{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,16]],"date-time":"2026-04-16T21:14:42Z","timestamp":1776374082076,"version":"3.51.2"},"reference-count":54,"publisher":"Springer Science and Business Media LLC","issue":"16","license":[{"start":{"date-parts":[[2024,7,20]],"date-time":"2024-07-20T00:00:00Z","timestamp":1721433600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,7,20]],"date-time":"2024-07-20T00:00:00Z","timestamp":1721433600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Supercomput"],"published-print":{"date-parts":[[2024,11]]},"DOI":"10.1007\/s11227-024-06366-5","type":"journal-article","created":{"date-parts":[[2024,7,20]],"date-time":"2024-07-20T07:01:53Z","timestamp":1721458913000},"page":"23565-23591","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Deriving change-prone thresholds from software evolution using ROC curves"],"prefix":"10.1007","volume":"80","author":[{"given":"Raed","family":"Shatnawi","sequence":"first","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,7,20]]},"reference":[{"issue":"12","key":"6366_CR1","doi-asserted-by":"publisher","first-page":"5690","DOI":"10.3390\/app11125690","volume":"11","author":"M Alenezi","year":"2021","unstructured":"Alenezi M (2021) Internal quality evolution of open-source software systems. Appl Sci 11(12):5690","journal-title":"Appl Sci"},{"issue":"3","key":"6366_CR2","first-page":"379","volume":"39","author":"S Christa","year":"2022","unstructured":"Christa S, Suma V, Mohan U (2022) Regression and decision tree approaches in predicting the effort in resolving incidents. Int J Bus Inf Syst 39(3):379\u2013399","journal-title":"Int J Bus Inf Syst"},{"key":"6366_CR3","doi-asserted-by":"publisher","first-page":"673","DOI":"10.1007\/s10515-016-0203-0","volume":"24","author":"R Malhotra","year":"2017","unstructured":"Malhotra R, Khanna M (2017) An exploratory study for software change prediction in object-oriented systems using hybridized techniques. Autom Softw Eng 24:673\u2013717","journal-title":"Autom Softw Eng"},{"key":"6366_CR4","doi-asserted-by":"publisher","first-page":"2511","DOI":"10.1007\/s00500-014-1576-2","volume":"19","author":"M Elish","year":"2015","unstructured":"Elish M, Aljamaan H, Ahmad I (2015) Three empirical studies on predicting software maintainability using ensemble methods. Soft Comput 19:2511\u20132524","journal-title":"Soft Comput"},{"issue":"23","key":"6366_CR5","doi-asserted-by":"publisher","first-page":"11377","DOI":"10.3390\/app112311377","volume":"11","author":"A Mishra","year":"2021","unstructured":"Mishra A, Shatnawi R, Catal C, Akbulut A (2021) Techniques for calculating software product metrics threshold values: a systematic mapping study. Appl Sci 11(23):11377","journal-title":"Appl Sci"},{"key":"6366_CR6","doi-asserted-by":"publisher","DOI":"10.1016\/j.jss.2020.110892","volume":"174","author":"M Kretsou","year":"2021","unstructured":"Kretsou M, Arvanitou M, Ampatzoglou A, Deligiannis I, Gerogiannis V (2021) Change impact analysis: a systematic mapping study. J Syst Softw 174:110892","journal-title":"J Syst Softw"},{"issue":"4","key":"6366_CR7","doi-asserted-by":"publisher","first-page":"2779","DOI":"10.1007\/s10586-021-03447-5","volume":"25","author":"Z Sakhrawi","year":"2022","unstructured":"Sakhrawi Z, Sellami A, Bouassida N (2022) Software enhancement effort estimation using correlation-based feature selection and stacking ensemble method. Clust Comput 25(4):2779\u20132792","journal-title":"Clust Comput"},{"issue":"8","key":"6366_CR8","doi-asserted-by":"publisher","first-page":"625","DOI":"10.1109\/TSE.2005.89","volume":"31","author":"A Koru","year":"2005","unstructured":"Koru A, Tian J (2005) Comparing high-change modules and modules with the highest measurement values in two large-scale open-source products. IEEE Trans Softw Eng 31(8):625\u2013642","journal-title":"IEEE Trans Softw Eng"},{"issue":"8","key":"6366_CR9","doi-asserted-by":"publisher","first-page":"491","DOI":"10.1109\/TSE.2004.41","volume":"30","author":"E Arisholm","year":"2004","unstructured":"Arisholm E, Briand L, F\u00f8yen A (2004) Dynamic coupling measurement for object-oriented software. IEEE Trans Softw Eng 30(8):491\u2013506","journal-title":"IEEE Trans Softw Eng"},{"issue":"15","key":"6366_CR10","doi-asserted-by":"publisher","first-page":"1551","DOI":"10.1002\/(SICI)1097-024X(19981225)28:15<1551::AID-SPE212>3.0.CO;2-0","volume":"28","author":"M Lindvall","year":"1998","unstructured":"Lindvall M (1998) Are large C++ classes change-prone? Empir Invest Software Pract Ex 28(15):1551\u20131558","journal-title":"Empir Invest Software Pract Ex"},{"issue":"6","key":"6366_CR11","doi-asserted-by":"publisher","first-page":"476","DOI":"10.1109\/32.295895","volume":"20","author":"S Chidamber","year":"1994","unstructured":"Chidamber S, Kemerer C (1994) A metrics suite for object-oriented design. IEEE Trans Softw Eng 20(6):476\u2013493","journal-title":"IEEE Trans Softw Eng"},{"issue":"8","key":"6366_CR12","doi-asserted-by":"publisher","first-page":"1397","DOI":"10.1016\/j.infsof.2013.02.009","volume":"55","author":"D Radjenovi\u0107","year":"2013","unstructured":"Radjenovi\u0107 D, Heri\u010dko M, Torkar R, \u017divkovi\u010d A (2013) Software fault prediction metrics: a systematic literature review. Inf Softw Technol 55(8):1397\u20131418","journal-title":"Inf Softw Technol"},{"issue":"1","key":"6366_CR13","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1002\/smr.404","volume":"22","author":"R Shatnawi","year":"2010","unstructured":"Shatnawi R, Li W, Swain J, Newman T (2010) Finding software metrics threshold values using roc curves. J Softw Maint Evol Res Pract 22(1):1\u201316","journal-title":"J Softw Maint Evol Res Pract"},{"issue":"2","key":"6366_CR14","doi-asserted-by":"publisher","first-page":"244","DOI":"10.1016\/j.jss.2011.05.044","volume":"85","author":"K Ferreira","year":"2012","unstructured":"Ferreira K, Bigonha M, Bigonha S, Mendes L, Almeida H (2012) Identifying thresholds for object-oriented software metrics. J Syst Softw 85(2):244\u2013257","journal-title":"J Syst Softw"},{"key":"6366_CR15","doi-asserted-by":"crossref","unstructured":"Oliveira P, Tulio F, Lima V (2014) Extracting Relative Thresholds for Source Code Metrics, In: IEEE Conference on Software Maintenance, Reengineering and Reverse Engineering (CSMR-WCRE) pp. 254\u2013263.","DOI":"10.1109\/CSMR-WCRE.2014.6747177"},{"issue":"8","key":"6366_CR16","first-page":"6339","volume":"34","author":"N Kaur","year":"2021","unstructured":"Kaur N, Singh H (2021) An empirical assessment of threshold techniques to discriminate the fault status of software. J King Saud Univ-Comput Inf Sci. 34(8):6339\u20136353","journal-title":"J King Saud Univ-Comput Inf Sci."},{"key":"6366_CR17","doi-asserted-by":"crossref","unstructured":"Hassan E, Holt R (2005) The top ten list: dynamic fault prediction, In: Proceedings of ICSM, pp. 263\u2013272.","DOI":"10.1109\/ICSM.2005.91"},{"key":"6366_CR18","doi-asserted-by":"crossref","unstructured":"Giger E, Pinzger M, Gall H (2012) Can we Predict Types of Code Changes? An Empirical Analysis, Mining Software Repositories (MSR), 2012, 9th IEEE Working Conference on, 2012, pp. 217\u2013226.","DOI":"10.1109\/MSR.2012.6224284"},{"key":"6366_CR19","doi-asserted-by":"publisher","first-page":"200","DOI":"10.1007\/s10664-011-9170-z","volume":"17","author":"H Lu","year":"2012","unstructured":"Lu H, Zhou Y, Xu B, Leung H, Chen L (2012) The ability of object-oriented metrics to predict change-proneness: a meta-analysis. Empir Softw Eng 17:200\u2013242. https:\/\/doi.org\/10.1007\/s10664-011-9170-z","journal-title":"Empir Softw Eng"},{"key":"6366_CR20","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.infsof.2017.07.003","volume":"92","author":"M Yan","year":"2017","unstructured":"Yan M, Zhang X, Liu C, Xu L, Yang M, Yang D (2017) Automated change-prone class prediction on unlabeled dataset using unsupervised method. Inf Softw Technol 92:1\u201316","journal-title":"Inf Softw Technol"},{"key":"6366_CR21","doi-asserted-by":"publisher","first-page":"778","DOI":"10.3745\/JIPS.04.0013","volume":"13","author":"R Malhotra","year":"2017","unstructured":"Malhotra R, Rupender J (2017) Prediction & assessment of change prone classes using statistical & machine learning techniques. J Inf Process Syst 13:778\u2013804. https:\/\/doi.org\/10.3745\/JIPS.04.0013","journal-title":"J Inf Process Syst"},{"key":"6366_CR22","doi-asserted-by":"crossref","unstructured":"Kumar L, Rath S, and Sureka A (2017) Empirical Analysis on Effectiveness of Source Code Metrics for Predicting Change-Proneness, In: Proceedings of the 10th Innovations in Software Engineering Conference (ISEC \u201817). Association for Computing Machinery, New York, NY, USA, 4\u201314.","DOI":"10.1145\/3021460.3021461"},{"issue":"21","key":"6366_CR23","doi-asserted-by":"publisher","first-page":"4867","DOI":"10.1016\/j.ins.2011.06.017","volume":"181","author":"C Catal","year":"2011","unstructured":"Catal C, Alan O, Balkan K (2011) Class noise detection based on software metrics and ROC curves. Inf Sci 181(21):4867\u20134877","journal-title":"Inf Sci"},{"issue":"2","key":"6366_CR24","doi-asserted-by":"publisher","first-page":"216","DOI":"10.1109\/TSE.2010.9","volume":"36","author":"R Shatnawi","year":"2010","unstructured":"Shatnawi R (2010) A quantitative investigation of the acceptable risk levels of object-oriented metrics in open-source systems. IEEE Trans Software Eng 36(2):216\u2013225","journal-title":"IEEE Trans Software Eng"},{"key":"6366_CR25","doi-asserted-by":"publisher","first-page":"203","DOI":"10.1111\/exsy.12078","volume":"32","author":"R Malhotra","year":"2015","unstructured":"Malhotra R, Bansal A (2015) Fault prediction considering threshold effects of object-oriented metrics. Expert Syst 32:203\u2013219","journal-title":"Expert Syst"},{"key":"6366_CR26","doi-asserted-by":"publisher","first-page":"106","DOI":"10.1016\/j.eswa.2016.05.018","volume":"61","author":"O Arar","year":"2016","unstructured":"Arar O, Ayan K (2016) Deriving thresholds of software metrics to predict faults on open source software: replicated case studies. Expert Syst Appl 61:106\u2013121","journal-title":"Expert Syst Appl"},{"key":"6366_CR27","doi-asserted-by":"publisher","first-page":"38","DOI":"10.1016\/j.infsof.2017.11.005","volume":"196","author":"A Boucher","year":"2018","unstructured":"Boucher A, Badri M (2018) Software metrics thresholds calculation techniques to predict fault-proneness: an empirical comparison. Inf Softw Technol 196:38\u201367","journal-title":"Inf Softw Technol"},{"key":"6366_CR28","doi-asserted-by":"crossref","unstructured":"Samal U, Kumar A (2023) Redefining software reliability modeling: embracing fault-dependency, imperfect removal, and maximum fault considerations. Qual Eng 1\u201310.","DOI":"10.1080\/08982112.2023.2241067"},{"key":"6366_CR29","doi-asserted-by":"crossref","unstructured":"Malhotra R, Chug A, & Khosla P (2015) Prioritization of Classes for Refactoring: a Step Towards Improvement in Software Quality. In: Proceedings of the Third International Symposium on Women in Computing and Informatics (pp. 228\u2013234).","DOI":"10.1145\/2791405.2791463"},{"issue":"8","key":"6366_CR30","doi-asserted-by":"publisher","DOI":"10.1002\/smr.2255","volume":"32","author":"B Mayvan","year":"2020","unstructured":"Mayvan B, Rasoolzadegan A, Javan Jafari A (2020) Bad smell detection using quality metrics and refactoring opportunities. J Softw Evol Process 32(8):e2255","journal-title":"J Softw Evol Process"},{"key":"6366_CR31","doi-asserted-by":"crossref","unstructured":"Alves T, Christiaan Y. Joost V (2010) Deriving Metric Thresholds From Benchmark Data. In: Proceedings of the IEEE International Conference on Software Maintenance (ICSM), Timisoara, Romania, 12\u201318; pp. 1\u201310.","DOI":"10.1109\/ICSM.2010.5609747"},{"issue":"3","key":"6366_CR32","doi-asserted-by":"publisher","first-page":"640","DOI":"10.1007\/s10664-013-9291-7","volume":"20","author":"R Jabangwe","year":"2015","unstructured":"Jabangwe R, Borstler J, Smite D, Wohlin C (2015) Empirical evidence on the link between object-oriented measures and external quality attributes: a systematic literature review. Empir Softw Eng 20(3):640\u2013693s","journal-title":"Empir Softw Eng"},{"key":"6366_CR33","unstructured":"Abreu F, Goulao M, Esteves R (1995) Toward the Design Quality Evaluation of Object-Oriented Software Systems, In: Proceedings of the 5th International Conference on Software Quality, pp. 44\u201357, 1995."},{"issue":"1","key":"6366_CR34","doi-asserted-by":"publisher","first-page":"4","DOI":"10.1109\/32.979986","volume":"28","author":"J Bansiya","year":"2002","unstructured":"Bansiya J, Davis CG (2002) A hierarchical model for object-oriented design quality assessment. IEEE Trans Software Eng 28(1):4\u201317","journal-title":"IEEE Trans Software Eng"},{"key":"6366_CR35","volume-title":"Kidd J (1994) Object-oriented software metrics: A practical guide","author":"M Lorenz","year":"1994","unstructured":"Lorenz M (1994) Kidd J (1994) Object-oriented software metrics: A practical guide. Prentice-Hall, New Jersey, USA"},{"key":"6366_CR36","doi-asserted-by":"crossref","unstructured":"D\u2019Ambros M, Lanza M, Robbes R (2010) An Extensive Comparison of Bug Prediction Approaches, In: Proceedings of MSR 2010 (7th IEEE Working Conference on Mining Software Repositories), pp. 31 - 41. IEEE CS Press, 2010.","DOI":"10.1109\/MSR.2010.5463279"},{"key":"6366_CR37","unstructured":"Demeyer S, Tichelaar S, Ducasse S (2001) FAMIX 2.1\u2014The FAMOOS Information Exchange Model, University of Bern, Tech. Rep"},{"key":"6366_CR38","doi-asserted-by":"crossref","unstructured":"Wohlin C, Runeson P, H\u00f6st M, Ohlsson M, Regnell B, Wessl\u00e9n A (2012) Experimentation in software engineering, Springer Science & Business Media","DOI":"10.1007\/978-3-642-29044-2"},{"key":"6366_CR39","doi-asserted-by":"crossref","unstructured":"Elish M, Elish K (2009) Application of TreeNet in Predicting Object-Oriented Software Maintainability: a Comparative Study, In: 13th European Conference on Software Maintenance and Reengineering (CSMR \u201809), pp 69\u201378","DOI":"10.1109\/CSMR.2009.57"},{"issue":"1","key":"6366_CR40","doi-asserted-by":"publisher","first-page":"59","DOI":"10.1016\/j.infsof.2005.03.002","volume":"48","author":"C Koten","year":"2006","unstructured":"Koten C, Gray A (2006) An application of Bayesian network for predicting object-oriented software maintainability. Inf Softw Technol 48(1):59\u201367","journal-title":"Inf Softw Technol"},{"issue":"1","key":"6366_CR41","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/2556777","volume":"23","author":"Y Zhou","year":"2014","unstructured":"Zhou Y, Xu B, Leung H, Chen L (2014) An in-depth study of the potentially confounding effect of class size in fault prediction. ACM Trans Software Eng Methodol 23(1):1\u201351","journal-title":"ACM Trans Software Eng Methodol"},{"key":"6366_CR42","doi-asserted-by":"crossref","unstructured":"Kaur A, Kaur M, and Kaur H (2016) Application of Machine Learning on Process Metrics for Defect Prediction in Mobile Application, In: Information Systems Design and Intelligent Applications, pp. 81\u201398.","DOI":"10.1007\/978-81-322-2755-7_10"},{"key":"6366_CR43","first-page":"2","volume":"30","author":"A Kaur","year":"2018","unstructured":"Kaur A, Kaur M (2018) An empirical evaluation of classification algorithms for fault prediction in open source projects. J King Saud Univ\u2014Comput Inf Sci 30:2\u201317","journal-title":"J King Saud Univ\u2014Comput Inf Sci"},{"issue":"2","key":"6366_CR44","doi-asserted-by":"publisher","first-page":"334","DOI":"10.1007\/s13198-016-0438-y","volume":"8","author":"R Jindal","year":"2017","unstructured":"Jindal R, Malhotra R, Jain A (2017) Prediction of defect severity by mining software project reports. Int J Syst Assur Eng Manag 8(2):334\u2013351","journal-title":"Int J Syst Assur Eng Manag"},{"key":"6366_CR45","doi-asserted-by":"publisher","DOI":"10.1002\/0471722146","volume-title":"Applied Logistic Regression","author":"D Hosmer","year":"2000","unstructured":"Hosmer D, Lemeshow S (2000) Applied Logistic Regression, 2nd edn. New York NY, Wiley-Interscience","edition":"2"},{"key":"6366_CR46","doi-asserted-by":"publisher","first-page":"86","DOI":"10.1016\/j.infsof.2017.11.001","volume":"95","author":"J Al Dallal","year":"2018","unstructured":"Al Dallal J, Morasca S (2018) Investigating the impact of fault data completeness over time on predicting class fault-proneness. Inf Softw Technol 95:86\u2013105","journal-title":"Inf Softw Technol"},{"key":"6366_CR47","doi-asserted-by":"publisher","first-page":"6038619","DOI":"10.1155\/2020\/6038619","volume":"2020","author":"S Meilong","year":"2020","unstructured":"Meilong S, He P, Xiao H, Li H, Zeng C (2020) An approach to semantic and structural features learning for software defect prediction. Math Probl Eng 2020:6038619","journal-title":"Math Probl Eng"},{"issue":"3","key":"6366_CR48","doi-asserted-by":"publisher","first-page":"167","DOI":"10.1002\/smr.229","volume":"13","author":"M Ohlsson","year":"2001","unstructured":"Ohlsson M, Amschler A, Wohlin C (2001) Modelling fault-proneness statistically over a sequence of releases: a case study. J Softw Maint 13(3):167\u2013199","journal-title":"J Softw Maint"},{"issue":"3","key":"6366_CR49","doi-asserted-by":"publisher","first-page":"191","DOI":"10.1007\/s40012-014-0057-1","volume":"2","author":"S Singh","year":"2014","unstructured":"Singh S, Kahlon K (2014) Object-oriented software metrics threshold values at quantitative acceptable risk level. CSI Trans ICT 2(3):191\u2013205","journal-title":"CSI Trans ICT"},{"key":"6366_CR50","doi-asserted-by":"crossref","unstructured":"Hussain S, Keung J, Khan A, Ebo Bennin K (2016) Detection of fault-prone classes using logistic regression based object-oriented metrics thresholds, Software Quality, Reliability and Security Companion (QRS-C), IEEE International Conference on, pp. 93\u2013100.","DOI":"10.1109\/QRS-C.2016.16"},{"key":"6366_CR51","doi-asserted-by":"publisher","first-page":"201","DOI":"10.1007\/s11334-017-0295-0","volume":"13","author":"R Shatnawi","year":"2017","unstructured":"Shatnawi R (2017) The application of ROC analysis in threshold identification data imbalance and metrics selection for software fault prediction. Innov Syst Soft Eng 13:201\u2013217","journal-title":"Innov Syst Soft Eng"},{"key":"6366_CR52","doi-asserted-by":"publisher","first-page":"561","DOI":"10.1007\/s10664-008-9079-3","volume":"13","author":"Y Jiang","year":"2008","unstructured":"Jiang Y, Cukic B, Ma Y (2008) Techniques for evaluating fault prediction models. Empir Softw Eng 13:561\u2013595","journal-title":"Empir Softw Eng"},{"key":"6366_CR53","doi-asserted-by":"crossref","unstructured":"Bird C, Bachmann A, Aune E, Duffy J, Bernstein A, Filkov V, and Devanbu P (2009) Fair and balanced: Bias in bug-fix datasets, 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 2009), pp. 121\u2013130.","DOI":"10.1145\/1595696.1595716"},{"key":"6366_CR54","doi-asserted-by":"publisher","DOI":"10.1007\/s00180-023-01430-9","author":"U Samal","year":"2023","unstructured":"Samal U, Kumar A (2023) A software reliability model incorporating fault removal efficiency and it\u2019s release policy. Comput Stat. https:\/\/doi.org\/10.1007\/s00180-023-01430-9","journal-title":"Comput Stat"}],"container-title":["The Journal of Supercomputing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11227-024-06366-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11227-024-06366-5\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11227-024-06366-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,8,24]],"date-time":"2024-08-24T12:17:06Z","timestamp":1724501826000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11227-024-06366-5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,7,20]]},"references-count":54,"journal-issue":{"issue":"16","published-print":{"date-parts":[[2024,11]]}},"alternative-id":["6366"],"URL":"https:\/\/doi.org\/10.1007\/s11227-024-06366-5","relation":{},"ISSN":["0920-8542","1573-0484"],"issn-type":[{"value":"0920-8542","type":"print"},{"value":"1573-0484","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,7,20]]},"assertion":[{"value":"14 July 2024","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"20 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":"The authors declare no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}