{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T13:06:51Z","timestamp":1743080811433,"version":"3.40.3"},"publisher-location":"Cham","reference-count":25,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030914516"},{"type":"electronic","value":"9783030914523"}],"license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"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":[],"published-print":{"date-parts":[[2021]]},"DOI":"10.1007\/978-3-030-91452-3_12","type":"book-chapter","created":{"date-parts":[[2021,11,23]],"date-time":"2021-11-23T20:00:31Z","timestamp":1637697631000},"page":"183-198","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Searching for Bellwether Developers for Cross-Personalized Defect Prediction"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8763-3457","authenticated-orcid":false,"given":"Sousuke","family":"Amasaki","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7074-5225","authenticated-orcid":false,"given":"Hirohisa","family":"Aman","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6681-2608","authenticated-orcid":false,"given":"Tomoyuki","family":"Yokogawa","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2021,11,23]]},"reference":[{"key":"12_CR1","doi-asserted-by":"publisher","unstructured":"Cabral, G.G., Minku, L.L., Shihab, E., Mujahid, S.: Class imbalance evolution and verification latency in just-in-time software defect prediction. In: 2019 IEEE\/ACM 41st International Conference on Software Engineering (ICSE), pp. 666\u2013676 (2019). https:\/\/doi.org\/10.1109\/ICSE.2019.00076","DOI":"10.1109\/ICSE.2019.00076"},{"key":"12_CR2","doi-asserted-by":"publisher","unstructured":"Catolino, G., Di Nucci, D., Ferrucci, F.: Cross-project just-in-time bug prediction for mobile apps: An empirical assessment. In: 2019 IEEE\/ACM 6th International Conference on Mobile Software Engineering and Systems (MOBILESoft), pp. 99\u2013110 (2019). https:\/\/doi.org\/10.1109\/MOBILESoft.2019.00023","DOI":"10.1109\/MOBILESoft.2019.00023"},{"key":"12_CR3","doi-asserted-by":"publisher","first-page":"321","DOI":"10.1613\/jair.953","volume":"16","author":"NV Chawla","year":"2002","unstructured":"Chawla, N.V., Bowyer, K.W., Hall, L.O., Kegelmeyer, W.P.: SMOTE: synthetic minority over-sampling technique. J. Artif. Intell. Res. 16, 321\u2013357 (2002)","journal-title":"J. Artif. Intell. Res."},{"key":"12_CR4","doi-asserted-by":"crossref","unstructured":"He, Z., Peters, F., Menzies, T., Yang, Y.: Learning from open-source projects: an empirical study on defect prediction. In: Proceedings of ESEM 2013, pp. 45\u201354. IEEE (2013)","DOI":"10.1109\/ESEM.2013.20"},{"key":"12_CR5","unstructured":"Herbold, S.: Training data selection for cross-project defect prediction. In: Proceedings of PROMISE \u201913, pp. 6:1\u20136:10. ACM (2013)"},{"issue":"2","key":"12_CR6","doi-asserted-by":"publisher","first-page":"111","DOI":"10.1109\/TSE.2017.2770124","volume":"45","author":"S Hosseini","year":"2019","unstructured":"Hosseini, S., Turhan, B., Gunarathna, D.: A systematic literature review and meta-analysis on cross project defect prediction. IEEE Trans. Softw. Eng. 45(2), 111\u2013147 (2019)","journal-title":"IEEE Trans. Softw. Eng."},{"key":"12_CR7","doi-asserted-by":"publisher","unstructured":"Jahanshahi, H., Jothimani, D., Ba\u015far, A., Cevik, M.: Does chronology matter in JIT defect prediction? A partial replication study. In: Proceedings of the Fifteenth International Conference on Predictive Models and Data Analytics in Software Engineering, pp. 90\u201399 (2019). https:\/\/doi.org\/10.1145\/3345629.3351449","DOI":"10.1145\/3345629.3351449"},{"key":"12_CR8","doi-asserted-by":"crossref","unstructured":"Jiang, T., Tan, L., Kim, S.: Personalized defect prediction. In: Proceedings of International Conference on Automated Software Engineering, pp. 279\u2013289 (2013)","DOI":"10.1109\/ASE.2013.6693087"},{"issue":"6","key":"12_CR9","doi-asserted-by":"publisher","first-page":"2072","DOI":"10.1007\/s10664-015-9400-x","volume":"21","author":"Y Kamei","year":"2016","unstructured":"Kamei, Y., Fukushima, T., McIntosh, S., Yamashita, K., Ubayashi, N., Hassan, A.E.: Studying just-in-time defect prediction using cross-project models. Empir. Softw. Eng. 21(6), 2072\u20132106 (2016). https:\/\/doi.org\/10.1007\/s10664-015-9400-x","journal-title":"Empir. Softw. Eng."},{"issue":"6","key":"12_CR10","doi-asserted-by":"publisher","first-page":"757","DOI":"10.1109\/TSE.2012.70","volume":"39","author":"Y Kamei","year":"2013","unstructured":"Kamei, Y., et al.: A large-scale empirical study of just-in-time quality assurance. IEEE Trans. Softw. Eng. 39(6), 757\u2013773 (2013). https:\/\/doi.org\/10.1109\/TSE.2012.70","journal-title":"IEEE Trans. Softw. Eng."},{"key":"12_CR11","doi-asserted-by":"crossref","unstructured":"Krishna, R., Menzies, T., Fu, W.: Too much automation? The bellwether effect and its implications for transfer learning. In: Proceedings of International Conference on Automated Software Engineering, pp. 122\u2013131 (2016)","DOI":"10.1145\/2970276.2970339"},{"key":"12_CR12","doi-asserted-by":"publisher","DOI":"10.1016\/j.infsof.2020.106364","volume":"126","author":"W Li","year":"2020","unstructured":"Li, W., Zhang, W., Jia, X., Huang, Z.: Effort-aware semi-supervised just-in-time defect prediction. Inf. Softw. Technol. 126, 106364 (2020). https:\/\/doi.org\/10.1016\/j.infsof.2020.106364","journal-title":"Inf. Softw. Technol."},{"key":"12_CR13","doi-asserted-by":"crossref","unstructured":"Ma, Y., Cukic, B.: Adequate and precise evaluation of quality models in software engineering studies. In: Proceedings of International Workshop on Predictor Models in Software Engineering, p. 9 (2007)","DOI":"10.1109\/PROMISE.2007.1"},{"issue":"4","key":"12_CR14","doi-asserted-by":"publisher","first-page":"537","DOI":"10.1109\/TSE.2012.45","volume":"39","author":"N Mittas","year":"2013","unstructured":"Mittas, N., Angelis, L.: Ranking and clustering software cost estimation models through a multiple comparisons algorithm. IEEE Trans. Softw. Eng. 39(4), 537\u2013551 (2013)","journal-title":"IEEE Trans. Softw. Eng."},{"key":"12_CR15","doi-asserted-by":"crossref","unstructured":"Panichella, A., Oliveto, R., De Lucia, A.: Cross-project defect prediction models: L\u2019Union fait la force. In: Proceedings of CSMR-WCRE \u201914, pp. 164\u2013173. IEEE (2014)","DOI":"10.1109\/CSMR-WCRE.2014.6747166"},{"key":"12_CR16","doi-asserted-by":"crossref","unstructured":"Rahman, F., Devanbu, P.: Ownership, experience and defects: a fine-grained study of authorship. In: Proceedings of International Conference on Software Engineering, pp. 491\u2013500 (2011)","DOI":"10.1145\/1985793.1985860"},{"issue":"6","key":"12_CR17","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/1218776.1218791","volume":"31","author":"A Schr\u00f6ter","year":"2006","unstructured":"Schr\u00f6ter, A., Zimmermann, T., Premraj, R., Zeller, A.: Where do bugs come from? SIGSOFT Softw. Eng. Notes 31(6), 1\u20132 (2006)","journal-title":"SIGSOFT Softw. Eng. Notes"},{"key":"12_CR18","doi-asserted-by":"publisher","unstructured":"Tabassum, S., Minku, L.L., Feng, D., Cabral, G.G., Song, L.: An investigation of cross-project learning in online just-in-time software defect prediction. In: Proceedings of International Conference on Software Engineering, New York, NY, USA, pp. 554\u2013565 (2020). https:\/\/doi.org\/10.1145\/3377811.3380403","DOI":"10.1145\/3377811.3380403"},{"key":"12_CR19","doi-asserted-by":"crossref","unstructured":"Trautsch, A., Herbold, S., Grabowski, J.: Static source code metrics and static analysis warnings for fine-grained just-in-time defect prediction. In: 2020 IEEE International Conference on Software Maintenance and Evolution (ICSME), pp. 127\u2013138 (2020)","DOI":"10.1109\/ICSME46990.2020.00022"},{"issue":"4","key":"12_CR20","doi-asserted-by":"publisher","first-page":"1810","DOI":"10.1109\/TR.2016.2588139","volume":"65","author":"X Xia","year":"2016","unstructured":"Xia, X., Lo, D., Wang, X., Yang, X.: Collective personalized change classification with multiobjective search. IEEE Trans. Reliab. 65(4), 1810\u20131829 (2016)","journal-title":"IEEE Trans. Reliab."},{"key":"12_CR21","doi-asserted-by":"publisher","first-page":"206","DOI":"10.1016\/j.infsof.2017.03.007","volume":"87","author":"X Yang","year":"2017","unstructured":"Yang, X., Lo, D., Xia, X., Sun, J.: TLEL: a two-layer ensemble learning approach for just-in-time defect prediction. Inf. Softw. Technol. 87, 206\u2013220 (2017)","journal-title":"Inf. Softw. Technol."},{"key":"12_CR22","doi-asserted-by":"crossref","unstructured":"Yang, Y., et al.: 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 (2016)","DOI":"10.1145\/2950290.2950353"},{"issue":"1","key":"12_CR23","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3183339","volume":"27","author":"Y Zhou","year":"2018","unstructured":"Zhou, Y., et al.: How far we have progressed in the journey? An examination of cross-project defect prediction. ACM Trans. Softw. Eng. Methodol. 27(1), 1\u201351 (2018)","journal-title":"ACM Trans. Softw. Eng. Methodol."},{"issue":"3","key":"12_CR24","doi-asserted-by":"publisher","first-page":"185","DOI":"10.1049\/iet-sen.2019.0278","volume":"14","author":"K Zhu","year":"2020","unstructured":"Zhu, K., Zhang, N., Ying, S., Zhu, D.: Within-project and cross-project just-in-time defect prediction based on denoising autoencoder and convolutional neural network. IET Softw. 14(3), 185\u2013195 (2020). https:\/\/doi.org\/10.1049\/iet-sen.2019.0278","journal-title":"IET Softw."},{"key":"12_CR25","doi-asserted-by":"crossref","unstructured":"Zimmermann, T., Nagappan, N., Gall, H., Giger, E., Murphy, B.: Cross-project defect prediction: a large scale experiment on data vs. domain vs. process. In: Proceedings of ESEC\/FSE \u201909, pp. 91\u2013100. ACM (2009)","DOI":"10.1145\/1595696.1595713"}],"container-title":["Lecture Notes in Computer Science","Product-Focused Software Process Improvement"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-91452-3_12","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,12,16]],"date-time":"2021-12-16T14:07:31Z","timestamp":1639663651000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-91452-3_12"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"ISBN":["9783030914516","9783030914523"],"references-count":25,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-91452-3_12","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2021]]},"assertion":[{"value":"23 November 2021","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"PROFES","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Product-Focused Software Process Improvement","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Turin","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Italy","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2021","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26 November 2021","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26 November 2021","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"profes2021","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/softeng.polito.it\/profes2021\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"EasaChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"48","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"17","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"35% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"2","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Out of the 20 accepted papers, 14 are full papers, 3 are short papers, and 3 are industry papers.","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}