{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,14]],"date-time":"2026-05-14T05:40:49Z","timestamp":1778737249277,"version":"3.51.4"},"reference-count":104,"publisher":"Springer Science and Business Media LLC","issue":"4","license":[{"start":{"date-parts":[[2022,4,6]],"date-time":"2022-04-06T00:00:00Z","timestamp":1649203200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,4,6]],"date-time":"2022-04-06T00:00:00Z","timestamp":1649203200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Empir Software Eng"],"published-print":{"date-parts":[[2022,7]]},"DOI":"10.1007\/s10664-022-10125-6","type":"journal-article","created":{"date-parts":[[2022,4,6]],"date-time":"2022-04-06T06:08:15Z","timestamp":1649225295000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Tracking bad updates in mobile apps: a search-based approach"],"prefix":"10.1007","volume":"27","author":[{"given":"Islem","family":"Saidani","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ali","family":"Ouni","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4708-0362","authenticated-orcid":false,"given":"Md","family":"Ahasanuzzaman","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Safwat","family":"Hassan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mohamed Wiem","family":"Mkaouer","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ahmed E.","family":"Hassan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,4,6]]},"reference":[{"issue":"1","key":"10125_CR1","doi-asserted-by":"publisher","first-page":"824","DOI":"10.1007\/s10664-019-09766-x","volume":"25","author":"M Ahasanuzzaman","year":"2020","unstructured":"Ahasanuzzaman M, Hassan S, Bezemer C-P, Hassan A E (2020) A longitudinal study of popular ad libraries in the google play store. Empir Softw Eng 25(1):824\u2013858","journal-title":"Empir Softw Eng"},{"key":"10125_CR2","unstructured":"Ahasanuzzaman M, Hassan S, Hassan A E (2020) Studying ad library integration strategies of top free-to-download apps. IEEE Trans Softw Eng"},{"key":"10125_CR3","unstructured":"Akdeniz (2013) Google play crawler. available online:. https:\/\/github.com\/Akdeniz\/google-play-crawler, Accessed: 2021-03-1"},{"key":"10125_CR4","doi-asserted-by":"crossref","unstructured":"Almarimi N, Ouni A, Chouchen M, Saidani I, Mkaouer MW (2020) On the detection of community smells using genetic programming-based ensemble classifier chain. In: 15th ACM international conference on global software engineering, pp 43\u201354","DOI":"10.1145\/3372787.3390439"},{"key":"10125_CR5","unstructured":"AppAnnie (2020) App annie. available online:. https:\/\/www.appannie.com\/en\/, Accessed: 2020-04-01"},{"key":"10125_CR6","doi-asserted-by":"crossref","unstructured":"Arcuri A, Briand L (2011) A practical guide for using statistical tests to assess randomized algorithms in software engineering. In: 33rd international conference on software engineering (ICSE), pp 1\u201310","DOI":"10.1145\/1985793.1985795"},{"key":"10125_CR7","doi-asserted-by":"crossref","unstructured":"Arcuri A, Fraser G (2011) On parameter tuning in search based software engineering. In: International symposium on search based software engineering. Springer, pp 33\u201347","DOI":"10.1007\/978-3-642-23716-4_6"},{"issue":"5","key":"10125_CR8","doi-asserted-by":"publisher","first-page":"502","DOI":"10.1111\/opo.12131","volume":"34","author":"RA Armstrong","year":"2014","unstructured":"Armstrong R A (2014) When to use the b onferroni correction. Ophthalmic Physiol Opt 34(5):502\u2013508","journal-title":"Ophthalmic Physiol Opt"},{"issue":"5","key":"10125_CR9","doi-asserted-by":"publisher","first-page":"94","DOI":"10.1007\/s10664-021-09988-y","volume":"26","author":"M Assi","year":"2021","unstructured":"Assi M, Hassan S, Tian Y, Zou Y (2021) Featcompare: Feature comparison for competing mobile apps leveraging user reviews. Empir Softw Eng 26 (5):94","journal-title":"Empir Softw Eng"},{"key":"10125_CR10","doi-asserted-by":"crossref","unstructured":"Bhowan U, Zhang M, Johnston M (2010) Genetic programming for classification with unbalanced data. In: European conference on genetic programming, pp 1\u201313","DOI":"10.1007\/978-3-642-12148-7_1"},{"key":"10125_CR11","doi-asserted-by":"crossref","unstructured":"Branco P, Torgo L, Ribeiro R P (2017) Relevance-based evaluation metrics for multi-class imbalanced domains. In: Pacific-Asia Conference on Knowledge Discovery and Data Mining. Springer, pp 698\u2013710","DOI":"10.1007\/978-3-319-57454-7_54"},{"issue":"1","key":"10125_CR12","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1023\/A:1010933404324","volume":"45","author":"L Breiman","year":"2001","unstructured":"Breiman L (2001) Random forests. Machine Learn 45(1):5\u201332","journal-title":"Machine Learn"},{"key":"10125_CR13","doi-asserted-by":"crossref","unstructured":"Calciati P, Gorla A (2017) How do apps evolve in their permission requests? a preliminary study. In: IEEE\/ACM 14th international conference on mining software repositories (MSR), pp 37\u201341","DOI":"10.1109\/MSR.2017.64"},{"key":"10125_CR14","doi-asserted-by":"crossref","unstructured":"Calciati P, Kuznetsov K, Bai X, Gorla A (2018) What did really change with the new release of the app?. In: 15th international conference on mining software repositories (MSR), pp 142\u2013152","DOI":"10.1145\/3196398.3196449"},{"key":"10125_CR15","doi-asserted-by":"crossref","unstructured":"Catolino G, Di Nucci D, Ferrucci F (2019) Cross-project just-in-time bug prediction for mobile apps: an empirical assessment. In: International conference on mobile software engineering and systems, pp 99\u2013110","DOI":"10.1109\/MOBILESoft.2019.00023"},{"key":"10125_CR16","doi-asserted-by":"publisher","first-page":"321","DOI":"10.1613\/jair.953","volume":"16","author":"NV Chawla","year":"2002","unstructured":"Chawla NV, Bowyer KW, Hall LO, Kegelmeyer WP (2002) Smote: synthetic minority over-sampling technique. J Artif Intell Res 16:321\u2013357","journal-title":"J Artif Intell Res"},{"issue":"3","key":"10125_CR17","doi-asserted-by":"publisher","first-page":"37:1","DOI":"10.1145\/3447808","volume":"30","author":"Q Chen","year":"2021","unstructured":"Chen Q, Chen C, Hassan S, Xing Z, Xia X, Hassan A E (2021) How should I improve the UI of my app?: A study of user reviews of popular apps in the google play. ACM Trans Softw Eng Methodol (TOSEM) 30(3):37:1\u201337:38","journal-title":"ACM Trans Softw Eng Methodol (TOSEM)"},{"key":"10125_CR18","unstructured":"Chen T, He T, Benesty M, Khotilovich V, Tang Y (2015) Xgboost: extreme gradient boosting. R package version 0.4-2, 1\u20134"},{"key":"10125_CR19","doi-asserted-by":"crossref","unstructured":"Chen Z, Lu S (2007) A genetic programming approach for classification of textures based on wavelet analysis. In: 2007 IEEE international symposium on intelligent signal processing. IEEE, pp 1\u20136","DOI":"10.1109\/WISP.2007.4447575"},{"issue":"1","key":"10125_CR20","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s12864-019-6413-7","volume":"21","author":"D Chicco","year":"2020","unstructured":"Chicco D, Jurman G (2020) The advantages of the matthews correlation coefficient (mcc) over f1 score and accuracy in binary classification evaluation. BMC genomics 21(1):1\u201313","journal-title":"BMC genomics"},{"key":"10125_CR21","doi-asserted-by":"crossref","unstructured":"Ciurumelea A, Schaufelb\u00fchl A, Panichella S, Gall HC (2017) Analyzing reviews and code of mobile apps for better release planning. In: 24th IEEE international conference on software analysis, evolution and reengineering (SANER), pp 91\u2013102","DOI":"10.1109\/SANER.2017.7884612"},{"key":"10125_CR22","doi-asserted-by":"crossref","unstructured":"Darwish SM, EL-Zoghabi AA, Ebaid DB (2015) A novel system for document classification using genetic programming. J Adv Inform Technol, 6(4)","DOI":"10.12720\/jait.6.4.194-200"},{"key":"10125_CR23","unstructured":"Dataset for bad releases detection (2021) Available at : https:\/\/github.com\/stilab-ets\/AppTracker"},{"key":"10125_CR24","doi-asserted-by":"crossref","unstructured":"Deb K, Pratap A, Agarwal S, Meyarivan TAMT (2002). In: A fast and elitist multiobjective genetic algorithm: NSGA-II, vol 6, pp 182\u2013197","DOI":"10.1109\/4235.996017"},{"key":"10125_CR25","doi-asserted-by":"crossref","unstructured":"Dom\u00ednguez-\u00c1lvarez D, Gorla A (2019) Release practices for ios and android apps. In: ACM SIGSOFT International Workshop on App Market Analytics, pp 15\u201318","DOI":"10.1145\/3340496.3342762"},{"key":"10125_CR26","doi-asserted-by":"crossref","unstructured":"Eberius J, Braunschweig K, Hentsch M, Thiele M, Ahmadov A, Lehner W (2015) Building the dresden web table corpus: A classification approach. In: 2015 IEEE\/ACM 2nd International Symposium on Big Data Computing (BDC). IEEE, pp 41\u201350","DOI":"10.1109\/BDC.2015.30"},{"issue":"2","key":"10125_CR27","doi-asserted-by":"publisher","first-page":"121","DOI":"10.1109\/TSMCC.2009.2033566","volume":"40","author":"PG Espejo","year":"2009","unstructured":"Espejo PG, Ventura S, Herrera F (2009) A survey on the application of genetic programming to classification. IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews) 40(2):121\u2013144","journal-title":"IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews)"},{"key":"10125_CR28","doi-asserted-by":"crossref","unstructured":"Evans BP, Xue B, Zhang M (2019) What\u2019s inside the black-box? a genetic programming method for interpreting complex machine learning models. In: Proceedings of the genetic and evolutionary computation conference, pp 1012\u20131020","DOI":"10.1145\/3321707.3321726"},{"issue":"177","key":"10125_CR29","first-page":"1","volume":"20","author":"A Fisher","year":"2019","unstructured":"Fisher A, Rudin C, Dominici F (2019) All models are wrong, but many are useful: Learning a variable\u2019s importance by studying an entire class of prediction models simultaneously. J Mach Learn Res 20(177):1\u201381","journal-title":"J Mach Learn Res"},{"key":"10125_CR30","unstructured":"Gui J, Nagappan M, Halfond WGJ (2017) What aspects of mobile ads do users care about? an empirical study of mobile in-app ad reviews. arXiv:1702.07681"},{"key":"10125_CR31","unstructured":"Hadka D Moea framework. http:\/\/moeaframework.org\/, Accessed: 2020-12-01"},{"key":"10125_CR32","doi-asserted-by":"crossref","unstructured":"Hamdi O, Ouni A, AlOmar EA, Cinn\u00e9ide MO, Mkaouer MW (2021) An empirical study on the impact of refactoring on quality metrics in android applications. In: IEEE\/ACM 8th international conference on mobile software engineering and systems (MobileSoft), pp 28\u201339","DOI":"10.1109\/MobileSoft52590.2021.00010"},{"key":"10125_CR33","doi-asserted-by":"publisher","first-page":"106699","DOI":"10.1016\/j.infsof.2021.106699","volume":"140","author":"O Hamdi","year":"2021","unstructured":"Hamdi O, Ouni A, Cinn\u00e9ide MO, Mkaouer MW (2021) A longitudinal study of the impact of refactoring in android applications. Inf Softw Technol 140:106699","journal-title":"Inf Softw Technol"},{"key":"10125_CR34","doi-asserted-by":"crossref","unstructured":"Harman M, Jia Y, Zhang Y (2012) App store mining and analysis: Msr for app stores. In: IEEE working conference on mining software repositories (MSR), pp 108\u2013111","DOI":"10.1109\/MSR.2012.6224306"},{"issue":"14","key":"10125_CR35","doi-asserted-by":"publisher","first-page":"833","DOI":"10.1016\/S0950-5849(01)00189-6","volume":"43","author":"M Harman","year":"2001","unstructured":"Harman M, Jones B F (2001) Search-based software engineering. Inform Softw Technol 43(14):833\u2013839","journal-title":"Inform Softw Technol"},{"issue":"1","key":"10125_CR36","doi-asserted-by":"publisher","first-page":"11","DOI":"10.1145\/2379776.2379787","volume":"45","author":"M Harman","year":"2012","unstructured":"Harman M, Mansouri SA, Zhang Y (2012) Search-based software engineering: Trends, techniques and applications. ACM Computing Surveys (CSUR) 45(1):11","journal-title":"ACM Computing Surveys (CSUR)"},{"key":"10125_CR37","doi-asserted-by":"crossref","unstructured":"Harman M, McMinn P, De Souza JT, Yoo S (2010) Search based software engineering: Techniques, taxonomy, tutorial. In: Empirical software engineering and verification. Springer, pp 1\u201359","DOI":"10.1007\/978-3-642-25231-0_1"},{"key":"10125_CR38","doi-asserted-by":"crossref","unstructured":"Hassan MM, Ullah S, Hossain MS, Alelaiwi A (2020) An end-to-end deep learning model for human activity recognition from highly sparse body sensor data in internet of medical things environment. The Journal of Supercomputing, 1\u201314","DOI":"10.1007\/s11227-020-03361-4"},{"key":"10125_CR39","unstructured":"Hassan S, Bezemer C-P, Hassan AE (2018) Studying bad updates of top free-to-download apps in the google play store. IEEE Trans Softw Eng"},{"issue":"1","key":"10125_CR40","doi-asserted-by":"publisher","first-page":"505","DOI":"10.1007\/s10664-016-9435-7","volume":"22","author":"S Hassan","year":"2017","unstructured":"Hassan S, Shang W, Hassan AE (2017) An empirical study of emergency updates for top android mobile apps. Empir Softw Eng 22(1):505\u2013546","journal-title":"Empir Softw Eng"},{"key":"10125_CR41","doi-asserted-by":"publisher","DOI":"10.1007\/978-0-387-84858-7","volume-title":"The elements of statistical learning: data mining, inference, and prediction","author":"T Hastie","year":"2009","unstructured":"Hastie T, Tibshirani R, Friedman J (2009) The elements of statistical learning: data mining, inference, and prediction. Springer Science & Business Media, Berlin"},{"issue":"2","key":"10125_CR42","doi-asserted-by":"publisher","first-page":"1","DOI":"10.5121\/ijdkp.2015.5201","volume":"5","author":"M Hossin","year":"2015","unstructured":"Hossin M, Sulaiman MN (2015) A review on evaluation metrics for data classification evaluations. Int J Data Mining Know Manag Process 5(2):1","journal-title":"Int J Data Mining Know Manag Process"},{"issue":"1","key":"10125_CR43","doi-asserted-by":"publisher","first-page":"7","DOI":"10.1007\/s10664-018-9617-6","volume":"24","author":"H Hu","year":"2019","unstructured":"Hu H, Wang S, Bezemer C-P, Hassan AE (2019) Studying the consistency of star ratings and reviews of popular free hybrid android and ios apps. Empir Softw Eng 24(1):7\u201332","journal-title":"Empir Softw Eng"},{"key":"10125_CR44","doi-asserted-by":"crossref","unstructured":"Huang Q, Xia X, Lo D (2017) Supervised vs unsupervised models: A holistic look at effort-aware just-in-time defect prediction. In: 2017 IEEE international conference on software maintenance and evolution (ICSME). IEEE, pp 159\u2013170","DOI":"10.1109\/ICSME.2017.51"},{"issue":"1","key":"10125_CR45","doi-asserted-by":"publisher","first-page":"290","DOI":"10.1007\/s10664-017-9518-0","volume":"23","author":"S Kabinna","year":"2018","unstructured":"Kabinna S, Bezemer C-P, Shang W, Syer MD, Hassan AE (2018) Examining the stability of logging statements. Empir Softw Eng 23(1):290\u2013333","journal-title":"Empir Softw Eng"},{"key":"10125_CR46","doi-asserted-by":"crossref","unstructured":"Kessentini M, Ouni A (2017) Detecting android smells using multi-objective genetic programming. In: Proceedings of the 4th international conference on mobile software engineering and systems, pp 122\u2013132","DOI":"10.1109\/MOBILESoft.2017.29"},{"issue":"9","key":"10125_CR47","doi-asserted-by":"publisher","first-page":"841","DOI":"10.1109\/TSE.2014.2331057","volume":"40","author":"W Kessentini","year":"2014","unstructured":"Kessentini W, Kessentini M, Sahraoui H, Bechikh S, Ouni A (2014) A cooperative parallel search-based software engineering approach for code-smells detection. IEEE Trans Softw Eng 40(9):841\u2013861","journal-title":"IEEE Trans Softw Eng"},{"issue":"3","key":"10125_CR48","doi-asserted-by":"publisher","first-page":"70","DOI":"10.1109\/MS.2014.50","volume":"32","author":"H Khalid","year":"2014","unstructured":"Khalid H, Shihab E, Nagappan M, Hassan A E (2014) What do mobile app users complain about?. IEEE Softw 32(3):70\u201377","journal-title":"IEEE Softw"},{"issue":"3","key":"10125_CR49","doi-asserted-by":"publisher","first-page":"242","DOI":"10.1109\/4235.873235","volume":"4","author":"JK Kishore","year":"2000","unstructured":"Kishore JK, Patnaik LM, Mani V, Agrawal VK (2000) Application of genetic programming for multicategory pattern classification. IEEE Trans Evolution Comput 4(3):242\u2013258","journal-title":"IEEE Trans Evolution Comput"},{"key":"10125_CR50","doi-asserted-by":"crossref","unstructured":"Klepper S, Krusche S, Peters S, Bruegge B, Alperowitz L (2015) Introducing continuous delivery of mobile apps in a corporate environment: A case study. In: 2015 IEEE\/ACM 2nd international workshop on rapid continuous software engineering. IEEE, pp 5\u201311","DOI":"10.1109\/RCoSE.2015.9"},{"key":"10125_CR51","unstructured":"learn S (2006) Scikit-learn classification and regression models. https:\/\/scikit-learn.org\/stable\/supervised_learning, Accessed: 2021-01-10"},{"key":"10125_CR52","unstructured":"learn S (2006) Scikit-learn multiclass-classification. https:\/\/scikit-learn.org\/stable\/modules\/multiclass.html#multiclass-classification, Accessed: 2021-01-10"},{"issue":"4","key":"10125_CR53","doi-asserted-by":"publisher","first-page":"1831","DOI":"10.1007\/s10664-016-9467-z","volume":"22","author":"H Li","year":"2017","unstructured":"Li H, Shang W, Zou Y, Hassan AE (2017) Towards just-in-time suggestions for log changes. Empir Softw Eng 22(4):1831\u20131865","journal-title":"Empir Softw Eng"},{"key":"10125_CR54","doi-asserted-by":"crossref","unstructured":"Loveard T, Ciesielski V (2001) Representing classification problems in genetic programming. In: Proceedings of the 2001 congress on evolutionary computation (IEEE Cat. No. 01TH8546), vol 2. IEEE, pp 1070\u20131077","DOI":"10.1109\/CEC.2001.934310"},{"key":"10125_CR55","doi-asserted-by":"crossref","unstructured":"Maalej W, Nabil H (2015) Bug report, feature request, or simply praise? on automatically classifying app reviews. In: 2015 IEEE 23rd international requirements engineering conference (RE). IEEE, pp 116\u2013125","DOI":"10.1109\/RE.2015.7320414"},{"issue":"5","key":"10125_CR56","doi-asserted-by":"publisher","first-page":"32","DOI":"10.1109\/MS.2019.2923603","volume":"36","author":"D Martens","year":"2019","unstructured":"Martens D, Maalej W (2019) Release early, release often, and watch your users\u2019 emotions: Lessons from emotional patterns. IEEE Softw 36(5):32\u201337","journal-title":"IEEE Softw"},{"key":"10125_CR57","doi-asserted-by":"crossref","unstructured":"Martin W, Sarro F, Harman M (2016) Causal impact analysis for app releases in google play. In: Proceedings of the 2016 24th ACM SIGSOFT international symposium on foundations of software engineering, pp 435\u2013446","DOI":"10.1145\/2950290.2950320"},{"issue":"9","key":"10125_CR58","doi-asserted-by":"publisher","first-page":"817","DOI":"10.1109\/TSE.2016.2630689","volume":"43","author":"W Martin","year":"2016","unstructured":"Martin W, Sarro F, Jia Y, Zhang Y, Harman M (2016) A survey of app store analysis for software engineering. IEEE Trans Softw Eng 43 (9):817\u2013847","journal-title":"IEEE Trans Softw Eng"},{"issue":"3","key":"10125_CR59","doi-asserted-by":"publisher","first-page":"17","DOI":"10.1145\/2729974","volume":"24","author":"W Mkaouer","year":"2015","unstructured":"Mkaouer W, Kessentini M, Shaout A, Koligheu P, Bechikh S, Deb K, Ouni A (2015) Many-objective software remodularization using nsga-iii. ACM Trans Softw Eng Methodol (TOSEM) 24(3):17","journal-title":"ACM Trans Softw Eng Methodol (TOSEM)"},{"key":"10125_CR60","doi-asserted-by":"crossref","unstructured":"Nayebi M, Adams B, Ruhe G (2016) Release practices for mobile apps \u2013 what do users and developers think?. In: IEEE 23rd international conference on software analysis, evolution, and reengineering (SANER), vol 1, pp 552\u2013562","DOI":"10.1109\/SANER.2016.116"},{"key":"10125_CR61","doi-asserted-by":"crossref","unstructured":"Nayebi M, Farahi H, Ruhe G (2017) Which version should be released to app store?. In: ACM\/IEEE international symposium on empirical software engineering and measurement (ESEM), pp 324\u2013333","DOI":"10.1109\/ESEM.2017.46"},{"key":"10125_CR62","doi-asserted-by":"crossref","unstructured":"Nejati S, Gay G (2019) 11th international symposium search-based software engineering. vol 11664","DOI":"10.1007\/978-3-030-27455-9"},{"issue":"6","key":"10125_CR63","doi-asserted-by":"publisher","first-page":"3088","DOI":"10.1007\/s10664-017-9507-3","volume":"22","author":"E Noei","year":"2017","unstructured":"Noei E, Syer M D, Zou Y, Hassan A E, Keivanloo I (2017) A study of the relation of mobile device attributes with the user-perceived quality of android apps. Empir Softw Eng 22(6):3088\u20133116","journal-title":"Empir Softw Eng"},{"key":"10125_CR64","doi-asserted-by":"crossref","unstructured":"Openja M, Adams B, Khomh F (2020) Analysis of modern release engineering topics:\u2013a large-scale study using stackoverflow\u2013. In: IEEE international conference on software maintenance and evolution (ICSME), pp 104\u2013114","DOI":"10.1109\/ICSME46990.2020.00020"},{"key":"10125_CR65","doi-asserted-by":"crossref","unstructured":"Ouni A (2020) Search based software engineering: challenges, opportunities and recent applications. In: Genetic and evolutionary computation conference (GECCO), pp 1114\u20131146","DOI":"10.1145\/3377929.3389887"},{"issue":"4","key":"10125_CR66","doi-asserted-by":"publisher","first-page":"603","DOI":"10.1109\/TSC.2015.2502595","volume":"10","author":"A Ouni","year":"2015","unstructured":"Ouni A, Kessentini M, Inoue K, Cinn\u00e9ide MO (2015) Search-based web service antipatterns detection. IEEE Trans Serv Comput 10(4):603\u2013617","journal-title":"IEEE Trans Serv Comput"},{"issue":"1","key":"10125_CR67","doi-asserted-by":"publisher","first-page":"47","DOI":"10.1007\/s10515-011-0098-8","volume":"20","author":"A Ouni","year":"2013","unstructured":"Ouni A, Kessentini M, Sahraoui H, Boukadoum M (2013) Maintainability defects detection and correction: a multi-objective approach. Autom Softw Eng 20(1):47\u201379","journal-title":"Autom Softw Eng"},{"key":"10125_CR68","doi-asserted-by":"crossref","unstructured":"Ouni A, Kessentini M, Sahraoui H, Hamdi M S (2012) Search-based refactoring: Towards semantics preservation. In: IEEE international conference on software maintenance (ICSM), pp 347\u2013356","DOI":"10.1109\/ICSM.2012.6405292"},{"issue":"3","key":"10125_CR69","doi-asserted-by":"publisher","first-page":"23","DOI":"10.1145\/2932631","volume":"25","author":"A Ouni","year":"2016","unstructured":"Ouni A, Kessentini M, Sahraoui H, Inoue K, Deb K (2016) Multi-criteria code refactoring using search-based software engineering: An industrial case study. ACM Trans Softw Eng Methodol (TOSEM) 25(3):23","journal-title":"ACM Trans Softw Eng Methodol (TOSEM)"},{"key":"10125_CR70","doi-asserted-by":"crossref","unstructured":"Pagano D, Maalej W (2013) User feedback in the appstore: An empirical study. In: 21st IEEE international requirements engineering conference (RE), pp 125\u2013134","DOI":"10.1109\/RE.2013.6636712"},{"key":"10125_CR71","doi-asserted-by":"crossref","unstructured":"Palomba F, Linares-Vasquez M, Bavota G, Oliveto R, Di Penta M, Poshyvanyk D, De Lucia A (2015) User reviews matter! tracking crowdsourced reviews to support evolution of successful apps. In: IEEE international conference on software maintenance and evolution (ICSME), pp 291\u2013300","DOI":"10.1109\/ICSM.2015.7332475"},{"key":"10125_CR72","doi-asserted-by":"crossref","unstructured":"Palomba F, Salza P, Ciurumelea A, Panichella S, Gall H, Ferrucci F, De Lucia A (2017) Recommending and localizing change requests for mobile apps based on user reviews. In: IEEE\/ACM 39th International Conference on Software Engineering (ICSE), pp 106\u2013117","DOI":"10.1109\/ICSE.2017.18"},{"key":"10125_CR73","doi-asserted-by":"crossref","unstructured":"Panichella S, Di Sorbo A, Guzman E, Visaggio CA, Canfora G, Gall HC (2015) How can i improve my app? classifying user reviews for software maintenance and evolution. In: 2015 IEEE international conference on software maintenance and evolution (ICSME). IEEE, pp 281\u2013290","DOI":"10.1109\/ICSM.2015.7332474"},{"key":"10125_CR74","doi-asserted-by":"crossref","unstructured":"Panichella S, Di Sorbo A, Guzman E, Visaggio CA, Canfora G, Gall HC (2016) Ardoc: App reviews development oriented classifier. In: Proceedings of the 2016 24th ACM SIGSOFT international symposium on foundations of software engineering, pp 1023\u20131027","DOI":"10.1145\/2950290.2983938"},{"key":"10125_CR75","doi-asserted-by":"crossref","unstructured":"Qiu F, Yan M, Xia X, Wang X, Fan Y, Hassan A E, Lo D (2020) Jito: a tool for just-in-time defect identification and localization. In: Proceedings of the 28th ACM joint meeting on european software engineering conference and symposium on the foundations of software engineering, pp 1586\u20131590","DOI":"10.1145\/3368089.3417927"},{"issue":"2","key":"10125_CR76","doi-asserted-by":"publisher","first-page":"289","DOI":"10.1109\/TNNLS.2013.2274735","volume":"25","author":"A Rocha","year":"2013","unstructured":"Rocha A, Goldenstein SK (2013) Multiclass from binary: Expanding one-versus-all, one-versus-one and ecoc-based approaches. IEEE Trans Neural Netw Learn Syst 25(2):289\u2013302","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"issue":"3","key":"10125_CR77","doi-asserted-by":"publisher","first-page":"117","DOI":"10.1007\/BF01891203","volume":"2","author":"P Royston","year":"1992","unstructured":"Royston P (1992) Approximating the shapiro-wilk w-test for non-normality. Stat Comput 2(3):117\u2013119","journal-title":"Stat Comput"},{"key":"10125_CR78","doi-asserted-by":"publisher","first-page":"106392","DOI":"10.1016\/j.infsof.2020.106392","volume":"128","author":"I Saidani","year":"2020","unstructured":"Saidani I, Ouni A, Chouchen M, Mkaouer M W (2020) Predicting continuous integration build failures using evolutionary search. Inf Softw Technol 128:106392","journal-title":"Inf Softw Technol"},{"key":"10125_CR79","doi-asserted-by":"crossref","unstructured":"Saidani I, Ouni A, Mkaouer W (2021) Detecting skipped commits in continuous integration using multi-objective evolutionary search. IEEE Trans Softw Eng","DOI":"10.1109\/TSE.2021.3129165"},{"key":"10125_CR80","doi-asserted-by":"crossref","unstructured":"Sarro F, Harman M, Jia Y, Zhang Y (2018) Customer rating reactions can be predicted purely using app features. In: IEEE 26th international requirements engineering conference (RE), pp 76\u201387","DOI":"10.1109\/RE.2018.00018"},{"key":"10125_CR81","doi-asserted-by":"crossref","unstructured":"Scalabrino S, Grano G, Di Nucci D, Oliveto R, De Lucia A (2016) Search-based testing of procedural programs: Iterative single-target or multi-target approach?. In: International symposium on search based software engineering, pp 64\u201379","DOI":"10.1007\/978-3-319-47106-8_5"},{"key":"10125_CR82","unstructured":"Scikit-learn.org (2006) Parameter estimation using grid search with scikit-learn. available online:. https:\/\/scikit-learn.org\/stable\/modules\/grid_search.html, Accessed: 2020-12-01"},{"key":"10125_CR83","doi-asserted-by":"crossref","unstructured":"Smart W, Zhang M (2005) Using genetic programming for multiclass classification by simultaneously solving component binary classification problems. In: European conference on genetic programming. Springer, pp 227\u2013239","DOI":"10.1007\/978-3-540-31989-4_20"},{"issue":"4","key":"10125_CR84","doi-asserted-by":"publisher","first-page":"427","DOI":"10.1016\/j.ipm.2009.03.002","volume":"45","author":"M Sokolova","year":"2009","unstructured":"Sokolova M, Lapalme G (2009) A systematic analysis of performance measures for classification tasks. Inform Process Manag 45(4):427\u2013437","journal-title":"Inform Process Manag"},{"key":"10125_CR85","unstructured":"Su T, Fan L, Chen S, Liu Y, Xu L, Pu G, Su Z (2020) Why my app crashes understanding and benchmarking framework-specific exceptions of android apps. IEEE Trans Softw Eng"},{"issue":"1","key":"10125_CR86","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s40537-020-00349-y","volume":"7","author":"J Tanha","year":"2020","unstructured":"Tanha J, Abdi Y, Samadi N, Razzaghi N, Asadpour M (2020) Boosting methods for multi-class imbalanced data classification: an experimental review. J Big Data 7(1):1\u201347","journal-title":"J Big Data"},{"key":"10125_CR87","doi-asserted-by":"crossref","unstructured":"Tantithamthavorn C, McIntosh S, Hassan AE, Ihara A, Matsumoto K (2015) The impact of mislabelling on the performance and interpretation of defect prediction models. In: 2015 IEEE\/ACM 37th IEEE international conference on software engineering, vol 1. IEEE, pp 812\u2013823","DOI":"10.1109\/ICSE.2015.93"},{"key":"10125_CR88","doi-asserted-by":"crossref","unstructured":"Tantithamthavorn C, McIntosh S, Hassan AE, Matsumoto K (2017) An empirical comparison of model validation techniques for defect prediction models. (1)","DOI":"10.1109\/TSE.2016.2584050"},{"key":"10125_CR89","doi-asserted-by":"crossref","unstructured":"Tantithamthavorn C, McIntosh S, Hassan AE, Matsumoto K (2018) The impact of automated parameter optimization for defect prediction models","DOI":"10.1109\/TSE.2018.2794977"},{"issue":"7","key":"10125_CR90","doi-asserted-by":"publisher","first-page":"683","DOI":"10.1109\/TSE.2018.2794977","volume":"45","author":"C Tantithamthavorn","year":"2018","unstructured":"Tantithamthavorn C, McIntosh S, Hassan AE, Matsumoto K (2018) The impact of automated parameter optimization on defect prediction models. IEEE Trans Softw Eng 45(7):683\u2013711","journal-title":"IEEE Trans Softw Eng"},{"issue":"1","key":"10125_CR91","doi-asserted-by":"publisher","first-page":"182","DOI":"10.1007\/s10664-012-9219-7","volume":"19","author":"SW Thomas","year":"2014","unstructured":"Thomas SW, Hemmati H, Hassan AE, Blostein D (2014) Static test case prioritization using topic models. Empir Softw Eng 19(1):182\u2013212","journal-title":"Empir Softw Eng"},{"key":"10125_CR92","doi-asserted-by":"crossref","unstructured":"Tian Y, Nagappan M, Lo D, Hassan AE (2015) What are the characteristics of high-rated apps? a case study on free android applications. In: IEEE international conference on software maintenance and evolution (ICSME), pp 301\u2013310","DOI":"10.1109\/ICSM.2015.7332476"},{"issue":"2","key":"10125_CR93","first-page":"101","volume":"25","author":"A Vargha","year":"2000","unstructured":"Vargha A, Delaney HD (2000) A critique and improvement of the cl common language effect size statistics of mcgraw and wong. J Educ Behav Stat 25 (2):101\u2013132","journal-title":"J Educ Behav Stat"},{"key":"10125_CR94","doi-asserted-by":"crossref","unstructured":"Villarroel L, Bavota G, Russo B, Oliveto R, Di Penta M (2016) Release planning of mobile apps based on user reviews. In: 2016 IEEE\/ACM 38th international conference on software engineering (ICSE). IEEE, pp 14\u201324","DOI":"10.1145\/2884781.2884818"},{"key":"10125_CR95","first-page":"171","volume":"1","author":"F Wilcoxon","year":"1970","unstructured":"Wilcoxon F, Katti SK, Wilcox R A (1970) Critical values and probability levels for the wilcoxon rank sum test and the wilcoxon signed rank test. Select Table Math Stat 1:171\u2013259","journal-title":"Select Table Math Stat"},{"key":"10125_CR96","unstructured":"XGBoost (2006) Xgboost python package. https:\/\/xgboost.readthedocs.io\/en\/latest\/python\/index.html, Accessed: 2021-01-10"},{"key":"10125_CR97","doi-asserted-by":"crossref","unstructured":"Xia J, Li Y, Wang C (2017) An empirical study on the cross-project predictability of continuous integration outcomes. In: 14th Web information systems and applications conference (WISA), pp 234\u2013239","DOI":"10.1109\/WISA.2017.53"},{"key":"10125_CR98","doi-asserted-by":"crossref","unstructured":"Xia X, Shihab E, Kamei Y, Lo D, Wang X (2016) Predicting crashing releases of mobile applications. In: Proceedings of the 10th ACM\/IEEE international symposium on empirical software engineering and measurement, pp 1\u201310","DOI":"10.1145\/2961111.2962606"},{"key":"10125_CR99","unstructured":"Yan M, Xia X, Fan Y, Hassan AE, Lo D, Li S (2020) Just-in-time defect identification and localization: A two-phase framework. IEEE Trans Softw Eng"},{"key":"10125_CR100","doi-asserted-by":"crossref","unstructured":"Yan M, Xia X, Fan Y, Lo D, Hassan AE, Zhang X (2020) Effort-aware just-in-time defect identification in practice: a case study at alibaba. In: Proceedings of the 28th ACM joint meeting on european software engineering conference and symposium on the foundations of software engineering, pp 1308\u20131319","DOI":"10.1145\/3368089.3417048"},{"key":"10125_CR101","doi-asserted-by":"crossref","unstructured":"Yang AZH, Hassan S, Zou Y, Hassan AE (2021) An empirical study on release notes patterns of popular apps in the google play store. Empir Softw Eng, 1\u201341","DOI":"10.1007\/s10664-021-10086-2"},{"key":"10125_CR102","doi-asserted-by":"crossref","unstructured":"Yang Y, Zhou Y, Liu J, Zhao Y, Lu H, Xu L, Xu B, Leung H (2016) Effort-aware just-in-time defect prediction: simple unsupervised models could be better than supervised models. In: Proceedings of the 2016 24th ACM SIGSOFT international symposium on foundations of software engineering, pp 157\u2013168","DOI":"10.1145\/2950290.2950353"},{"key":"10125_CR103","doi-asserted-by":"crossref","unstructured":"Zar J H (2005) Spearman rank correlation. Encyclopedia Biostat. vol. 7","DOI":"10.1002\/0470011815.b2a15150"},{"key":"10125_CR104","doi-asserted-by":"crossref","unstructured":"Zarif OE, da Costa DA, Hassan S, Zou Y (2020) On the relationship between user churn and software issues. In: 17th international conference on mining software repositories (MSR). ACM, pp 339\u2013349","DOI":"10.1145\/3379597.3387456"}],"container-title":["Empirical Software Engineering"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10664-022-10125-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10664-022-10125-6\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10664-022-10125-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,6,10]],"date-time":"2022-06-10T06:47:28Z","timestamp":1654843648000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10664-022-10125-6"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,4,6]]},"references-count":104,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2022,7]]}},"alternative-id":["10125"],"URL":"https:\/\/doi.org\/10.1007\/s10664-022-10125-6","relation":{},"ISSN":["1382-3256","1573-7616"],"issn-type":[{"value":"1382-3256","type":"print"},{"value":"1573-7616","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,4,6]]},"assertion":[{"value":"24 January 2022","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"6 April 2022","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}],"article-number":"81"}}