literature review","volume":"21","author":"\u00c1guila Isabel M. del","year":"2015","unstructured":"Isabel M. del \u00c1guila and Jos\u00e9 del Sagrado. 2015. Bayesian networks for enhancement of requirements engineering: A literature review. Require. Eng. 21, 4 (May2015), 461\u2013480. DOI:https:\/\/doi.org\/10.1007\/s00766-015-0225-3","journal-title":"Require. Eng."},{"key":"e_1_3_2_47_2","first-page":"51","volume-title":"Proceedings of the 24th Asia-Pacific Software Engineering Conference (APSEC\u201917)","author":"Dong Liming","year":"2017","unstructured":"Liming Dong, Bohan Liu, Zheng Li, Ou Wu, Muhammad A. Babar, and Bingbing Xue. 2017. A mapping study on mining software process. In Proceedings of the 24th Asia-Pacific Software Engineering Conference (APSEC\u201917). IEEE, 51\u201360. DOI:https:\/\/doi.org\/10.1109\/APSEC.2017.11"},{"key":"e_1_3_2_48_2","volume-title":"Proceedings of the IEEE 7th International Conference on Global Software Engineering","author":"Santos Alinne C. C. dos","year":"2012","unstructured":"Alinne C. C. dos Santos, Ivaldir H. de Farias Junior, Hermano P. de Moura, and Sabrina Marczak. 2012. A systematic tertiary study of communication in distributed software development projects. In Proceedings of the IEEE 7th International Conference on Global Software Engineering. IEEE. DOI:https:\/\/doi.org\/10.1109\/icgse.2012.42"},{"issue":"3","key":"e_1_3_2_49_2","doi-asserted-by":"crossref","first-page":"1189","DOI":"10.1109\/TR.2019.2892517","article-title":"Machine learning applied to software testing: A systematic mapping study","volume":"68","author":"Durelli Vinicius H. S.","year":"2019","unstructured":"Vinicius H. S. Durelli, Rafael S. Durelli, Simone S. Borges, Andre T. Endo, Marcelo M. Eler, Diego R. C. Dias, and Marcelo P. Guimar\u00e3es. 2019. Machine learning applied to software testing: A systematic mapping study. IEEE Trans. Reliabil. 68, 3 (Sept.2019), 1189\u20131212. DOI:https:\/\/doi.org\/10.1109\/TR.2019.2892517","journal-title":"IEEE Trans. Reliabil."},{"key":"e_1_3_2_50_2","first-page":"178","volume-title":"Proceedings of the 2nd International Symposium on Empirical Software Engineering and Measurement (ESEM\u201908)","author":"Dyb\u00e5 Tore","year":"2008","unstructured":"Tore Dyb\u00e5 and Torgeir Dings\u00f8yr. 2008. Strength of evidence in systematic reviews in software engineering. In Proceedings of the 2nd International Symposium on Empirical Software Engineering and Measurement (ESEM\u201908). ACM, New York, NY, 178\u2013187. DOI:https:\/\/doi.org\/10.1145\/1414004.1414034"},{"key":"e_1_3_2_51_2","first-page":"285","volume-title":"Selecting Empirical Methods for Software Engineering Research","author":"Easterbrook Steve","year":"2008","unstructured":"Steve Easterbrook, Janice Singer, Margaret-Anne Storey, and Daniela Damian. 2008. Selecting Empirical Methods for Software Engineering Research. Springer, London, 285\u2013311. DOI:https:\/\/doi.org\/10.1007\/978-1-84800-044-5_11"},{"issue":"1","key":"e_1_3_2_52_2","first-page":"141","article-title":"Empirical studies on software product maintainability prediction: A systematic mapping and review","volume":"13","author":"Elmidaoui Sara","year":"2019","unstructured":"Sara Elmidaoui, Laila Cheikhi, Ali Idri, and Alain Abran. 2019. Empirical studies on software product maintainability prediction: A systematic mapping and review. e-Info. Softw. Eng. J. 13, 1 (2019), 141\u2013202. DOI:https:\/\/doi.org\/10.5277\/E-INF190105","journal-title":"e-Info. Softw. Eng. J."},{"issue":"5","key":"e_1_3_2_53_2","doi-asserted-by":"crossref","first-page":"1147","DOI":"10.1007\/s11390-020-9668-1","article-title":"Machine learning techniques for software maintainability prediction: Accuracy analysis","volume":"35","author":"Elmidaoui Sara","year":"2020","unstructured":"Sara Elmidaoui, Laila Cheikhi, Ali Idri, and Alain Abran. 2020. Machine learning techniques for software maintainability prediction: Accuracy analysis. J. Comput. Sci. Technol. 35, 5 (Oct.2020), 1147\u20131174. DOI:https:\/\/doi.org\/10.1007\/s11390-020-9668-1","journal-title":"J. Comput. Sci. Technol."},{"key":"e_1_3_2_54_2","doi-asserted-by":"crossref","first-page":"289","DOI":"10.1007\/978-3-030-00623-5_20","volume-title":"Proceedings of the 18th International Conference on Software Process Improvement and Capability Determination (SPICE\u201918)","author":"Erdem Sezen","year":"2018","unstructured":"Sezen Erdem, Onur Demir\u00f6rs, and Fethi Rabhi. 2018. Systematic mapping study on process mining in agile software development. In Proceedings of the 18th International Conference on Software Process Improvement and Capability Determination (SPICE\u201918). Springer International Publishing, 289\u2013299. DOI:https:\/\/doi.org\/10.1007\/978-3-030-00623-5_20"},{"key":"e_1_3_2_55_2","doi-asserted-by":"crossref","first-page":"113","DOI":"10.1007\/978-3-030-05318-5_6","volume-title":"Proceedings of the Automated Machine Learning","author":"Feurer Matthias","year":"2019","unstructured":"Matthias Feurer, Aaron Klein, Katharina Eggensperger, Jost Tobias Springenberg, Manuel Blum, and Frank Hutter. 2019. Auto-sklearn: Efficient and robust automated machine learning. In Proceedings of the Automated Machine Learning. Springer International Publishing, 113\u2013134. DOI:https:\/\/doi.org\/10.1007\/978-3-030-05318-5_6"},{"issue":"1","key":"e_1_3_2_56_2","doi-asserted-by":"crossref","first-page":"34","DOI":"10.1145\/3375572.3375582","article-title":"MALTESQUE 2019 workshop summary","volume":"45","author":"Fontana Francesca Arcelli","year":"2020","unstructured":"Francesca Arcelli Fontana, Gilles Perrouin, Apostolos Ampatzoglou, Mathieu Archer, Bartosz Walter, Maxime Cordy, Fabio Palomba, and Xavier Devroey. 2020. MALTESQUE 2019 workshop summary. SIGSOFT Softw. Eng. Notes 45, 1 (Jan.2020), 34\u201335. DOI:https:\/\/doi.org\/10.1145\/3375572.3375582","journal-title":"SIGSOFT Softw. Eng. Notes"},{"issue":"9","key":"e_1_3_2_57_2","doi-asserted-by":"crossref","first-page":"1779","DOI":"10.1109\/TKDE.2018.2866842","article-title":"Real-time data retrieval in cyber-physical systems with temporal validity and data availability constraints","volume":"31","author":"Fu Chenchen","year":"2019","unstructured":"Chenchen Fu, Qiangqiang Liu, Peng Wu, Minming Li, Chun Jason Xue, Yingchao Zhao, Jingtong Hu, and Song Han. 2019. Real-time data retrieval in cyber-physical systems with temporal validity and data availability constraints. IEEE Trans. Knowl. Data Eng. 31, 9 (Sept.2019), 1779\u20131793. DOI:https:\/\/doi.org\/10.1109\/tkde.2018.2866842","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"e_1_3_2_58_2","doi-asserted-by":"crossref","first-page":"195","DOI":"10.1016\/j.infsof.2016.09.002","article-title":"A systematic literature review of literature reviews in software testing","volume":"80","author":"Garousi Vahid","year":"2016","unstructured":"Vahid Garousi and Mika V. M\u00e4ntyl\u00e4. 2016. A systematic literature review of literature reviews in software testing. Info. Softw. Technol. 80, C (Dec.2016), 195\u2013216. DOI:https:\/\/doi.org\/10.1016\/j.infsof.2016.09.002","journal-title":"Info. Softw. Technol."},{"key":"e_1_3_2_59_2","doi-asserted-by":"crossref","first-page":"106","DOI":"10.1016\/j.infsof.2016.07.006","article-title":"Challenges and best practices in industry-academia collaborations in software engineering: A systematic literature review","volume":"79","author":"Garousi Vahid","year":"2016","unstructured":"Vahid Garousi, Kai Petersen, and Baris Ozkan. 2016. Challenges and best practices in industry-academia collaborations in software engineering: A systematic literature review. Info. Softw. Technol. 79 (2016), 106\u2013127. DOI:https:\/\/doi.org\/10.1016\/j.infsof.2016.07.006","journal-title":"Info. Softw. Technol."},{"key":"e_1_3_2_60_2","first-page":"42","volume-title":"Proceedings of the 27th IEEE\/ACM International Conference on Program Comprehension (ICPC\u201919)","author":"Gon\u00e7ales Lucian","year":"2019","unstructured":"Lucian Gon\u00e7ales, Kleinner Farias, Bruno da Silva, and Jonathan Fessler. 2019. Measuring the cognitive load of software developers: A systematic mapping study. In Proceedings of the 27th IEEE\/ACM International Conference on Program Comprehension (ICPC\u201919). IEEE, 42\u201352. DOI:https:\/\/doi.org\/10.1109\/ICPC.2019.00018"},{"key":"e_1_3_2_61_2","article-title":"Measuring the cognitive load of software developers: An extended systematic mapping study","volume":"136","author":"Gon\u00e7ales Lucian Jos\u00e9","year":"2021","unstructured":"Lucian Jos\u00e9 Gon\u00e7ales, Kleinner Farias, and Bruno C. da Silva. 2021. Measuring the cognitive load of software developers: An extended systematic mapping study. Info. Softw. Technol. 136, C (Aug.2021), 30. DOI:https:\/\/doi.org\/10.1016\/j.infsof.2021.106563","journal-title":"Info. Softw. Technol."},{"key":"e_1_3_2_62_2","first-page":"933","volume-title":"Proceedings of the 40th International Conference on Software Engineering (ICSE\u201918)","author":"Gu Xiaodong","year":"2018","unstructured":"Xiaodong Gu, Hongyu Zhang, and Sunghun Kim. 2018. Deep code search. In Proceedings of the 40th International Conference on Software Engineering (ICSE\u201918). ACM, 933\u2013944. DOI:https:\/\/doi.org\/10.1145\/3180155.3180167"},{"key":"e_1_3_2_63_2","doi-asserted-by":"crossref","first-page":"1276","DOI":"10.1109\/TSE.2011.103","article-title":"A systematic literature review on fault prediction performance in software engineering","volume":"38","author":"Hall Tracy","year":"2012","unstructured":"Tracy Hall, Sarah Beecham, David Bowes, David Gray, and Steve Counsell. 2012. A systematic literature review on fault prediction performance in software engineering. IEEE Trans. Softw. Eng. 38 (2012), 1276\u20131304. DOI:https:\/\/doi.org\/10.1109\/TSE.2011.103","journal-title":"IEEE Trans. Softw. Eng."},{"key":"e_1_3_2_64_2","first-page":"17","volume-title":"Proceedings of the 6th International Conference on Global Software Engineering Workshop (ICGSE-W\u201911)","author":"Hanssen Geir K.","year":"2011","unstructured":"Geir K. Hanssen, Darja \u0160mite, and Nils Brede Moe. 2011. Signs of agile trends in global software engineering research: A tertiary study. In Proceedings of the 6th International Conference on Global Software Engineering Workshop (ICGSE-W\u201911). IEEE Computer Society, 17\u201323. DOI:https:\/\/doi.org\/10.1109\/ICGSE-W.2011.12"},{"issue":"11","key":"e_1_3_2_65_2","doi-asserted-by":"crossref","first-page":"793","DOI":"10.1038\/s41562-018-0444-y","article-title":"Mapping the universe of registered reports","volume":"2","author":"Hardwicke Tom E.","year":"2018","unstructured":"Tom E. Hardwicke and John P. A. Ioannidis. 2018. Mapping the universe of registered reports. Nature Hum. Behav. 2, 11 (2018), 793\u2013796.","journal-title":"Nature Hum. Behav."},{"key":"e_1_3_2_66_2","first-page":"1","volume-title":"Proceedings of the 1st International Workshop on Realizing AI Synergies in Software Engineering (RAISE\u201912)","author":"Harman Mark","year":"2012","unstructured":"Mark Harman. 2012. The role of artificial intelligence in software engineering. In Proceedings of the 1st International Workshop on Realizing AI Synergies in Software Engineering (RAISE\u201912). 1\u20136. DOI:https:\/\/doi.org\/10.1109\/RAISE.2012.6227961"},{"key":"e_1_3_2_67_2","doi-asserted-by":"crossref","unstructured":"Ruben Heradio David Fernandez-Amoros Cristina Cerrada and Manuel Cobo. 2021. Machine learning for software engineering: A bibliometric analysis from 2015 to 2019. DOI:https:\/\/doi.org\/10.24251\/HICSS.2021.235","DOI":"10.24251\/HICSS.2021.235"},{"issue":"2","key":"e_1_3_2_68_2","doi-asserted-by":"crossref","first-page":"111","DOI":"10.1109\/TSE.2017.2770124","article-title":"A systematic literature review and meta-analysis on cross project defect prediction","volume":"45","author":"Hosseini Seyedrebvar","year":"2019","unstructured":"Seyedrebvar Hosseini, Burak Turhan, and Dimuthu Gunarathna. 2019. A systematic literature review and meta-analysis on cross project defect prediction. IEEE Trans. Softw. Eng. 45, 2 (Feb.2019), 111\u2013147. DOI:https:\/\/doi.org\/10.1109\/TSE.2017.2770124","journal-title":"IEEE Trans. Softw. Eng."},{"key":"e_1_3_2_69_2","volume-title":"Proceedings of the International Workshop on the Development of Intelligent Information Systems","author":"Huff K. E.","year":"1990","unstructured":"K. E. Huff and O. G Selfridge. 1990. Evolution in future intelligent information systems. In Proceedings of the International Workshop on the Development of Intelligent Information Systems."},{"key":"e_1_3_2_70_2","first-page":"1","volume-title":"Proceedings of the 16th IEEE\/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel\/Distributed Computing (SNPD\u201915)","author":"Idri Ali","year":"2015","unstructured":"Ali Idri, Ibtissam Abnane, and Alain Abran. 2015. Systematic mapping study of missing values techniques in software engineering data. In Proceedings of the 16th IEEE\/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel\/Distributed Computing (SNPD\u201915). IEEE, 1\u20138. DOI:https:\/\/doi.org\/10.1109\/SNPD.2015.7176280"},{"key":"e_1_3_2_71_2","doi-asserted-by":"crossref","first-page":"151","DOI":"10.1016\/j.jss.2016.05.016","article-title":"Systematic literature review of ensemble effort estimation","volume":"118","author":"Idri Ali","year":"2016","unstructured":"Ali Idri, Mohamed Hosni, and Alain Abran. 2016. Systematic literature review of ensemble effort estimation. J. Syst. Softw. 118, C (Aug.2016), 151\u2013175. DOI:https:\/\/doi.org\/10.1016\/j.jss.2016.05.016","journal-title":"J. Syst. Softw."},{"key":"e_1_3_2_72_2","first-page":"132","volume-title":"Proceedings of the 11th International Conference on Evaluation of Novel Software Approaches to Software Engineering (ENASE\u201916)","author":"Idri Ali","year":"2016","unstructured":"Ali Idri, Mohamed Hosni, and Alain Abran. 2016. Systematic mapping study of ensemble effort estimation. In Proceedings of the 11th International Conference on Evaluation of Novel Software Approaches to Software Engineering (ENASE\u201916). 132\u2013139. DOI:https:\/\/doi.org\/10.5220\/0005822701320139"},{"key":"e_1_3_2_73_2","unstructured":"IEEE-CS Professional & Educational Activities Board (PEAB) SWEBOK Evolution Team. 2022. IEEE-CS SWEBOK V4 Public Review. Retrieved from https:\/\/www.computer.org\/volunteering\/boards-and-committees\/professional-educational-activities\/software-engineering-committee\/swebok-evolution.Accessed November 2022."},{"key":"e_1_3_2_74_2","doi-asserted-by":"crossref","first-page":"177","DOI":"10.1145\/2460999.2461025","volume-title":"Proceedings of the 17th International Conference on Evaluation and Assessment in Software Engineering (EASE\u201913)","author":"Imtiaz Salma","year":"2013","unstructured":"Salma Imtiaz, Muneera Bano, Naveed Ikram, and Mahmood Niazi. 2013. A tertiary study: Experiences of conducting systematic literature reviews in software engineering. In Proceedings of the 17th International Conference on Evaluation and Assessment in Software Engineering (EASE\u201913). ACM, New York, NY, 177\u2013182. DOI:https:\/\/doi.org\/10.1145\/2460999.2461025"},{"issue":"7386","key":"e_1_3_2_75_2","doi-asserted-by":"crossref","first-page":"485","DOI":"10.1038\/nature10836","article-title":"The case for open computer programs","volume":"482","author":"Ince Darrel C.","year":"2012","unstructured":"Darrel C. Ince, Leslie Hatton, and John Graham-Cumming. 2012. The case for open computer programs. Nature 482, 7386 (2012), 485\u2013488.","journal-title":"Nature"},{"key":"e_1_3_2_76_2","first-page":"111","volume-title":"Proceedings of the 7th Joint Meeting of the European Software Engineering Conference and the ACM SIGSOFT Symposium on The Foundations of Software Engineering (ESEC\/FSE\u201909)","author":"Jeong Gaeul","year":"2009","unstructured":"Gaeul Jeong, Sunghun Kim, and Thomas Zimmermann. 2009. Improving bug triage with bug tossing graphs. In Proceedings of the 7th Joint Meeting of the European Software Engineering Conference and the ACM SIGSOFT Symposium on The Foundations of Software Engineering (ESEC\/FSE\u201909). ACM, New York, NY, 111\u2013120. DOI:https:\/\/doi.org\/10.1145\/1595696.1595715"},{"key":"e_1_3_2_77_2","doi-asserted-by":"crossref","first-page":"33","DOI":"10.1109\/TSE.2007.256943","article-title":"A systematic review of software development cost estimation studies","volume":"33","author":"J\u00f8rgensen Magne","year":"2007","unstructured":"Magne J\u00f8rgensen and Martin Shepperd. 2007. A systematic review of software development cost estimation studies. IEEE Trans. Softw. Eng. 33 (Feb.2007), 33\u201353. DOI:https:\/\/doi.org\/10.1109\/TSE.2007.256943","journal-title":"IEEE Trans. Softw. Eng."},{"key":"e_1_3_2_78_2","volume-title":"Proceedings of the International Conference on Advances in Computing, Communication Control and Networking (ICACCCN\u201918)","author":"Kaur Arvinder","year":"2018","unstructured":"Arvinder Kaur and Shubhra Goyal Jindal. 2018. Severity prediction of bug reports using text mining: A systematic review. In Proceedings of the International Conference on Advances in Computing, Communication Control and Networking (ICACCCN\u201918). IEEE. DOI:https:\/\/doi.org\/10.1109\/icacccn.2018.8748582"},{"issue":"2","key":"e_1_3_2_79_2","article-title":"Effective regression test case selection: A systematic literature review","volume":"50","author":"Kazmi Rafaqut","year":"2017","unstructured":"Rafaqut Kazmi, Dayang N. A. Jawawi, Radziah Mohamad, and Imran Ghani. 2017. Effective regression test case selection: A systematic literature review. Comput. Surveys 50, 2 (June2017), 32. DOI:https:\/\/doi.org\/10.1145\/3057269","journal-title":"Comput. Surveys"},{"key":"e_1_3_2_80_2","doi-asserted-by":"crossref","first-page":"166262","DOI":"10.1109\/ACCESS.2021.3135508","article-title":"Trend application of machine learning in test case prioritization: A review on techniques","volume":"9","author":"Khatibsyarbini Muhammad","year":"2021","unstructured":"Muhammad Khatibsyarbini, Mohd Adham Isa, Dayang N. A. Jawawi, Muhammad Luqman Mohd Shafie, Wan Mohd Nasir Wan-Kadir, Haza Nuzly Abdull Hamed, and Muhammad Dhiauddin Mohamed Suffian. 2021. Trend application of machine learning in test case prioritization: A review on techniques. IEEE Access 9 (2021), 166262\u2013166282. DOI:https:\/\/doi.org\/10.1109\/access.2021.3135508","journal-title":"IEEE Access"},{"key":"e_1_3_2_81_2","doi-asserted-by":"crossref","first-page":"89093","DOI":"10.1109\/ACCESS.2019.2926384","article-title":"A comprehensive investigation of modern test suite optimization trends, tools and techniques","volume":"7","author":"Kiran Ayesha","year":"2019","unstructured":"Ayesha Kiran, Wasi H. Butt, Muhammad W. Anwar, Farooque Azam, and Bilal Maqbool. 2019. A comprehensive investigation of modern test suite optimization trends, tools and techniques. IEEE Access 7 (2019), 89093\u201389117. DOI:https:\/\/doi.org\/10.1109\/ACCESS.2019.2926384","journal-title":"IEEE Access"},{"key":"e_1_3_2_82_2","article-title":"Procedures for performing systematic reviews","author":"Kitchenham Barbara","year":"2004","unstructured":"Barbara Kitchenham. 2004. Procedures for performing systematic reviews. Keele University Technical Report TR\/SE-0401, Keele, UK.","journal-title":"Keele University Technical Report TR\/SE-0401, Keele, UK"},{"issue":"12","key":"e_1_3_2_83_2","doi-asserted-by":"crossref","first-page":"2049","DOI":"10.1016\/j.infsof.2013.07.010","article-title":"A systematic review of systematic review process research in software engineering","volume":"55","author":"Kitchenham Barbara","year":"2013","unstructured":"Barbara Kitchenham and Pearl Brereton. 2013. A systematic review of systematic review process research in software engineering. Info. Softw. Technol. 55, 12 (Dec.2013), 2049\u20132075. DOI:https:\/\/doi.org\/10.1016\/j.infsof.2013.07.010","journal-title":"Info. Softw. Technol."},{"key":"e_1_3_2_84_2","unstructured":"Barbara Kitchenham and Stuart Charters. 2007. Guidelines for performing systematic literature reviews in software engineering. EBSE Technical Report EBSE-2007-01."},{"issue":"1","key":"e_1_3_2_85_2","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1016\/j.infsof.2008.09.009","article-title":"Systematic literature reviews in software engineering\u2014A systematic literature review","volume":"51","author":"Kitchenham Barbara","year":"2009","unstructured":"Barbara Kitchenham, O. Pearl Brereton, David Budgen, Mark Turner, John Bailey, and Stephen Linkman. 2009. Systematic literature reviews in software engineering\u2014A systematic literature review. Info. Softw. Technol. 51, 1 (Jan.2009), 7\u201315. DOI:https:\/\/doi.org\/10.1016\/j.infsof.2008.09.009","journal-title":"Info. Softw. Technol."},{"issue":"8","key":"e_1_3_2_86_2","doi-asserted-by":"crossref","first-page":"792","DOI":"10.1016\/j.infsof.2010.03.006","article-title":"Systematic literature reviews in software engineering\u2014A tertiary study","volume":"52","author":"Kitchenham Barbara","year":"2010","unstructured":"Barbara Kitchenham, Rialette Pretorius, David Budgen, O. Pearl Brereton, Mark Turner, Mahmood Niazi, and Stephen Linkman. 2010. Systematic literature reviews in software engineering\u2014A tertiary study. Info. Softw. Technol. 52, 8 (Aug.2010), 792\u2013805. DOI:https:\/\/doi.org\/10.1016\/j.infsof.2010.03.006","journal-title":"Info. Softw. Technol."},{"key":"e_1_3_2_87_2","doi-asserted-by":"crossref","DOI":"10.1201\/b19467","volume-title":"Evidence-based Software Engineering and Systematic Reviews","author":"Kitchenham Barbara Ann","year":"2015","unstructured":"Barbara Ann Kitchenham, David Budgen, and Pearl Brereton. 2015. Evidence-based Software Engineering and Systematic Reviews. Chapman & Hall\/CRC."},{"issue":"6","key":"e_1_3_2_88_2","doi-asserted-by":"crossref","first-page":"638","DOI":"10.1016\/j.infsof.2010.12.011","article-title":"Using mapping studies as the basis for further research\u2014A participant-observer case study","volume":"53","author":"Kitchenham Barbara A.","year":"2011","unstructured":"Barbara A. Kitchenham, David Budgen, and O. Pearl Brereton. 2011. Using mapping studies as the basis for further research\u2014A participant-observer case study. Info. Softw. Technol. 53, 6 (June2011), 638\u2013651. DOI:https:\/\/doi.org\/10.1016\/j.infsof.2010.12.011","journal-title":"Info. Softw. Technol."},{"key":"e_1_3_2_89_2","doi-asserted-by":"crossref","first-page":"3288","DOI":"10.1007\/s10664-020-09834-7","article-title":"Standing on shoulders or feet? An extended study on the usage of the MSR data papers","volume":"25","author":"Kotti Zoe","year":"2020","unstructured":"Zoe Kotti, Konstantinos Kravvaritis, Konstantina Dritsa, and Diomidis Spinellis. 2020. Standing on shoulders or feet? An extended study on the usage of the MSR data papers. Empir. Softw. Eng. 25 (July2020), 3288\u20133322. DOI:https:\/\/doi.org\/10.1007\/s10664-020-09834-7","journal-title":"Empir. Softw. Eng."},{"key":"e_1_3_2_90_2","first-page":"140","volume-title":"Proceedings of the 42th Euromicro Conference on Software Engineering and Advanced Applications (SEAA\u201916)","author":"Koutbi Salma E.","year":"2016","unstructured":"Salma E. Koutbi, Ali Idri, and Alain Abran. 2016. Systematic mapping study of dealing with error in software development effort estimation. In Proceedings of the 42th Euromicro Conference on Software Engineering and Advanced Applications (SEAA\u201916). IEEE, 140\u2013147. DOI:https:\/\/doi.org\/10.1109\/SEAA.2016.39"},{"key":"e_1_3_2_91_2","volume-title":"Content Analysis: An Introduction to Its Methodology (4th ed.)","author":"Krippendorff Klaus","year":"2018","unstructured":"Klaus Krippendorff. 2018. Content Analysis: An Introduction to Its Methodology (4th ed.). SAGE Publications."},{"issue":"3","key":"e_1_3_2_92_2","first-page":"62","article-title":"Deep learning for source code modeling and generation: Models, applications, and challenges","volume":"53","author":"Le Triet H. M.","year":"2020","unstructured":"Triet H. M. Le, Hao Chen, and Muhammad Ali Babar. 2020. Deep learning for source code modeling and generation: Models, applications, and challenges. Comput. Surveys 53, 3, Article 62 (June2020), 38 pages. DOI:https:\/\/doi.org\/10.1145\/3383458","journal-title":"Comput. Surveys"},{"key":"e_1_3_2_93_2","first-page":"27","volume-title":"Proceedings of the 26th International Symposium on Static Analysis","author":"Lei Yuxiang","year":"2019","unstructured":"Yuxiang Lei and Yulei Sui. 2019. Fast and precise handling of positive weight cycles for field-sensitive pointer analysis. In Proceedings of the 26th International Symposium on Static Analysis. Springer-Verlag, Berlin, 27\u201347. DOI:https:\/\/doi.org\/10.1007\/978-3-030-32304-2_3"},{"key":"e_1_3_2_94_2","first-page":"285","volume-title":"Code Smells Detection Using Artificial Intelligence Techniques: A Business-Driven Systematic Review","author":"Lewowski Tomasz","year":"2022","unstructured":"Tomasz Lewowski and Lech Madeyski. 2022. Code Smells Detection Using Artificial Intelligence Techniques: A Business-Driven Systematic Review. Springer International Publishing, Cham, 285\u2013319. DOI:https:\/\/doi.org\/10.1007\/978-3-030-77916-0_12"},{"key":"e_1_3_2_95_2","article-title":"A survey on renamings of software entities","volume":"53","author":"Li Guangjie","year":"2020","unstructured":"Guangjie Li, Hui Liu, and Ally S. Nyamawe. 2020. A survey on renamings of software entities. Comput. Surveys 53 (April2020). DOI:https:\/\/doi.org\/10.1145\/3379443","journal-title":"Comput. Surveys"},{"issue":"1","key":"e_1_3_2_96_2","first-page":"1","article-title":"Improving software quality and productivity leveraging mining techniques: [Summary of the second workshop on software mining at ASE 2013]","volume":"40","author":"Li Ming","year":"2015","unstructured":"Ming Li, Hongyu Zhang, David Lo, and Lucia. 2015. Improving software quality and productivity leveraging mining techniques: [Summary of the second workshop on software mining at ASE 2013]. SIGSOFT Softw. Eng. Notes 40, 1 (Feb.2015), 1\u20132. DOI:https:\/\/doi.org\/10.1145\/2693208.2693219","journal-title":"SIGSOFT Softw. Eng. Notes"},{"key":"e_1_3_2_97_2","first-page":"133","volume-title":"Proceedings of the 21st International Systems and Software Product Line Conference\u2014Volume A (SPLC\u201917)","author":"Li Yang","year":"2017","unstructured":"Yang Li, Sandro Schulze, and Gunter Saake. 2017. Reverse engineering variability from natural language documents: A systematic literature review. In Proceedings of the 21st International Systems and Software Product Line Conference\u2014Volume A (SPLC\u201917). ACM, 133\u2013142. DOI:https:\/\/doi.org\/10.1145\/3106195.3106207"},{"key":"e_1_3_2_98_2","volume-title":"Guidelines for Conducting Surveys in Software Engineering","author":"Lin\u00e5ker Johan","year":"2015","unstructured":"Johan Lin\u00e5ker, Sardar Muhammad Sulaman, Rafael Maiani de Mello, and Martin H\u00f6st. 2015. Guidelines for Conducting Surveys in Software Engineering. Department of Computer Science, Lund University."},{"issue":"1","key":"e_1_3_2_99_2","first-page":"39","article-title":"Software effort estimation accuracy prediction of machine learning techniques: A systematic performance evaluation","volume":"52","author":"Mahmood Yasir","year":"2022","unstructured":"Yasir Mahmood, Nazri Kama, Azri Azmi, Ahmad Salman Khan, and Mazlan Ali. 2022. Software effort estimation accuracy prediction of machine learning techniques: A systematic performance evaluation. Softw.: Pract. Exper. 52, 1 (2022), 39\u201365. DOI:https:\/\/doi.org\/10.1002\/spe.3009","journal-title":"Softw.: Pract. Exper."},{"key":"e_1_3_2_100_2","doi-asserted-by":"crossref","first-page":"504","DOI":"10.1016\/j.asoc.2014.11.023","article-title":"A systematic review of machine learning techniques for software fault prediction","volume":"27","author":"Malhotra Ruchika","year":"2015","unstructured":"Ruchika Malhotra. 2015. A systematic review of machine learning techniques for software fault prediction. Appl. Soft Comput. 27 (Feb.2015), 504\u2013518. DOI:https:\/\/doi.org\/10.1016\/j.asoc.2014.11.023","journal-title":"Appl. Soft Comput."},{"key":"e_1_3_2_101_2","first-page":"1","volume-title":"Proceedings of the 4th International Conference on Reliability, Infocom Technologies and Optimization (ICRITO\u201915)","author":"Malhotra Ruchika","year":"2015","unstructured":"Ruchika Malhotra and Ankita Bansal. 2015. Predicting change using software metrics: A review. In Proceedings of the 4th International Conference on Reliability, Infocom Technologies and Optimization (ICRITO\u201915). IEEE, 1\u20136. DOI:https:\/\/doi.org\/10.1109\/ICRITO.2015.7359253"},{"key":"e_1_3_2_102_2","doi-asserted-by":"crossref","first-page":"240","DOI":"10.1504\/IJCAT.2016.080487","article-title":"Software change prediction: A literature review","volume":"54","author":"Malhotra Ruchika","year":"2016","unstructured":"Ruchika Malhotra and Ankita J. Bansal. 2016. Software change prediction: A literature review. Int. J. Comput. Appl. Technol. 54 (Jan.2016), 240\u2013256. DOI:https:\/\/doi.org\/10.1504\/IJCAT.2016.080487","journal-title":"Int. J. Comput. Appl. Technol."},{"issue":"08","key":"e_1_3_2_103_2","doi-asserted-by":"crossref","first-page":"1221","DOI":"10.1142\/S0218194016500431","article-title":"Software maintainability: Systematic literature review and current trends","volume":"26","author":"Malhotra Ruchika","year":"2016","unstructured":"Ruchika Malhotra and Anuradha Chug. 2016. Software maintainability: Systematic literature review and current trends. Int. J. Softw. Eng. Knowl. Eng. 26, 08 (Oct.2016), 1221\u20131253. DOI:https:\/\/doi.org\/10.1142\/s0218194016500431","journal-title":"Int. J. Softw. Eng. Knowl. Eng."},{"issue":"1","key":"e_1_3_2_104_2","first-page":"227","article-title":"Software change prediction: A systematic review and future guidelines","volume":"13","author":"Malhotra Ruchika","year":"2019","unstructured":"Ruchika Malhotra and Megha Khanna. 2019. Software change prediction: A systematic review and future guidelines. e-Informat. Softw. Eng. J. 13, 1 (2019), 227\u2013259. DOI:https:\/\/doi.org\/10.5277\/E-INF190107","journal-title":"e-Informat. Softw. Eng. J."},{"key":"e_1_3_2_105_2","doi-asserted-by":"crossref","first-page":"85","DOI":"10.1016\/j.swevo.2016.10.002","article-title":"On the application of search-based techniques for software engineering predictive modeling: A systematic review and future directions","volume":"32","author":"Malhotra Ruchika","year":"2017","unstructured":"Ruchika Malhotra, Megha Khanna, and Rajeev R. Raje. 2017. On the application of search-based techniques for software engineering predictive modeling: A systematic review and future directions. Swarm Evolution. Comput. 32 (Feb.2017), 85\u2013109. DOI:https:\/\/doi.org\/10.1016\/j.swevo.2016.10.002","journal-title":"Swarm Evolution. Comput."},{"issue":"21","key":"e_1_3_2_106_2","doi-asserted-by":"crossref","first-page":"16655","DOI":"10.1007\/s00500-020-05005-4","article-title":"A systematic literature review on empirical studies towards prediction of software maintainability","volume":"24","author":"Malhotra Ruchika","year":"2020","unstructured":"Ruchika Malhotra and Kusum Lata. 2020. A systematic literature review on empirical studies towards prediction of software maintainability. Soft Comput. 24, 21 (May2020), 16655\u201316677. DOI:https:\/\/doi.org\/10.1007\/s00500-020-05005-4","journal-title":"Soft Comput."},{"key":"e_1_3_2_107_2","doi-asserted-by":"crossref","first-page":"143","DOI":"10.1145\/3106195.3106212","volume-title":"Proceedings of the 21st International Systems and Software Product Line Conference\u2014Volume A (SPLC\u201917)","author":"Marimuthu C.","year":"2017","unstructured":"C. Marimuthu and K. Chandrasekaran. 2017. Systematic studies in software product lines: A tertiary study. In Proceedings of the 21st International Systems and Software Product Line Conference\u2014Volume A (SPLC\u201917). ACM, New York, NY, 143\u2013152. DOI:https:\/\/doi.org\/10.1145\/3106195.3106212"},{"key":"e_1_3_2_108_2","first-page":"134","volume-title":"Proceedings of the IEEE Seventh International Conference on Global Software Engineering","author":"Marques Anna Beatriz","year":"2012","unstructured":"Anna Beatriz Marques, Rosiane Rodrigues, and Tayana Conte. 2012. Systematic literature reviews in distributed software development: A tertiary study. In Proceedings of the IEEE Seventh International Conference on Global Software Engineering. 134\u2013143. DOI:https:\/\/doi.org\/10.1109\/ICGSE.2012.29"},{"issue":"4","key":"e_1_3_2_109_2","doi-asserted-by":"crossref","first-page":"1160","DOI":"10.1016\/j.joi.2018.09.002","article-title":"Google scholar, web of science, and scopus: A systematic comparison of citations in 252 subject categories","volume":"12","author":"Mart\u00edn-Mart\u00edn Alberto","year":"2018","unstructured":"Alberto Mart\u00edn-Mart\u00edn, Enrique Orduna-Malea, Mike Thelwall, and Emilio Delgado L\u00f3pez-C\u00f3zar. 2018. Google scholar, web of science, and scopus: A systematic comparison of citations in 252 subject categories. J. Informetr. 12, 4 (Nov.2018), 1160\u20131177. DOI:https:\/\/doi.org\/10.1016\/j.joi.2018.09.002","journal-title":"J. Informetr."},{"issue":"2","key":"e_1_3_2_110_2","first-page":"37e","article-title":"Software engineering for AI-based systems: A survey","volume":"31","author":"Mart\u00ednez-Fern\u00e1ndez Silverio","year":"2022","unstructured":"Silverio Mart\u00ednez-Fern\u00e1ndez, Justus Bogner, Xavier Franch, Marc Oriol, Julien Siebert, Adam Trendowicz, Anna Maria Vollmer, and Stefan Wagner. 2022. Software engineering for AI-based systems: A survey. ACM Trans. Softw. Eng. Methodol. 31, 2, Article 37e (April2022), 59 pages. DOI:https:\/\/doi.org\/10.1145\/3487043","journal-title":"ACM Trans. Softw. Eng. Methodol."},{"key":"e_1_3_2_111_2","volume-title":"Proceedings of the 1st IEEE International Conference on Hot Information-Centric Networking (HotICN\u201918)","author":"Mastorakis Spyridon","year":"2018","unstructured":"Spyridon Mastorakis, Peter Gusev, Alexander Afanasyev, and Lixia Zhang. 2018. Real-time data retrieval in named data networking. In Proceedings of the 1st IEEE International Conference on Hot Information-Centric Networking (HotICN\u201918). IEEE. DOI:https:\/\/doi.org\/10.1109\/hoticn.2018.8605992"},{"issue":"2","key":"e_1_3_2_112_2","doi-asserted-by":"crossref","first-page":"403","DOI":"10.32604\/iasc.2021.017562","article-title":"Software defect prediction using supervised machine learning techniques: A systematic literature review","volume":"29","author":"Matloob Faseeha","year":"2021","unstructured":"Faseeha Matloob, Shabib Aftab, Munir Ahmad, Muhammad Adnan Khan, Areej Fatima, Muhammad Iqbal, Wesam Mohsen Alruwaili, and Nouh Sabri Elmitwally. 2021. Software defect prediction using supervised machine learning techniques: A systematic literature review. Intell. Autom. Soft Comput. 29, 2 (2021), 403\u2013421. DOI:https:\/\/doi.org\/10.32604\/iasc.2021.017562","journal-title":"Intell. Autom. Soft Comput."},{"key":"e_1_3_2_113_2","doi-asserted-by":"crossref","first-page":"175","DOI":"10.1016\/j.compeleceng.2019.02.022","article-title":"A systematic literature review and meta-analysis on artificial intelligence in penetration testing and vulnerability assessment","volume":"75","author":"McKinnel Dean Richard","year":"2019","unstructured":"Dean Richard McKinnel, Tooska Dargahi, Ali Dehghantanha, and Kim-Kwang Raymond Choo. 2019. A systematic literature review and meta-analysis on artificial intelligence in penetration testing and vulnerability assessment. Comput. Electr. Eng. 75, C (May2019), 175\u2013188. DOI:https:\/\/doi.org\/10.1016\/j.compeleceng.2019.02.022","journal-title":"Comput. Electr. Eng."},{"key":"e_1_3_2_114_2","doi-asserted-by":"crossref","first-page":"548","DOI":"10.1145\/3183440.3183461","volume-title":"Proceedings of the 40th International Conference on Software Engineering: Companion Proceedings (ICSE\u201918)","author":"Meinke Karl","year":"2018","unstructured":"Karl Meinke and Amel Bennaceur. 2018. Machine learning for software engineering: Models, methods, and applications. In Proceedings of the 40th International Conference on Software Engineering: Companion Proceedings (ICSE\u201918). ACM, New York, NY, 548\u2013549. DOI:https:\/\/doi.org\/10.1145\/3183440.3183461"},{"key":"e_1_3_2_115_2","article-title":"Decision trees-based software development effort estimation: A systematic mapping study","author":"Najm Assia","year":"2019","unstructured":"Assia Najm, Abdelali Zakrani, and Abdelaziz Marzak. 2019. Decision trees-based software development effort estimation: A systematic mapping study. Proceedings of the 2nd International Conference of Computer Science and Renewable Energies. DOI:https:\/\/doi.org\/10.1109\/ICCSRE.2019.8807544","journal-title":"Proceedings of the 2nd International Conference of Computer Science and Renewable Energies"},{"issue":"12","key":"e_1_3_2_116_2","doi-asserted-by":"crossref","first-page":"4679","DOI":"10.1109\/TITS.2019.2924883","article-title":"Online incremental machine learning platform for big data-driven smart traffic management","volume":"20","author":"Nallaperuma Dinithi","year":"2019","unstructured":"Dinithi Nallaperuma, Rashmika Nawaratne, Tharindu Bandaragoda, Achini Adikari, Su Nguyen, Thimal Kempitiya, Daswin De Silva, Damminda Alahakoon, and Dakshan Pothuhera. 2019. Online incremental machine learning platform for big data-driven smart traffic management. IEEE Trans. Intell. Transport. Syst. 20, 12 (Dec.2019), 4679\u20134690. DOI:https:\/\/doi.org\/10.1109\/TITS.2019.2924883","journal-title":"IEEE Trans. Intell. Transport. Syst."},{"key":"e_1_3_2_117_2","doi-asserted-by":"crossref","first-page":"99","DOI":"10.1145\/3364641.3364653","volume-title":"Proceedings of the 28th Brazilian Symposium on Software Quality (SBQS\u201919)","author":"Norberto Marcus","year":"2019","unstructured":"Marcus Norberto, Lukas Gaedicke, Maicon Bernardino, Guilherme Legramante, Fabio Paulo Basso, and Elder Macedo Rodrigues. 2019. Performance testing in mobile application: A systematic literature map. In Proceedings of the 28th Brazilian Symposium on Software Quality (SBQS\u201919). ACM, New York, NY, 99\u2013108. DOI:https:\/\/doi.org\/10.1145\/3364641.3364653"},{"key":"e_1_3_2_118_2","volume-title":"Curriculum Guidelines for Undergraduate Degree Programs in Software Engineering","author":"Curricula The Joint Task Force on Computing","year":"2004","unstructured":"The Joint Task Force on Computing Curricula. 2004. Curriculum Guidelines for Undergraduate Degree Programs in Software Engineering. Technical Report. New York, NY, USA. DOI:https:\/\/doi.org\/10.1145\/2594168"},{"key":"e_1_3_2_119_2","first-page":"659","volume-title":"Proceedings of the 4th International Conference on Technology Trends (CITT\u201918)","author":"Ordo\u00f1ez Pablo F. Ordo\u00f1ez","year":"2018","unstructured":"Pablo F. Ordo\u00f1ez Ordo\u00f1ez, Milton Quizhpe, Oscar M. Cumbicus-Pineda, Valeria Herrera Salazar, and Roberth Figueroa-Diaz. 2018. Application of genetic algorithms in software engineering: A systematic literature review. In Proceedings of the 4th International Conference on Technology Trends (CITT\u201918). Springer International Publishing, 659\u2013670. DOI:https:\/\/doi.org\/10.1007\/978-3-030-05532-5_50"},{"key":"e_1_3_2_120_2","first-page":"532","volume-title":"Proceedings of the 10th Turkish National Software Engineering Symposium (UYMS\u201916)","author":"\u00d6zakinc R.","year":"2016","unstructured":"R. \u00d6zakinc and A. Tarhan. 2016. Yazilim gelistirmede erken asamalarda toplanan verinin hata tahmini performansina etkisi. In Proceedings of the 10th Turkish National Software Engineering Symposium (UYMS\u201916). CEUR-WS, 532\u2013543."},{"key":"e_1_3_2_121_2","doi-asserted-by":"crossref","first-page":"216","DOI":"10.1016\/j.jss.2018.06.025","article-title":"Early software defect prediction: A systematic map and review","volume":"144","author":"\u00d6zak\u0131nc\u0131 Rana","year":"2018","unstructured":"Rana \u00d6zak\u0131nc\u0131 and Ay\u00e7a Tarhan. 2018. Early software defect prediction: A systematic map and review. J. Syst. Softw. 144 (Oct.2018), 216\u2013239. DOI:https:\/\/doi.org\/10.1016\/j.jss.2018.06.025","journal-title":"J. Syst. Softw."},{"key":"e_1_3_2_122_2","doi-asserted-by":"crossref","first-page":"104773","DOI":"10.1016\/j.engappai.2022.104773","article-title":"A systematic literature review on software defect prediction using artificial intelligence: Datasets, data validation methods, approaches, and tools","volume":"111","author":"Pachouly Jalaj","year":"2022","unstructured":"Jalaj Pachouly, Swati Ahirrao, Ketan Kotecha, Ganeshsree Selvachandran, and Ajith Abraham. 2022. A systematic literature review on software defect prediction using artificial intelligence: Datasets, data validation methods, approaches, and tools. Eng. Appl. Artific. Intell. 111 (May2022), 104773. DOI:https:\/\/doi.org\/10.1016\/j.engappai.2022.104773","journal-title":"Eng. Appl. Artific. Intell."},{"key":"e_1_3_2_123_2","doi-asserted-by":"crossref","first-page":"114595","DOI":"10.1016\/j.eswa.2021.114595","article-title":"Machine learning based methods for software fault prediction: A survey","volume":"172","author":"Pandey Sushant Kumar","year":"2021","unstructured":"Sushant Kumar Pandey, Ravi Bhushan Mishra, and Anil Kumar Tripathi. 2021. Machine learning based methods for software fault prediction: A survey. Expert Syst. Appl. 172 (June2021), 114595. DOI:https:\/\/doi.org\/10.1016\/j.eswa.2021.114595","journal-title":"Expert Syst. Appl."},{"key":"e_1_3_2_124_2","article-title":"Learning software configuration spaces: A systematic literature review","volume":"182","author":"Pereira Juliana Alves","year":"2021","unstructured":"Juliana Alves Pereira, Mathieu Acher, Hugo Martin, Jean-Marc J\u00e9z\u00e9quel, Goetz Botterweck, and Anthony Ventresque. 2021. Learning software configuration spaces: A systematic literature review. J. Syst. Softw. 182, C (Dec.2021), 29. DOI:https:\/\/doi.org\/10.1016\/j.jss.2021.111044","journal-title":"J. Syst. Softw."},{"key":"e_1_3_2_125_2","doi-asserted-by":"crossref","first-page":"110657","DOI":"10.1016\/j.jss.2020.110657","article-title":"Systematic literature reviews in software engineering-enhancement of the study selection process using cohen\u2019s kappa statistic","author":"P\u00e9rez Jorge","year":"2020","unstructured":"Jorge P\u00e9rez, Jessica D\u00edaz, Javier Garcia-Martin, and Bernardo Tabuenca. 2020. Systematic literature reviews in software engineering-enhancement of the study selection process using cohen\u2019s kappa statistic. J. Syst. Softw. (2020), 110657.","journal-title":"J. Syst. Softw."},{"key":"e_1_3_2_126_2","article-title":"Intelligent software engineering in the context of agile software development: A systematic literature review","volume":"119","author":"Perkusich Mirko","year":"2020","unstructured":"Mirko Perkusich, Lenardo Chaves e Silva, Alexandre Costa, Felipe Ramos, Renata Saraiva, Arthur Freire, Ednaldo Dilorenzo, Emanuel Dantas, Danilo Santos, Kyller Gorg\u00f4nio, Kyller Almeida, and Angelo Perkusich. 2020. Intelligent software engineering in the context of agile software development: A systematic literature review. Info. Softw. Technol. 119 (Mar.2020). DOI:https:\/\/doi.org\/10.1016\/j.infsof.2019.106241","journal-title":"Info. Softw. Technol."},{"key":"e_1_3_2_127_2","first-page":"68","volume-title":"Proceedings of the 12th International Conference on Evaluation and Assessment in Software Engineering (EASE\u201908)","author":"Petersen Kai","year":"2008","unstructured":"Kai Petersen, Robert Feldt, Shahid Mujtaba, and Michael Mattsson. 2008. Systematic mapping studies in software engineering. In Proceedings of the 12th International Conference on Evaluation and Assessment in Software Engineering (EASE\u201908). BCS Learning & Development, Swindon, GBR, 68\u201377."},{"key":"e_1_3_2_128_2","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.infsof.2015.03.007","article-title":"Guidelines for conducting systematic mapping studies in software engineering: An update","volume":"64","author":"Petersen Kai","year":"2015","unstructured":"Kai Petersen, Sairam Vakkalanka, and Ludwik Kuzniarz. 2015. Guidelines for conducting systematic mapping studies in software engineering: An update. Info. Softw. Technol. 64 (2015), 1\u201318. DOI:https:\/\/doi.org\/10.1016\/j.infsof.2015.03.007","journal-title":"Info. Softw. Technol."},{"key":"e_1_3_2_129_2","doi-asserted-by":"crossref","first-page":"83","DOI":"10.1109\/OJEMB.2020.2981258","article-title":"Overcoming the barriers that obscure the interlinking and analysis of clinical data through harmonization and incremental learning","volume":"1","author":"Pezoulas Vasileios C.","year":"2020","unstructured":"Vasileios C. Pezoulas, Konstantina D. Kourou, Fanis Kalatzis, Themis P. Exarchos, Evi Zampeli, Saviana Gandolfo, Andreas Goules, Chiara Baldini, Fotini Skopouli, Salvatore De Vita, Athanasios G. Tzioufas, and Dimitrios I. Fotiadis. 2020. Overcoming the barriers that obscure the interlinking and analysis of clinical data through harmonization and incremental learning. IEEE Open J. Eng. Med. Biol. 1 (2020), 83\u201390. DOI:https:\/\/doi.org\/10.1109\/OJEMB.2020.2981258","journal-title":"IEEE Open J. Eng. Med. Biol."},{"issue":"3","key":"e_1_3_2_130_2","doi-asserted-by":"crossref","first-page":"856","DOI":"10.5465\/amj.2012.0458","article-title":"Distant search, narrow attention: How crowding alters organizations\u2019 filtering of suggestions in crowdsourcing","volume":"58","author":"Piezunka Henning","year":"2015","unstructured":"Henning Piezunka and Linus Dahlander. 2015. Distant search, narrow attention: How crowding alters organizations\u2019 filtering of suggestions in crowdsourcing. Acad. Manage. J. 58, 3 (2015), 856\u2013880. DOI:https:\/\/doi.org\/10.5465\/amj.2012.0458","journal-title":"Acad. Manage. J."},{"key":"e_1_3_2_131_2","first-page":"833","volume-title":"Proceedings of the TENCON IEEE Region 10 Conference","author":"Pillai Sreekumar P.","year":"2017","unstructured":"Sreekumar P. Pillai, S. D. Madhukumar, and T. Radharamanan. 2017. Consolidating evidence based studies in software cost\/effort estimation\u2014A tertiary study. In Proceedings of the TENCON IEEE Region 10 Conference. 833\u2013838. DOI:https:\/\/doi.org\/10.1109\/TENCON.2017.8227974"},{"key":"e_1_3_2_132_2","unstructured":"Critical Appraisal Skills Programme. 2022. CASP Systematic Review Checklist. Retrieved from https:\/\/casp-uk.net\/casp-tools-checklists\/.Accessed July 2022."},{"key":"e_1_3_2_133_2","volume-title":"Proceedings of the 21st International Workshop on Design, Optimization, Languages and Analytical Processing of Big Data (DOLAP\u201919)","volume":"2324","author":"Quemy Alexandre","year":"2019","unstructured":"Alexandre Quemy. 2019. Data pipeline selection and optimization. In Proceedings of the 21st International Workshop on Design, Optimization, Languages and Analytical Processing of Big Data (DOLAP\u201919), Vol. 2324. CEUR-WS.org."},{"key":"e_1_3_2_134_2","unstructured":"Lukasz Radlinski. 2010. A Survey of Bayesian Net Models for Software Development Effort Prediction. Int. J. Softw. Eng. Comput. 2 2 (July2010) 95\u2013109."},{"issue":"9","key":"e_1_3_2_135_2","article-title":"A systematic literature review on regression test case prioritization","volume":"12","author":"Rahmani Ani","year":"2021","unstructured":"Ani Rahmani, Sabrina Ahmad, Intan Ermahani A. Jalil, and Adhitia Putra Herawan. 2021. A systematic literature review on regression test case prioritization. Int. J. Adv. Comput. Sci. Appl. 12, 9 (2021). DOI:https:\/\/doi.org\/10.14569\/ijacsa.2021.0120929","journal-title":"Int. J. Adv. Comput. Sci. Appl."},{"key":"e_1_3_2_136_2","doi-asserted-by":"crossref","first-page":"11816","DOI":"10.1109\/ACCESS.2018.2809600","article-title":"A systematic review on test suite reduction: Approaches, experiment\u2019s quality evaluation, and guidelines","volume":"6","author":"Khan Saif U. Rehman","year":"2018","unstructured":"Saif U. Rehman Khan, Sai P. Lee, Nadeem Javaid, and Wadood Abdul. 2018. A systematic review on test suite reduction: Approaches, experiment\u2019s quality evaluation, and guidelines. IEEE Access 6 (Feb.2018), 11816\u201311841. DOI:https:\/\/doi.org\/10.1109\/ACCESS.2018.2809600","journal-title":"IEEE Access"},{"key":"e_1_3_2_137_2","doi-asserted-by":"crossref","first-page":"367","DOI":"10.1109\/ESEM.2009.5314233","volume-title":"Proceedings of the 3rd International Symposium on Empirical Software Engineering and Measurement (ESEM\u201909)","author":"Riaz Mehwish","year":"2009","unstructured":"Mehwish Riaz, Emilia Mendes, and Ewan Tempero. 2009. A systematic review of software maintainability prediction and metrics. In Proceedings of the 3rd International Symposium on Empirical Software Engineering and Measurement (ESEM\u201909). IEEE, 367\u2013377. DOI:https:\/\/doi.org\/10.1109\/ESEM.2009.5314233"},{"key":"e_1_3_2_138_2","doi-asserted-by":"crossref","first-page":"396","DOI":"10.1145\/2597073.2597129","volume-title":"Proceedings of the 11th Working Conference on Mining Software Repositories (MSR\u201914)","author":"Robles Gregorio","year":"2014","unstructured":"Gregorio Robles, Laura Arjona Reina, Alexander Serebrenik, Bogdan Vasilescu, and Jes\u00fas M. Gonz\u00e1lez-Barahona. 2014. FLOSS 2013: A survey dataset about free software contributors: Challenges for curating, sharing, and combining. In Proceedings of the 11th Working Conference on Mining Software Repositories (MSR\u201914). ACM, New York, NY, 396\u2013399. DOI:https:\/\/doi.org\/10.1145\/2597073.2597129"},{"issue":"11","key":"e_1_3_2_139_2","doi-asserted-by":"crossref","first-page":"12","DOI":"10.1145\/2366316.2366320","article-title":"Major update to ACM\u2019s computing classification system","volume":"55","author":"Rous Bernard","year":"2012","unstructured":"Bernard Rous. 2012. Major update to ACM\u2019s computing classification system. Commun. ACM 55, 11 (Nov.2012), 12. DOI:https:\/\/doi.org\/10.1145\/2366316.2366320","journal-title":"Commun. ACM"},{"issue":"3","key":"e_1_3_2_140_2","first-page":"50","article-title":"Machine learning for detecting data exfiltration: A review","volume":"54","author":"Sabir Bushra","year":"2021","unstructured":"Bushra Sabir, Faheem Ullah, M. Ali Babar, and Raj Gaire. 2021. Machine learning for detecting data exfiltration: A review. Comput. Surveys 54, 3, Article 50 (May2021), 47 pages. DOI:https:\/\/doi.org\/10.1145\/3442181","journal-title":"Comput. Surveys"},{"issue":"1","key":"e_1_3_2_141_2","first-page":"3","article-title":"A systematic literature review on the detection of smells and their evolution in object-oriented and service-oriented systems","volume":"49","author":"Sabir Fatima","year":"2019","unstructured":"Fatima Sabir, Francis Palma, Ghulam Rasool, Yann-Ga\u00ebl Gu\u00e9h\u00e9neuc, and Naouel Moha. 2019. A systematic literature review on the detection of smells and their evolution in object-oriented and service-oriented systems. Softw.: Pract. Exper. 49, 1 (2019), 3\u201339. DOI:https:\/\/doi.org\/10.1002\/spe.2639","journal-title":"Softw.: Pract. Exper."},{"issue":"6","key":"e_1_3_2_142_2","article-title":"Software enhancement effort prediction using machine-learning techniques: A systematic mapping study","volume":"2","author":"Sakhrawi Zaineb","year":"2021","unstructured":"Zaineb Sakhrawi, Asma Sellami, and Nadia Bouassida. 2021. Software enhancement effort prediction using machine-learning techniques: A systematic mapping study. SN Comput. Sci. 2, 6 (Sept.2021). DOI:https:\/\/doi.org\/10.1007\/s42979-021-00872-6","journal-title":"SN Comput. Sci."},{"issue":"2","key":"e_1_3_2_143_2","article-title":"The gardens of learning: A vision for AI","volume":"14","author":"Selfridge Oliver G.","year":"1993","unstructured":"Oliver G. Selfridge. 1993. The gardens of learning: A vision for AI. AI Mag. 14, 2 (Mar.1993). DOI:https:\/\/doi.org\/10.1609\/aimag.v14i2.1041","journal-title":"AI Mag."},{"issue":"6","key":"e_1_3_2_144_2","doi-asserted-by":"crossref","first-page":"654","DOI":"10.1049\/iet-sen.2020.0084","article-title":"Literature survey of deep learning-based vulnerability analysis on source code","volume":"14","author":"Semasaba Abubakar Omari Abdallah","year":"2020","unstructured":"Abubakar Omari Abdallah Semasaba, Wei Zheng, Xiaoxue Wu, and Samuel Akwasi Agyemang. 2020. Literature survey of deep learning-based vulnerability analysis on source code. IET Softw. 14, 6 (Dec.2020), 654\u2013664. DOI:https:\/\/doi.org\/10.1049\/iet-sen.2020.0084","journal-title":"IET Softw."},{"key":"e_1_3_2_145_2","doi-asserted-by":"crossref","first-page":"158","DOI":"10.1016\/j.jss.2017.12.034","article-title":"A survey on software smells","volume":"138","author":"Sharma Tushar","year":"2018","unstructured":"Tushar Sharma and Diomidis Spinellis. 2018. A survey on software smells. J. Syst. Softw. 138 (2018), 158\u2013173. DOI:https:\/\/doi.org\/10.1016\/j.jss.2017.12.034","journal-title":"J. Syst. Softw."},{"issue":"6","key":"e_1_3_2_146_2","article-title":"Topic modeling in software engineering research","volume":"26","author":"Silva Camila Costa","year":"2021","unstructured":"Camila Costa Silva, Matthias Galster, and Fabian Gilson. 2021. Topic modeling in software engineering research. Empir. Softw. Eng. 26, 6 (Nov.2021), 62. DOI:https:\/\/doi.org\/10.1007\/s10664-021-10026-0","journal-title":"Empir. Softw. Eng."},{"key":"e_1_3_2_147_2","doi-asserted-by":"crossref","first-page":"51021","DOI":"10.1109\/ACCESS.2022.3174115","article-title":"Systematic mapping: Artificial intelligence techniques in software engineering","volume":"10","author":"Sofian Hazrina","year":"2022","unstructured":"Hazrina Sofian, Nur Arzilawati Md Yunus, and Rodina Ahmad. 2022. Systematic mapping: Artificial intelligence techniques in software engineering. IEEE Access 10 (2022), 51021\u201351040. DOI:https:\/\/doi.org\/10.1109\/access.2022.3174115","journal-title":"IEEE Access"},{"key":"e_1_3_2_148_2","doi-asserted-by":"crossref","first-page":"190539","DOI":"10.1109\/ACCESS.2020.3031690","article-title":"A systematic literature review and quality analysis of javascript malware detection","volume":"8","author":"Sohan Md. Fahimuzzman","year":"2020","unstructured":"Md. Fahimuzzman Sohan and Anas Basalamah. 2020. A systematic literature review and quality analysis of javascript malware detection. IEEE Access 8 (2020), 190539\u2013190552. DOI:https:\/\/doi.org\/10.1109\/access.2020.3031690","journal-title":"IEEE Access"},{"issue":"2","key":"e_1_3_2_149_2","doi-asserted-by":"crossref","first-page":"212","DOI":"10.3390\/sym11020212","article-title":"Empirical study of software defect prediction: A systematic mapping","volume":"11","author":"Son Le","year":"2019","unstructured":"Le Son, Nakul Pritam, Manju Khari, Raghvendra Kumar, Pham Phuong, and Pham Thong. 2019. Empirical study of software defect prediction: A systematic mapping. Symmetry 11, 2 (Feb.2019), 212. DOI:https:\/\/doi.org\/10.3390\/sym11020212","journal-title":"Symmetry"},{"key":"e_1_3_2_150_2","first-page":"265","volume-title":"Proceedings of the 25th International Conference on Compiler Construction","author":"Sui Yulei","year":"2016","unstructured":"Yulei Sui and Jingling Xue. 2016. SVF: Interprocedural static value-flow analysis in LLVM. In Proceedings of the 25th International Conference on Compiler Construction. ACM, New York, NY, 265\u2013266. DOI:https:\/\/doi.org\/10.1145\/2892208.2892235"},{"key":"e_1_3_2_151_2","first-page":"357","article-title":"Exploring topic models in software engineering data analysis: A survey","author":"Sun Xiaobing","year":"2016","unstructured":"Xiaobing Sun, Xiangyue Liu, Bin Li, Yucong Duan, Hui Yang, and Jiajun Hu. 2016. Exploring topic models in software engineering data analysis: A survey. Proceedings of the 17th IEEE\/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel\/Distributed Computing. 357\u2013362. DOI:https:\/\/doi.org\/10.1109\/SNPD.2016.7515925","journal-title":"Proceedings of the 17th IEEE\/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel\/Distributed Computing"},{"issue":"8","key":"e_1_3_2_152_2","doi-asserted-by":"crossref","first-page":"2477","DOI":"10.1016\/j.engstruct.2010.04.024","article-title":"Fault-tolerant adaptive control of nonlinear base-isolated buildings using EMRAN","volume":"32","author":"Suresh Sundaram","year":"2010","unstructured":"Sundaram Suresh, Sriram Narasimhan, Satish Nagarajaiah, and Narasimhan Sundararajan. 2010. Fault-tolerant adaptive control of nonlinear base-isolated buildings using EMRAN. Eng. Struct. 32, 8 (Aug.2010), 2477\u20132487. DOI:https:\/\/doi.org\/10.1016\/j.engstruct.2010.04.024","journal-title":"Eng. Struct."},{"key":"e_1_3_2_153_2","doi-asserted-by":"crossref","DOI":"10.1007\/978-3-031-01551-9","volume-title":"Algorithms for Reinforcement Learning","author":"Szepesv\u00e1ri Csaba","year":"2010","unstructured":"Csaba Szepesv\u00e1ri. 2010. Algorithms for Reinforcement Learning. Morgan & Claypool Publishers. DOI:https:\/\/doi.org\/10.2200\/S00268ED1V01Y201005AIM009"},{"key":"e_1_3_2_154_2","doi-asserted-by":"crossref","first-page":"257","DOI":"10.1145\/3369255.3369289","volume-title":"Proceedings of the 11th International Conference on Education Technology and Computers (ICETC\u201919)","author":"Tarar M. Irtaza N.","year":"2019","unstructured":"M. Irtaza N. Tarar, Mubashir Ali, and Wasi H. Butt. 2019. Bug report summarization: A systematic literature review. In Proceedings of the 11th International Conference on Education Technology and Computers (ICETC\u201919). ACM, New York, NY, 257\u2013261. DOI:https:\/\/doi.org\/10.1145\/3369255.3369289"},{"key":"e_1_3_2_155_2","doi-asserted-by":"crossref","first-page":"847","DOI":"10.1145\/2487575.2487629","volume-title":"Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD\u201913)","author":"Thornton Chris","year":"2013","unstructured":"Chris Thornton, Frank Hutter, Holger H. Hoos, and Kevin Leyton-Brown. 2013. Auto-WEKA: Combined selection and hyperparameter optimization of classification algorithms. In Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD\u201913). ACM, New York, NY, 847\u2013855. DOI:https:\/\/doi.org\/10.1145\/2487575.2487629"},{"key":"e_1_3_2_156_2","first-page":"17","volume-title":"Proceedings of the 25th International Conference on Intelligent User Interfaces Companion (IUI\u201920)","author":"Todi Kashyap","year":"2020","unstructured":"Kashyap Todi, Jean Vanderdonckt, Xiaojuan Ma, Jeffrey Nichols, and Nikola Banovic. 2020. AI4AUI: Workshop on AI methods for adaptive user interfaces. In Proceedings of the 25th International Conference on Intelligent User Interfaces Companion (IUI\u201920). ACM, New York, NY, 17\u201318. DOI:https:\/\/doi.org\/10.1145\/3379336.3379359"},{"key":"e_1_3_2_157_2","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1007\/s11219-015-9297-z","article-title":"A systematic literature review on the applications of bayesian networks to predict software quality","volume":"25","author":"Tosun Ayse","year":"2017","unstructured":"Ayse Tosun, Ayse B. Bener, and Shirin Akbarinasaji. 2017. A systematic literature review on the applications of bayesian networks to predict software quality. Softw. Qual. J. 25 (Mar.2017), 273\u2013305. DOI:https:\/\/doi.org\/10.1007\/s11219-015-9297-z","journal-title":"Softw. Qual. J."},{"key":"e_1_3_2_158_2","doi-asserted-by":"crossref","first-page":"832","DOI":"10.1145\/3238147.3240732","volume-title":"Proceedings of the 33rd ACM\/IEEE International Conference on Automated Software Engineering (ASE\u201918)","author":"Tufano Michele","year":"2018","unstructured":"Michele Tufano, Cody Watson, Gabriele Bavota, Massimiliano Di Penta, Martin White, and Denys Poshyvanyk. 2018. An empirical investigation into learning bug-fixing patches in the wild via neural machine translation. In Proceedings of the 33rd ACM\/IEEE International Conference on Automated Software Engineering (ASE\u201918). ACM, 832\u2013837. DOI:https:\/\/doi.org\/10.1145\/3238147.3240732"},{"issue":"2","key":"e_1_3_2_159_2","doi-asserted-by":"crossref","first-page":"145","DOI":"10.1007\/s10462-016-9478-6","article-title":"A survey on bug prioritization","volume":"47","author":"Uddin Jamal","year":"2017","unstructured":"Jamal Uddin, Rozaida Ghazali, Mustafa M. Deris, Rashid Naseem, and Habib Shah. 2017. A survey on bug prioritization. Artific. Intell. Rev. 47, 2 (Feb.2017), 145\u2013180. DOI:https:\/\/doi.org\/10.1007\/s10462-016-9478-6","journal-title":"Artific. Intell. Rev."},{"key":"e_1_3_2_160_2","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1016\/j.jnca.2017.10.016","article-title":"Data exfiltration: A review of external attack vectors and countermeasures","volume":"101","author":"Ullah Faheem","year":"2018","unstructured":"Faheem Ullah, Matthew Edwards, Rajiv Ramdhany, Ruzanna Chitchyan, M. Ali Babar, and Awais Rashid. 2018. Data exfiltration: A review of external attack vectors and countermeasures. J. Netw. Comput. Appl. 101 (Jan.2018), 18\u201354. DOI:https:\/\/doi.org\/10.1016\/j.jnca.2017.10.016","journal-title":"J. Netw. Comput. Appl."},{"key":"e_1_3_2_161_2","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1016\/j.infsof.2017.01.006","article-title":"Taxonomies in software engineering: A systematic mapping study and a revised taxonomy development method","volume":"85","author":"Usman Muhammad","year":"2017","unstructured":"Muhammad Usman, Ricardo Britto, J\u00fcrgen B\u00f6rstler, and Emilia Mendes. 2017. Taxonomies in software engineering: A systematic mapping study and a revised taxonomy development method. Info. Softw. Technol. 85 (2017), 43\u201359. DOI:https:\/\/doi.org\/10.1016\/j.infsof.2017.01.006","journal-title":"Info. Softw. Technol."},{"key":"e_1_3_2_162_2","doi-asserted-by":"crossref","first-page":"444","DOI":"10.1007\/11494744_25","volume-title":"Proceedings of the International Conference on Application and Theory of Petri Nets (ICATPN\u201905)","author":"Dongen B. F. van","year":"2005","unstructured":"B. F. van Dongen, A. K. A. de Medeiros, H. M. W. Verbeek, A. J. M. M. Weijters, and W. M. P. van der Aalst. 2005. The ProM framework: A new era in process mining tool support. In Proceedings of the International Conference on Application and Theory of Petri Nets (ICATPN\u201905), Gianfranco Ciardo and Philippe Darondeau (Eds.). Springer, Berlin, 444\u2013454. DOI:https:\/\/doi.org\/10.1007\/11494744_25"},{"key":"e_1_3_2_163_2","first-page":"2","volume-title":"Proceedings of the 16th International Conference on Evaluation Assessment in Software Engineering (EASE\u201912)","author":"Verner June M.","year":"2012","unstructured":"June M. Verner, O. Pearl Brereton, Barbara A. Kitchenham, Mark Turner, and Mahmood Niazi. 2012. Systematic literature reviews in global software development: A tertiary study. In Proceedings of the 16th International Conference on Evaluation Assessment in Software Engineering (EASE\u201912). 2\u201311. DOI:https:\/\/doi.org\/10.1049\/ic.2012.0001"},{"issue":"6","key":"e_1_3_2_164_2","first-page":"1","article-title":"Quality of flow diagram in systematic review and\/or meta-analysis","volume":"13","author":"Vu-Ngoc Hai","year":"2018","unstructured":"Hai Vu-Ngoc, Sameh Samir Elawady, Ghaleb Muhammad Mehyar, Amr Hesham Abdelhamid, Omar Mohamed Mattar, Oday Halhouli, Nguyen Lam Vuong, Citra Dewi Mohd Ali, Ummu Helma Hassan, Nguyen Dang Kien, Kenji Hirayama, and Nguyen Tien Huy. 2018. Quality of flow diagram in systematic review and\/or meta-analysis. PLoS One 13, 6 (June2018), 1\u201316. DOI:https:\/\/doi.org\/10.1371\/journal.pone.0195955","journal-title":"PLoS One"},{"issue":"2","key":"e_1_3_2_165_2","first-page":"32","article-title":"A systematic literature review on the use of deep learning in software engineering research","volume":"31","author":"Watson Cody","year":"2022","unstructured":"Cody Watson, Nathan Cooper, David Nader Palacio, Kevin Moran, and Denys Poshyvanyk. 2022. A systematic literature review on the use of deep learning in software engineering research. ACM Trans. Softw. Eng. Methodol. 31, 2, Article 32 (March2022), 58 pages. DOI:https:\/\/doi.org\/10.1145\/3485275","journal-title":"ACM Trans. Softw. Eng. Methodol."},{"key":"e_1_3_2_166_2","first-page":"141","volume-title":"Proceedings of the International Conference on Software Testing Verification and Validation","author":"Wedyan Fadi","year":"2009","unstructured":"Fadi Wedyan, Dalal Alrmuny, and James M. Bieman. 2009. The effectiveness of automated static analysis tools for fault detection and refactoring prediction. In Proceedings of the International Conference on Software Testing Verification and Validation. 141\u2013150. DOI:https:\/\/doi.org\/10.1109\/ICST.2009.21"},{"key":"e_1_3_2_167_2","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1016\/j.infsof.2011.09.002","article-title":"Systematic literature review of machine learning based software development effort estimation models","volume":"54","author":"Wen Jianfeng","year":"2012","unstructured":"Jianfeng Wen, Shixian Li, Zhiyong Lin, Yong Hu, and Changqin Huang. 2012. Systematic literature review of machine learning based software development effort estimation models. Info. Softw. Technol. 54 (Jan.2012), 41\u201359. DOI:https:\/\/doi.org\/10.1016\/j.infsof.2011.09.002","journal-title":"Info. Softw. Technol."},{"key":"e_1_3_2_168_2","volume-title":"Proceedings of the 18th International Conference on Evaluation and Assessment in Software Engineering (EASE\u201914)","author":"Wohlin Claes","year":"2014","unstructured":"Claes Wohlin. 2014. Guidelines for snowballing in systematic literature studies and a replication in software engineering. In Proceedings of the 18th International Conference on Evaluation and Assessment in Software Engineering (EASE\u201914). ACM, New York, NY, Article 38, 10 pages. DOI:https:\/\/doi.org\/10.1145\/2601248.2601268"},{"key":"e_1_3_2_169_2","doi-asserted-by":"crossref","first-page":"106366","DOI":"10.1016\/j.infsof.2020.106366","article-title":"Guidelines for the search strategy to update systematic literature reviews in software engineering","volume":"127","author":"Wohlin Claes","year":"2020","unstructured":"Claes Wohlin, Emilia Mendes, Katia Romero Felizardo, and Marcos Kalinowski. 2020. Guidelines for the search strategy to update systematic literature reviews in software engineering. Info. Softw. Technol. 127 (Nov.2020), 106366. DOI:https:\/\/doi.org\/10.1016\/j.infsof.2020.106366","journal-title":"Info. Softw. Technol."},{"key":"e_1_3_2_170_2","doi-asserted-by":"crossref","first-page":"919","DOI":"10.1016\/j.infsof.2013.02.002","article-title":"Systematic literature reviews in software engineering","volume":"55","author":"Wohlin C.","year":"2013","unstructured":"C. Wohlin and Rafael Prikladnicki. 2013. Systematic literature reviews in software engineering. Info. Softw. Technol. 55 (2013), 919\u2013920.","journal-title":"Info. Softw. Technol."},{"key":"e_1_3_2_171_2","doi-asserted-by":"crossref","DOI":"10.1007\/978-3-642-29044-2","volume-title":"Experimentation in Software Engineering","author":"Wohlin Claes","year":"2012","unstructured":"Claes Wohlin, Per Runeson, Martin Hst, Magnus C. Ohlsson, Bjrn Regnell, and Anders Wessln. 2012. Experimentation in Software Engineering. Springer."},{"key":"e_1_3_2_172_2","volume-title":"Proceedings of the IEEE International Conference on Software Maintenance and Evolution (ICSME\u201916)","author":"Wu Hong","year":"2016","unstructured":"Hong Wu, Lin Shi, Celia Chen, Qing Wang, and Barry Boehm. 2016. Maintenance effort estimation for open source software: A systematic literature review. In Proceedings of the IEEE International Conference on Software Maintenance and Evolution (ICSME\u201916). IEEE. DOI:https:\/\/doi.org\/10.1109\/icsme.2016.87"},{"issue":"4","key":"e_1_3_2_173_2","doi-asserted-by":"crossref","first-page":"1769","DOI":"10.1177\/8755293020919419","article-title":"The promise of implementing machine learning in earthquake engineering: A state-of-the-art review","volume":"36","author":"Xie Yazhou","year":"2020","unstructured":"Yazhou Xie, Majid Ebad Sichani, Jamie E. Padgett, and Reginald DesRoches. 2020. The promise of implementing machine learning in earthquake engineering: A state-of-the-art review. Earthquake Spectra 36, 4 (June2020), 1769\u20131801. DOI:https:\/\/doi.org\/10.1177\/8755293020919419","journal-title":"Earthquake Spectra"},{"issue":"3","key":"e_1_3_2_174_2","first-page":"56","article-title":"Predictive models in software engineering: Challenges and opportunities","volume":"31","author":"Yang Yanming","year":"2022","unstructured":"Yanming Yang, Xin Xia, David Lo, Tingting Bi, John Grundy, and Xiaohu Yang. 2022. Predictive models in software engineering: Challenges and opportunities. ACM Trans. Softw. Eng. Methodol. 31, 3, Article 56 (Apr.2022), 72 pages. DOI:https:\/\/doi.org\/10.1145\/3503509","journal-title":"ACM Trans. Softw. Eng. Methodol."},{"key":"e_1_3_2_175_2","article-title":"A survey on deep learning for software engineering","author":"Yang Yanming","year":"2021","unstructured":"Yanming Yang, Xin Xia, David Lo, and John Grundy. 2021. A survey on deep learning for software engineering. Comput. Surveys (Dec.2021). DOI:https:\/\/doi.org\/10.1145\/3505243","journal-title":"Comput. Surveys"},{"key":"e_1_3_2_176_2","volume-title":"Proceedings of the International Conference on Software and System Process","author":"Yin Huishi","year":"2015","unstructured":"Huishi Yin. 2015. A study plan: Open innovation based on internet data mining in software engineering. In Proceedings of the International Conference on Software and System Process. ACM. DOI:https:\/\/doi.org\/10.1145\/2785592.2795366"},{"key":"e_1_3_2_177_2","first-page":"1","volume-title":"Proceedings of the 13th International Conference on Emerging Technologies (ICET\u201917)","author":"Zahid Maryam","year":"2017","unstructured":"Maryam Zahid, Zahid Mehmmod, and Irum Inayat. 2017. Evolution in software architecture recovery techniques\u2014A survey. In Proceedings of the 13th International Conference on Emerging Technologies (ICET\u201917). IEEE, 1\u20136. DOI:https:\/\/doi.org\/10.1109\/ICET.2017.8281704"},{"key":"e_1_3_2_178_2","volume-title":"Proceedings of the 29th International Requirements Engineering Conference Workshops (REW\u201921)","author":"Zamani Kareshna","year":"2021","unstructured":"Kareshna Zamani, Didar Zowghi, and Chetan Arora. 2021. Machine learning in requirements engineering: A mapping study. In Proceedings of the 29th International Requirements Engineering Conference Workshops (REW\u201921). IEEE. DOI:https:\/\/doi.org\/10.1109\/rew53955.2021.00023"},{"key":"e_1_3_2_179_2","doi-asserted-by":"crossref","first-page":"334","DOI":"10.1016\/j.jss.2016.03.065","article-title":"A systematic mapping study of mobile application testing techniques","volume":"117","author":"Zein Samer","year":"2016","unstructured":"Samer Zein, Norsaremah Salleh, and John Grundy. 2016. A systematic mapping study of mobile application testing techniques. J. Syst. Softw. 117, C (July2016), 334\u2013356. DOI:https:\/\/doi.org\/10.1016\/j.jss.2016.03.065","journal-title":"J. Syst. Softw."},{"key":"e_1_3_2_180_2","doi-asserted-by":"crossref","first-page":"87","DOI":"10.1023\/A:1023760326768","article-title":"Machine learning and software engineering","volume":"11","author":"Zhang Du","year":"2003","unstructured":"Du Zhang and Jeffrey J. P. Tsai. 2003. Machine learning and software engineering. Softw. Qual. J. 11 (June2003), 87\u2013119. DOI:https:\/\/doi.org\/10.1023\/A:1023760326768","journal-title":"Softw. Qual. J."},{"issue":"4","key":"e_1_3_2_181_2","doi-asserted-by":"crossref","first-page":"240","DOI":"10.1109\/TSE.2006.38","article-title":"On the value of static analysis for fault detection in software","volume":"32","author":"Zheng J.","year":"2006","unstructured":"J. Zheng, L. Williams, N. Nagappan, W. Snipes, J. P. Hudepohl, and M. A. Vouk. 2006. On the value of static analysis for fault detection in software. IEEE Trans. Softw. Eng. 32, 4 (2006), 240\u2013253. DOI:https:\/\/doi.org\/10.1109\/TSE.2006.38","journal-title":"IEEE Trans. Softw. Eng."},{"key":"e_1_3_2_182_2","volume-title":"Proceedings of the 19th International Conference on Evaluation and Assessment in Software Engineering (EASE\u201915)","author":"Zhou You","year":"2015","unstructured":"You Zhou, He Zhang, Xin Huang, Song Yang, Muhammad Ali Babar, and Hao Tang. 2015. Quality assessment of systematic reviews in software engineering: A tertiary study. In Proceedings of the 19th International Conference on Evaluation and Assessment in Software Engineering (EASE\u201915). ACM, New York, NY, Article 14, 14 pages. DOI:https:\/\/doi.org\/10.1145\/2745802.2745815"}],"container-title":["ACM Computing Surveys"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3572905","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3572905","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T17:51:38Z","timestamp":1750182698000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3572905"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,3,2]]},"references-count":181,"journal-issue":{"issue":"12","published-print":{"date-parts":[[2023,12,31]]}},"alternative-id":["10.1145\/3572905"],"URL":"https:\/\/doi.org\/10.1145\/3572905","relation":{},"ISSN":["0360-0300","1557-7341"],"issn-type":[{"value":"0360-0300","type":"print"},{"value":"1557-7341","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,3,2]]},"assertion":[{"value":"2021-11-22","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2022-11-22","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2023-03-02","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}