{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,3]],"date-time":"2026-03-03T00:49:57Z","timestamp":1772498997934,"version":"3.50.1"},"reference-count":64,"publisher":"Springer Science and Business Media LLC","issue":"5","license":[{"start":{"date-parts":[[2024,7,30]],"date-time":"2024-07-30T00:00:00Z","timestamp":1722297600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2024,7,30]],"date-time":"2024-07-30T00:00:00Z","timestamp":1722297600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/501100003252","name":"Lund University","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100003252","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Empir Software Eng"],"published-print":{"date-parts":[[2024,9]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>[Context] The continuous inflow of bug reports is a considerable challenge in large development projects. Inspired by contemporary work on mining software repositories, we designed a prototype bug assignment solution based on machine learning in 2011-2016. The prototype evolved into an internal Ericsson product, TRR, in 2017-2018. TRR\u2019s first bug assignment without human intervention happened in April 2019. [Objective] Our study evaluates the adoption of TRR within its industrial context at Ericsson, i.e., we provide lessons learned related to the productization of a research prototype within a company. Moreover, we investigate 1) how TRR performs in the field, 2) what value TRR provides to Ericsson, and 3) how TRR has influenced the ways of working. [Method] We conduct a preregistered industrial case study combining interviews with TRR stakeholders, minutes from sprint planning meetings, and bug-tracking data. The data analysis includes thematic analysis, descriptive statistics, and Bayesian causal analysis. [Results] TRR is now an incorporated part of the bug assignment process. Considering the abstraction levels of the telecommunications stack, high-level modules are more positive while low-level modules experienced some drawbacks. Most importantly, some bug reports directly reach low-level modules without first having passed through fundamental root-cause analysis steps at higher levels. On average, TRR automatically assigns 30% of the incoming bug reports with an accuracy of 75%. Auto-routed TRs are resolved around 21% faster within Ericsson, and TRR has saved highly seasoned engineers many hours of work. Indirect effects of adopting TRR include process improvements, process awareness, increased communication, and higher job satisfaction. [Conclusions] TRR has saved time at Ericsson, but the adoption of automated bug assignment was more intricate compared to similar endeavors reported from other companies. We primarily attribute the difference to the very large size of the organization and the complex products. Key facilitators in the successful adoption include a gradual introduction, product champions, and careful stakeholder analysis.<\/jats:p>","DOI":"10.1007\/s10664-024-10507-y","type":"journal-article","created":{"date-parts":[[2024,7,30]],"date-time":"2024-07-30T08:02:11Z","timestamp":1722326531000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Adopting automated bug assignment in practice \u2014 a longitudinal case study at Ericsson"],"prefix":"10.1007","volume":"29","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7879-4371","authenticated-orcid":false,"given":"Markus","family":"Borg","sequence":"first","affiliation":[]},{"given":"Leif","family":"Jonsson","sequence":"additional","affiliation":[]},{"given":"Emelie","family":"Engstr\u00f6m","sequence":"additional","affiliation":[]},{"given":"B\u00e9la","family":"Bartalos","sequence":"additional","affiliation":[]},{"given":"Attila","family":"Szab\u00f3","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,7,30]]},"reference":[{"key":"10507_CR1","doi-asserted-by":"crossref","unstructured":"Aktas EU, Yilmaz C (2020) Automated issue assignment: results and insights from an industrial case. Empirical Softw Eng 25(5):3544\u20133589","DOI":"10.1007\/s10664-020-09846-3"},{"key":"10507_CR2","doi-asserted-by":"crossref","unstructured":"Aktas EU, Yilmaz C (2020b) An exploratory study on improving automated issue triage with attached screenshots. In: Proc. of the 42nd international conference on software engineering: companion proceedings, pp 292\u2013293","DOI":"10.1145\/3377812.3390805"},{"issue":"3","key":"10507_CR3","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/2000791.2000794","volume":"20","author":"J Anvik","year":"2011","unstructured":"Anvik J, Murphy G (2011) Reducing the effort of bug report triage: Recommenders for development-oriented decisions. Trans Softw Eng Methodol 20(3):1\u201335","journal-title":"Trans Softw Eng Methodol"},{"key":"10507_CR4","unstructured":"Baltes S, Ralph P (2020) Sampling in software engineering research: A critical review and guidelines. arXiv:2002.07764"},{"key":"10507_CR5","doi-asserted-by":"crossref","unstructured":"Baysal O, Godfrey M, Cohen R (2009) A bug you like: A framework for automated assignment of bugs. In: Proc. of the 17th International conference on program comprehension, pp 297\u2013298","DOI":"10.1109\/ICPC.2009.5090066"},{"key":"10507_CR6","doi-asserted-by":"crossref","unstructured":"Bettenburg N, Premraj R, Zimmermann T et\u00a0al (2008) Duplicate bug reports considered harmful... really? In: Proc. of the International conference on software maintenance, pp 337\u2013345","DOI":"10.1109\/ICSM.2008.4658082"},{"issue":"10","key":"10507_CR7","doi-asserted-by":"publisher","first-page":"2275","DOI":"10.1016\/j.jss.2012.04.053","volume":"85","author":"P Bhattacharya","year":"2012","unstructured":"Bhattacharya P, Neamtiu I, Shelton C (2012) Automated, highly-accurate, bug assignment using machine learning and tossing graphs. J Syst Softw 85(10):2275\u20132292","journal-title":"J Syst Softw"},{"key":"10507_CR8","doi-asserted-by":"crossref","unstructured":"Borg M, Runeson P (2014) Changes, evolution, and bugs. In: Recommendation systems in software engineering. Springer, p 477\u2013509","DOI":"10.1007\/978-3-642-45135-5_18"},{"issue":"7","key":"10507_CR9","doi-asserted-by":"publisher","first-page":"675","DOI":"10.1109\/TSE.2016.2620458","volume":"43","author":"M Borg","year":"2016","unstructured":"Borg M, Wnuk K, Regnell B et al (2016) Supporting change impact analysis using a recommendation system: An industrial case study in a safety-critical context. Trans Softw Eng 43(7):675\u2013700","journal-title":"Trans Softw Eng"},{"key":"10507_CR10","unstructured":"Borg M, Jonsson L, Engstr\u00f6m E, et\u00a0al (2021) Adopting automated bug assignment in practice: A registered report of an industrial case study. arXiv:2109.13635"},{"issue":"5","key":"10507_CR11","doi-asserted-by":"publisher","first-page":"120","DOI":"10.1109\/MS.2018.3571250","volume":"35","author":"J Carver","year":"2018","unstructured":"Carver J, Prikladnicki R (2018) Industry-academia collaboration in software engineering. IEEE Softw 35(5):120\u2013124","journal-title":"IEEE Softw"},{"key":"10507_CR12","doi-asserted-by":"crossref","unstructured":"Chattamvelli R, Shanmugam R (2021) Continuous Distributions in Engineering and the Applied Sciences: Part I. Synthesis Lectures on Mathematics and Statistics Series, Morgan & Claypool Publishers","DOI":"10.1007\/978-3-031-02435-1"},{"key":"10507_CR13","unstructured":"Crow E, Shimizu K (1988) Lognormal Distributions: Theory and Applications. Statistics: A Series of Textbooks and Monographs, Taylor & Francis"},{"key":"10507_CR14","doi-asserted-by":"crossref","unstructured":"Cruzes D, Dyb\u00e5T (2011) Recommended steps for thematic synthesis in software engineering. In: Proc. of the International symposium on empirical software engineering and measurement, pp 275\u2013284","DOI":"10.1109\/ESEM.2011.36"},{"key":"10507_CR15","doi-asserted-by":"crossref","unstructured":"Davis F (1989) Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS quarterly pp 319\u2013340","DOI":"10.2307\/249008"},{"key":"10507_CR16","doi-asserted-by":"crossref","unstructured":"Engstr\u00f6m E, Feldt R, Torkar R (2012) Indirect effects in evidential assessment: a case study on regression test technology adoption. In: Proceedings of the 2nd international workshop on Evidential assessment of software technologies, pp 15\u201320","DOI":"10.1145\/2372233.2372239"},{"issue":"4","key":"10507_CR17","doi-asserted-by":"publisher","first-page":"2630","DOI":"10.1007\/s10664-020-09818-7","volume":"25","author":"E Engstr\u00f6m","year":"2020","unstructured":"Engstr\u00f6m E, Storey M, Runeson P et al (2020) How software engineering research aligns with design science: a review. Empirical Softw Eng 25(4):2630\u20132660","journal-title":"Empirical Softw Eng"},{"key":"10507_CR18","doi-asserted-by":"crossref","unstructured":"Fan A, Gokkaya B, Harman M et\u00a0al (2023) Large language models for software engineering: Survey and open problems. arXiv:2310.03533","DOI":"10.1109\/ICSE-FoSE59343.2023.00008"},{"key":"10507_CR19","unstructured":"Favre JM, Estublier J, Sanlaville A (2003) Tool adoption issues in a very large software company. In: Proceedings of 3rd International workshop on adoption-centric software engineering (ACSE\u201903), Portland, Oregon, USA, pp 81\u201389"},{"key":"10507_CR20","unstructured":"Flaounas I (2017) Beyond the technical challenges for deploying machine learning solutions in a software company. In: Proc. of the Human in the loop machine learning workshop"},{"issue":"9","key":"10507_CR21","first-page":"1786","volume":"47","author":"CA Furia","year":"2019","unstructured":"Furia CA, Feldt R, Torkar R (2019) Bayesian data analysis in empirical software engineering research. IEEE Trans Softw Eng 47(9):1786\u20131810","journal-title":"IEEE Trans Softw Eng"},{"issue":"4","key":"10507_CR22","doi-asserted-by":"publisher","first-page":"2540","DOI":"10.1007\/s10664-019-09711-y","volume":"24","author":"V Garousi","year":"2019","unstructured":"Garousi V, Pfahl D, Fernandes JM et al (2019) Characterizing industry-academia collaborations in software engineering: evidence from 101 projects. Empirical Softw Eng 24(4):2540\u20132602","journal-title":"Empirical Softw Eng"},{"key":"10507_CR23","doi-asserted-by":"crossref","unstructured":"Garousi V, Borg M, Oivo M (2020) Practical relevance of software engineering research: synthesizing the community\u2019s voice. Empirical Softw Eng 25(3):1687\u20131754","DOI":"10.1007\/s10664-020-09803-0"},{"key":"10507_CR24","doi-asserted-by":"crossref","unstructured":"Gelman A, Carlin JB, Stern HS, et\u00a0al (2013) Bayesian Data Analysis, 3rd edn. Chapman and Hall\/CRC","DOI":"10.1201\/b16018"},{"key":"10507_CR25","doi-asserted-by":"crossref","unstructured":"Gelman A, Lee D, Guo J (2015) Stan: A probabilistic programming language for bayesian inference and optimization","DOI":"10.3102\/1076998615606113"},{"issue":"1","key":"10507_CR26","doi-asserted-by":"publisher","first-page":"10","DOI":"10.1145\/1656274.1656278","volume":"11","author":"M Hall","year":"2009","unstructured":"Hall M, Frank E, Holmes G et al (2009) The WEKA data mining software: An update. SIGKDD Explorations Newsletter 11(1):10\u201318","journal-title":"SIGKDD Explorations Newsletter"},{"issue":"3","key":"10507_CR27","doi-asserted-by":"publisher","first-page":"358","DOI":"10.1016\/j.jengtecman.2012.03.007","volume":"29","author":"MA Hameed","year":"2012","unstructured":"Hameed MA, Counsell S, Swift S (2012) A conceptual model for the process of it innovation adoption in organizations. J Eng Technol Manag 29(3):358\u2013390","journal-title":"J Eng Technol Manag"},{"key":"10507_CR28","doi-asserted-by":"crossref","unstructured":"Hansen KB (2020) The virtue of simplicity: On machine learning models in algorithmic trading. Big Data & Society 7(1):2053951720926,558","DOI":"10.1177\/2053951720926558"},{"key":"10507_CR29","volume-title":"Causal inference: What if","author":"M Hern\u00e1n","year":"2020","unstructured":"Hern\u00e1n M, Robins J (2020) Causal inference: What if. Chapman & Hall\/CRC, Boca Raton, FL, USA"},{"issue":"3","key":"10507_CR30","doi-asserted-by":"publisher","first-page":"407","DOI":"10.1177\/0018720814547570","volume":"57","author":"KA Hoff","year":"2015","unstructured":"Hoff KA, Bashir M (2015) Trust in automation: Integrating empirical evidence on factors that influence trust. Hum Fact 57(3):407\u2013434","journal-title":"Hum Fact"},{"key":"10507_CR31","doi-asserted-by":"crossref","unstructured":"Jeong G, Kim S, Zimmermann T (2009) Improving bug triage with bug tossing graphs. In: Proc. of the 7th Joint Meeting of the European software engineering conference and the acm sigsoft symposium on the foundations of software engineering, pp 111\u2013120","DOI":"10.1145\/1595696.1595715"},{"key":"10507_CR32","doi-asserted-by":"crossref","unstructured":"John MM, Olsson HH, Bosch J (2021) Towards MLOps: A framework and maturity model. In: 2021 47th Euromicro Conference on software engineering and advanced applications (SEAA), IEEE, pp 1\u20138","DOI":"10.1109\/SEAA53835.2021.00050"},{"key":"10507_CR33","doi-asserted-by":"crossref","unstructured":"Jonsson L (2013) Increasing anomaly handling efficiency in large organizations using applied machine learning. In: 2013 35th International conference on software engineering (ICSE), IEEE, pp 1361\u20131364","DOI":"10.1109\/ICSE.2013.6606717"},{"key":"10507_CR34","doi-asserted-by":"crossref","unstructured":"Jonsson L, Broman D, Sandahl K et\u00a0al (2012) Towards automated anomaly report assignment in large complex systems using stacked generalization. In: Proc. of the 5th International conference on software testing, verification and validation, pp 437\u2013446","DOI":"10.1109\/ICST.2012.124"},{"issue":"4","key":"10507_CR35","doi-asserted-by":"publisher","first-page":"1533","DOI":"10.1007\/s10664-015-9401-9","volume":"21","author":"L Jonsson","year":"2016","unstructured":"Jonsson L, Borg M, Broman D et al (2016) Automated bug assignment: Ensemble-based machine learning in large scale industrial contexts. Empirical Softw Eng 21(4):1533\u20131578","journal-title":"Empirical Softw Eng"},{"key":"10507_CR36","doi-asserted-by":"crossref","unstructured":"Jonsson L, Broman D, Magnusson M, et\u00a0al (2016b) Automatic localization of bugs to faulty components in large scale software systems using bayesian classification. In: 2016 IEEE International conference on software quality, reliability and security (QRS), IEEE, pp 423\u2013430","DOI":"10.1109\/QRS.2016.54"},{"key":"10507_CR37","doi-asserted-by":"crossref","unstructured":"Just S, Premraj R, Zimmermann T (2008) Towards the next generation of bug tracking systems. In: Proc. of the Symposium on visual languages and human-centric computing, pp 82\u201385","DOI":"10.1109\/VLHCC.2008.4639063"},{"issue":"1","key":"10507_CR38","doi-asserted-by":"publisher","first-page":"50","DOI":"10.1518\/hfes.46.1.50.30392","volume":"46","author":"JD Lee","year":"2004","unstructured":"Lee JD, See KA (2004) Trust in automation: Designing for appropriate reliance. Human Factors 46(1):50\u201380","journal-title":"Human Factors"},{"key":"10507_CR39","doi-asserted-by":"crossref","unstructured":"McElreath R (2020) Statistical rethinking: A Bayesian course with examples in R and Stan, 2nd edn. Chapman and Hall\/CRC","DOI":"10.1201\/9780429029608"},{"key":"10507_CR40","doi-asserted-by":"crossref","unstructured":"Murphy-Hill E, Murphy G (2014) Recommendation Delivery. In: Robillard M, Maalej W, Walker R et\u00a0al (eds) Recommendation Systems in Software Engineering. Springer, p 223\u2013242, http:\/\/link.springer.com\/chapter\/10.1007\/978-3-642-45135-5_9","DOI":"10.1007\/978-3-642-45135-5_9"},{"key":"10507_CR41","doi-asserted-by":"crossref","unstructured":"Oliveira P, Andrade RM, Barreto I et\u00a0al (2021) Issue auto-assignment in software projects with machine learning techniques. In: Proc. of the 8th International workshop on software engineering research and industrial practice (SER &IP), pp 65\u201372","DOI":"10.1109\/SER-IP52554.2021.00018"},{"key":"10507_CR42","unstructured":"Paleyes A, Urma RG, Lawrence ND (2020) Challenges in deploying machine learning: a survey of case studies. ACM Computing Surveys (CSUR)"},{"issue":"3","key":"10507_CR43","doi-asserted-by":"publisher","first-page":"286","DOI":"10.1109\/3468.844354","volume":"30","author":"R Parasuraman","year":"2000","unstructured":"Parasuraman R, Sheridan T, Wickens C (2000) A model for types and levels of human interaction with automation. Transactions on Systems, Man, and Cybernetics-Part A: Systems and Humans 30(3):286\u2013297","journal-title":"Transactions on Systems, Man, and Cybernetics-Part A: Systems and Humans"},{"key":"10507_CR44","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9780511803161","volume-title":"Causality: Models, reasoning and inference","author":"J Pearl","year":"2009","unstructured":"Pearl J (2009) Causality: Models, reasoning and inference, 2nd edn. Cambridge University Press, Cambridge, UK","edition":"2"},{"key":"10507_CR45","volume-title":"The Book of Why: The New Science of Cause and Effect","author":"J Pearl","year":"2018","unstructured":"Pearl J, Mackenzie D (2018) The Book of Why: The New Science of Cause and Effect, 1st edn. Basic Books Inc, USA","edition":"1"},{"key":"10507_CR46","unstructured":"Pearl J, Glymour M, Jewell N (2016) Causal Inference in Statistics: A Primer. Wiley"},{"key":"10507_CR47","doi-asserted-by":"crossref","unstructured":"Petersen K, Wohlin C (2009) Context in industrial software engineering research. In: Proc. of the 3rd International symposium on empirical software engineering and measurement, pp 401\u2013404","DOI":"10.1109\/ESEM.2009.5316010"},{"issue":"2\u20133","key":"10507_CR48","doi-asserted-by":"publisher","first-page":"105","DOI":"10.1145\/217278.217291","volume":"26","author":"G Premkumar","year":"1995","unstructured":"Premkumar G, Potter M (1995) Adoption of computer aided software engineering (case) technology: an innovation adoption perspective. ACM SIGMIS Database: the DATABASE for Advances in Information Systems 26(2\u20133):105\u2013124","journal-title":"ACM SIGMIS Database: the DATABASE for Advances in Information Systems"},{"issue":"2","key":"10507_CR49","doi-asserted-by":"publisher","first-page":"42","DOI":"10.1109\/MS.2008.48","volume":"25","author":"B Regnell","year":"2008","unstructured":"Regnell B, Berntsson Svensson R, Olsson T (2008) Supporting roadmapping of quality requirements. IEEE Softw 25(2):42\u201347","journal-title":"IEEE Softw"},{"issue":"10","key":"10507_CR50","volume":"33","author":"S Rico","year":"2021","unstructured":"Rico S, Bjarnason E, Engstr\u00f6m E et al (2021) A case study of industry-academia communication in a joint software engineering research project. J Softw: Evolution Process 33(10):e2372","journal-title":"J Softw: Evolution Process"},{"key":"10507_CR51","doi-asserted-by":"crossref","unstructured":"Runeson P, H\u00f6st M, Rainer A, et\u00a0al (2012) Case study research in software engineering: Guidelines and examples. John Wiley & Sons","DOI":"10.1002\/9781118181034"},{"key":"10507_CR52","doi-asserted-by":"crossref","unstructured":"Runeson P, Engstr\u00f6m E, Storey M (2020) The design science paradigm as a frame for empirical software engineering. In: Contemporary empirical methods in software engineering. Springer, p 127\u2013147","DOI":"10.1007\/978-3-030-32489-6_5"},{"issue":"9","key":"10507_CR53","volume":"32","author":"A Sajedi-Badashian","year":"2020","unstructured":"Sajedi-Badashian A, Stroulia E (2020) Guidelines for evaluating bug-assignment research. J Softw: Evolution Process 32(9):e2250","journal-title":"J Softw: Evolution Process"},{"key":"10507_CR54","doi-asserted-by":"crossref","unstructured":"Sarkar A, Rigby P, Bartalos B (2019) Improving bug triaging with high confidence predictions at Ericsson. In: Proc. of the international conference on software maintenance and evolution, IEEE, pp 81\u201391","DOI":"10.1109\/ICSME.2019.00018"},{"issue":"4","key":"10507_CR55","doi-asserted-by":"publisher","first-page":"337","DOI":"10.1109\/TDSC.2009.4","volume":"7","author":"B Schroeder","year":"2009","unstructured":"Schroeder B, Gibson GA (2009) A large-scale study of failures in high-performance computing systems. IEEE Trans Dependable Secure Comput 7(4):337\u2013350","journal-title":"IEEE Trans Dependable Secure Comput"},{"key":"10507_CR56","unstructured":"Stan Development Team (2022) Stan Modeling Language User\u2019s Guide and Reference Manual, Version 2.30. http:\/\/mc-stan.org\/"},{"key":"10507_CR57","unstructured":"Stefi A (2015) Do developers make unbiased decisions? The effect of mindfulness and not-invented-here bias on the adoption of software components. In: Proc. of the 23rd European conference on information systems, p Paper 175"},{"key":"10507_CR58","doi-asserted-by":"publisher","unstructured":"Tantithamthavorn C, Jiarpakdee J (2021). Monash University, https:\/\/doi.org\/10.5281\/zenodo.4769127, http:\/\/xai4se.github.io\/, retrieved 2021-05-17","DOI":"10.5281\/zenodo.4769127"},{"key":"10507_CR59","doi-asserted-by":"crossref","unstructured":"Textor J, Van der Zander B, Gilthorpe MS et al (2016) Robust causal inference using directed acyclic graphs: the r package \u2018dagitty\u2019 . Int J Epidemiol 45(6):1887\u20131894","DOI":"10.1093\/ije\/dyw341"},{"key":"10507_CR60","doi-asserted-by":"crossref","unstructured":"Vogelsang A, Borg M (2019) Requirements engineering for machine learning: Perspectives from data scientists. In: 2019 IEEE 27th International requirements engineering conference workshops (REW), IEEE, pp 245\u2013251","DOI":"10.1109\/REW.2019.00050"},{"key":"10507_CR61","unstructured":"Wirth R, Hipp J (2000) Crisp-dm: Towards a standard process model for data mining. In: Proceedings of the 4th international conference on the practical applications of knowledge discovery and data mining, Manchester, pp 29\u201339"},{"issue":"3","key":"10507_CR62","doi-asserted-by":"publisher","first-page":"258","DOI":"10.1049\/iet-sen.2017.0159","volume":"12","author":"H Wu","year":"2018","unstructured":"Wu H, Liu H, Ma Y (2018) Empirical study on developer factors affecting tossing path length of bug reports. IET Softw 12(3):258\u2013270","journal-title":"IET Softw"},{"key":"10507_CR63","doi-asserted-by":"crossref","unstructured":"Zhang H, Gong L, Versteeg S (2013) Predicting bug-fixing time: an empirical study of commercial software projects. In: 2013 35th International conference on software engineering (ICSE), IEEE, pp 1042\u20131051","DOI":"10.1109\/ICSE.2013.6606654"},{"issue":"8","key":"10507_CR64","doi-asserted-by":"publisher","first-page":"836","DOI":"10.1109\/TSE.2018.2870414","volume":"46","author":"W Zou","year":"2018","unstructured":"Zou W, Lo D, Chen Z et al (2018) How practitioners perceive automated bug report management techniques. IEEE Trans Softw Eng 46(8):836\u2013862","journal-title":"IEEE Trans Softw Eng"}],"container-title":["Empirical Software Engineering"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10664-024-10507-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10664-024-10507-y\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10664-024-10507-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,6]],"date-time":"2024-09-06T03:57:15Z","timestamp":1725595035000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10664-024-10507-y"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,7,30]]},"references-count":64,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2024,9]]}},"alternative-id":["10507"],"URL":"https:\/\/doi.org\/10.1007\/s10664-024-10507-y","relation":{},"ISSN":["1382-3256","1573-7616"],"issn-type":[{"value":"1382-3256","type":"print"},{"value":"1573-7616","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,7,30]]},"assertion":[{"value":"22 May 2024","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"30 July 2024","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"Ericsson representatives reviewed the manuscript to ensure that no sensitive information about products or processes was disclosed. Moreover, the second, fourth, and fifth authors are employed by Ericsson. The second author published the first conceptual paper about automated bug assignment at Ericsson. The first author joined shortly after to support the development and empirical evaluations of the tool that is now TRR. Beyond this, the authors have no competing interests to declare that are relevant to the content of this article.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of Interests"}}],"article-number":"126"}}