{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,27]],"date-time":"2025-10-27T16:19:28Z","timestamp":1761581968395},"reference-count":33,"publisher":"Institute of Electronics, Information and Communications Engineers (IEICE)","issue":"6","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEICE Trans. Inf. &amp; Syst."],"published-print":{"date-parts":[[2020,6,1]]},"DOI":"10.1587\/transinf.2019kbp0019","type":"journal-article","created":{"date-parts":[[2020,5,31]],"date-time":"2020-05-31T22:09:58Z","timestamp":1590962998000},"page":"1319-1327","source":"Crossref","is-referenced-by-count":1,"title":["Evaluation of Software Fault Prediction Models Considering Faultless Cases"],"prefix":"10.1587","volume":"E103.D","author":[{"given":"Yukasa","family":"MURAKAMI","sequence":"first","affiliation":[{"name":"Kindai University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Masateru","family":"TSUNODA","sequence":"additional","affiliation":[{"name":"Kindai University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Koji","family":"TODA","sequence":"additional","affiliation":[{"name":"Fukuoka Institute of Technology University"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"532","reference":[{"key":"1","doi-asserted-by":"crossref","unstructured":"[1] K.E. Bennin, J. Keung, P. Phannachitta, A. Monden, and S. Mensah, \u201cMAHAKIL: Diversity Based Oversampling Approach to Alleviate the Class Imbalance Issue in Software Defect Prediction,\u201d IEEE Trans. Softw. Eng., vol.44, no.6, pp.534-550, 2018.","DOI":"10.1109\/TSE.2017.2731766"},{"key":"2","doi-asserted-by":"publisher","unstructured":"[2] S. Bibi, G. Tsoumakas, I. Stamelos, and I. Vlahavas, \u201cRegression via Classification applied on software defect estimation,\u201d Expert Systems with Applications, vol.34, no.3, pp.2091-2101, 2008. 10.1016\/j.eswa.2007.02.012","DOI":"10.1016\/j.eswa.2007.02.012"},{"key":"3","doi-asserted-by":"publisher","unstructured":"[3] C. Burgess and M. Lefley, \u201cCan genetic programming improve software effort estimation? A comparative evaluation,\u201d Journal of Information and Software Technology, vol.43, no.14, pp.863-873, 2001. 10.1016\/s0950-5849(01)00192-6","DOI":"10.1016\/S0950-5849(01)00192-6"},{"key":"4","unstructured":"[4] S. Conte, H. Dunsmore, and V. Shen, Software Engineering, Metrics and Models, Benjamin\/Cummings, 1986."},{"key":"5","doi-asserted-by":"publisher","unstructured":"[5] N. Fenton, M. Neil, W. Marsh, P. Hearty, \u0141. Radli\u0144ski, and P. Krause, \u201cOn the effectiveness of early life cycle defect prediction with Bayesian Nets,\u201d Empirical Software Engineering, vol.13, no.5, pp.499-537, 2008. 10.1007\/s10664-008-9072-x","DOI":"10.1007\/s10664-008-9072-x"},{"key":"6","doi-asserted-by":"publisher","unstructured":"[6] F. Gonz\u00e1lez-Ladr\u00f3n-de-Guevara, M. Fern\u00e1ndez-Diego, and C. Lokan, \u201cThe usage of ISBSG data fields in software effort estimation: A systematic mapping study,\u201d Journal of Systems and Software, vol.113, pp.188-215, 2016. 10.1016\/j.jss.2015.11.040","DOI":"10.1016\/j.jss.2015.11.040"},{"key":"7","doi-asserted-by":"publisher","unstructured":"[7] T. Hall, S. Beecham, D. Bowes, D. Gray, and S. Counsell, \u201cA Systematic Literature Review on Fault Prediction Performance in Software Engineering,\u201d IEEE Trans. Softw. Eng., vol.38, no.6, pp.1276-1304, 2012. 10.1109\/tse.2011.103","DOI":"10.1109\/TSE.2011.103"},{"key":"8","doi-asserted-by":"crossref","unstructured":"[8] H. Hata, O. Mizuno, and T. Kikuno, \u201cBug prediction based on fine-grained module histories,\u201d Proc. International Conference on Software Engineering (ICSE), pp.200-210, 2012. 10.1109\/icse.2012.6227193","DOI":"10.1109\/ICSE.2012.6227193"},{"key":"9","unstructured":"[9] International Software Benchmarking Standards Group, ISBSG Estimating, Benchmarking and Research Suite Release 9, ISBSG, 2004."},{"key":"10","doi-asserted-by":"publisher","unstructured":"[10] Y. Kamei, E. Shihab, B. Adams, A.E. Hassan, A. Mockus, A. Sinha, and N. Ubayashi, \u201cA Large-Scale Empirical Study of Just-In-Time Quality Assurance,\u201d IEEE Trans. Softw. Eng., vol.39, no.6, pp.757-773, 2013. 10.1109\/tse.2012.70","DOI":"10.1109\/TSE.2012.70"},{"key":"11","doi-asserted-by":"crossref","unstructured":"[11] Y. Kastro and A. Bener, \u201cA fault prediction method for software versioning,\u201d Software Quality Control, vol.16, no.4, pp.543-562, 2008.","DOI":"10.1007\/s11219-008-9053-8"},{"key":"12","unstructured":"[12] T. Khoshgoftaar, K. Gao, and R. Szabo, \u201cAn application of zero-inflated poisson regression for software fault prediction,\u201d Proc. International Symposium on Software Reliability Engineering (ISSRE), pp.66-73, 2001. 10.1109\/issre.2001.989459"},{"key":"13","doi-asserted-by":"publisher","unstructured":"[13] T. Khoshgoftaar and N. Seliya, \u201cFault Prediction Modeling for Software Quality Estimation: Comparing Commonly Used Techniques,\u201d Empirical Software Engineering, vol.8, no.3, pp.255-283, 2003. 10.1023\/a:1024424811345","DOI":"10.1023\/A:1024424811345"},{"key":"14","doi-asserted-by":"publisher","unstructured":"[14] B. Kitchenham, S. MacDonell, L. Pickard, and M. Shepperd, \u201cWhat Accuracy Statistics Really Measure,\u201d Proc. IEE Software, vol.148, no.3, pp.81-85, 2001. 10.1049\/ip-sen:20010506","DOI":"10.1049\/ip-sen:20010506"},{"key":"15","doi-asserted-by":"crossref","unstructured":"[15] B. Kitchenham and E. Mendes, \u201cWhy comparative effort prediction studies may be invalid,\u201d Proc. International Conference on Predictor Models in Software Engineering (PROMISE), art.4, p.5, 2009. 10.1145\/1540438.1540444","DOI":"10.1145\/1540438.1540444"},{"key":"16","doi-asserted-by":"crossref","unstructured":"[16] J. Klein and M. Moeschberger, Survival Analysis: Techniques for Censored and Truncated Data, Springer, 2003. 10.1007\/b97377","DOI":"10.1007\/b97377"},{"key":"17","doi-asserted-by":"publisher","unstructured":"[17] E. Kocaguneli, T. Menzies, and J. Keung, \u201cOn the value of ensemble effort estimation,\u201d IEEE Trans. Softw. Eng., vol.38, no.6, pp.1403-1416, 2012. 10.1109\/tse.2011.111","DOI":"10.1109\/TSE.2011.111"},{"key":"18","doi-asserted-by":"publisher","unstructured":"[18] M. Kondo, C. Bezemer, Y. Kamei, A. Hassan, and O. Mizuno, \u201cThe impact of feature reduction techniques on defect prediction models,\u201d Empirical Software Engineering, vol.24, no.4, pp.1925-1963, 2019. 10.1007\/s10664-018-9679-5","DOI":"10.1007\/s10664-018-9679-5"},{"key":"19","doi-asserted-by":"crossref","unstructured":"[19] A. Koru, D. Zhang, and H. Liu, \u201cModeling the Effect of Size on Fault Proneness for Open-Source Software,\u201d Proc. International Workshop on Predictor Models in Software Engineering (PROMISE), p.10, 2007.","DOI":"10.1109\/PROMISE.2007.9"},{"key":"20","unstructured":"[20] C. Lokan, \u201cWhat Should You Optimize When Building an Estimation Model?,\u201d Proc. International Software Metrics Symposium (METRICS), p.34, Como, Italy, Sept. 2005. 10.1109\/metrics.2005.55"},{"key":"21","doi-asserted-by":"crossref","unstructured":"[21] C. Lokan and E. Mendes, \u201cCross-company and single-company effort models using the ISBSG Database: a further replicated study,\u201d Proc. International Symposium on Empirical Software Engineering (ISESE), pp.75-84, Rio de Janeiro, Brazil, Sept. 2006. 10.1145\/1159733.1159747","DOI":"10.1145\/1159733.1159747"},{"key":"22","unstructured":"[22] E. Mendes, C. Lokan, R. Harrison, and C. Triggs, \u201cA Replicated Comparison of Cross-company and Within-company Effort Estimation Models using the ISBSG Database,\u201d Proc. International Software Metrics Symposium (METRICS), p.36, 2005. 10.1109\/metrics.2005.4"},{"key":"23","doi-asserted-by":"publisher","unstructured":"[23] Y. Miyazaki, M. Terakado, K. Ozaki, and H. Nozaki, \u201cRobust Regression for Developing Software Estimation Models,\u201d Journal of Systems and Software, vol.27, no.1, pp.3-16, 1994. 10.1016\/0164-1212(94)90110-4","DOI":"10.1016\/0164-1212(94)90110-4"},{"key":"24","unstructured":"[24] M. Mizuochi, \u201cIntroduction to Censored and Truncated Regression Models,\u201d Sociological Theory and Methods, vol.24, no.1, pp.129-138, 2009 (in Japanese)."},{"key":"25","doi-asserted-by":"publisher","unstructured":"[25] K. M\u00f8lokken-\u00d8stvold and M. J\u00f8rgensen, \u201cA Comparison of Software Project Overruns-Flexible versus Sequential Development Models,\u201d IEEE Trans. Softw. Eng., vol.31, no.9, pp.754-766, 2005. 10.1109\/tse.2005.96","DOI":"10.1109\/TSE.2005.96"},{"key":"26","doi-asserted-by":"crossref","unstructured":"[26] L. Pascarella, F. Palomba, and A. Bacchelli, \u201cRe-evaluating method-level bug prediction,\u201d Proc. International Conference on Software Analysis, Evolution and Reengineering (SANER), pp.592-601, 2018. 10.1109\/saner.2018.8330264","DOI":"10.1109\/SANER.2018.8330264"},{"key":"27","doi-asserted-by":"publisher","unstructured":"[27] I. Samoladas, L. Angelis, and I. Stamelos, \u201cSurvival analysis on the duration of open source projects,\u201d Information and Software Technology, vol.52, no.9, pp.902-922, 2010. 10.1016\/j.infsof.2010.05.001","DOI":"10.1016\/j.infsof.2010.05.001"},{"key":"28","doi-asserted-by":"publisher","unstructured":"[28] B. Shao and W. Lin, \u201cTechnical efficiency analysis of information technology investments: A two-stage empirical investigation,\u201d Information and Management, vol.39, no.5, pp.391-401, 2002. 10.1016\/s0378-7206(01)00105-7","DOI":"10.1016\/S0378-7206(01)00105-7"},{"key":"29","doi-asserted-by":"publisher","unstructured":"[29] M. Sojer and J. Henkel, \u201cLicense risks from ad hoc reuse of code from the internet,\u201d Communications of the ACM, vol.54, no.12, pp.74-81, 2011. 10.1145\/2043174.2043193","DOI":"10.1145\/2043174.2043193"},{"key":"30","doi-asserted-by":"publisher","unstructured":"[30] M. Sokolova and G. Lapalme, \u201cA systematic analysis of performance measures for classification tasks,\u201d Information Processing and Management, vol.45, no.4, pp.427-437, 2009. 10.1016\/j.ipm.2009.03.002","DOI":"10.1016\/j.ipm.2009.03.002"},{"key":"31","doi-asserted-by":"crossref","unstructured":"[31] J. Tobin, \u201cEstimation of relationships for limited dependent variables,\u201d Econometrica, vol.26, no.1, pp.24-36, 1956. 10.2307\/1907382","DOI":"10.2307\/1907382"},{"key":"32","doi-asserted-by":"crossref","unstructured":"[32] M. Usman, E. Mendes, F. Weidt, and R. Britto, \u201cEffort estimation in agile software development: a systematic literature review,\u201d Proc. International Conference on Predictive Models in Software Engineering (PROMISE), pp.82-91, 2014. 10.1145\/2639490.2639503","DOI":"10.1145\/2639490.2639503"},{"key":"33","doi-asserted-by":"crossref","unstructured":"[33] X. Yang, D. Lo, X. Xia, Y. Zhang, and J. Sun, \u201cDeep Learning for Just-in-Time Defect Prediction,\u201d Proc. International Conference on Software Quality, Reliability and Security, pp.17-26, 2015. 10.1109\/qrs.2015.14","DOI":"10.1109\/QRS.2015.14"}],"container-title":["IEICE Transactions on Information and Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.jstage.jst.go.jp\/article\/transinf\/E103.D\/6\/E103.D_2019KBP0019\/_pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,6,6]],"date-time":"2020-06-06T03:27:37Z","timestamp":1591414057000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.jstage.jst.go.jp\/article\/transinf\/E103.D\/6\/E103.D_2019KBP0019\/_article"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,6,1]]},"references-count":33,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2020]]}},"URL":"https:\/\/doi.org\/10.1587\/transinf.2019kbp0019","relation":{},"ISSN":["0916-8532","1745-1361"],"issn-type":[{"value":"0916-8532","type":"print"},{"value":"1745-1361","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,6,1]]}}}