{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,11]],"date-time":"2025-09-11T06:05:57Z","timestamp":1757570757254,"version":"3.40.3"},"publisher-location":"Cham","reference-count":42,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030646936"},{"type":"electronic","value":"9783030646943"}],"license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020]]},"DOI":"10.1007\/978-3-030-64694-3_14","type":"book-chapter","created":{"date-parts":[[2020,11,30]],"date-time":"2020-11-30T12:02:53Z","timestamp":1606737773000},"page":"229-244","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Investigating the Impact of Functional Size Measurement on Predicting Software Enhancement Effort Using Correlation-Based Feature Selection Algorithm and SVR Method"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1052-3502","authenticated-orcid":false,"given":"Zaineb","family":"Sakhrawi","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6739-5508","authenticated-orcid":false,"given":"Asma","family":"Sellami","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0434-2465","authenticated-orcid":false,"given":"Nadia","family":"Bouassida","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2020,12,1]]},"reference":[{"key":"14_CR1","doi-asserted-by":"crossref","unstructured":"Ali, S.S., Zafar, M.S., Saeed, M.T.: Effort estimation problems in software maintenance-a survey. In: 2020 3rd International Conference on Computing, Mathematics and Engineering Technologies (iCoMET), pp. 1\u20139. IEEE (2020)","DOI":"10.1109\/iCoMET48670.2020.9073823"},{"key":"14_CR2","first-page":"171","volume":"6","author":"A Bala","year":"2016","unstructured":"Bala, A., Abran, A.: Use of the multiple imputation strategy to deal with missing data in the ISBSG repository. J. Inf. Technol. Softw. Eng. 6, 171 (2016)","journal-title":"J. Inf. Technol. Softw. Eng."},{"key":"14_CR3","doi-asserted-by":"crossref","unstructured":"Basgalupp, M.P., Barros, R.C., Ruiz, D.D.: Predicting software maintenance effort through evolutionary-based decision trees. In: Proceedings of the 27th Annual ACM Symposium on Applied Computing, pp. 1209\u20131214 (2012)","DOI":"10.1145\/2245276.2231966"},{"issue":"5","key":"14_CR4","first-page":"33","volume":"5","author":"M Bhardwaj","year":"2015","unstructured":"Bhardwaj, M., Ajay, R.: Estimation of testing and rework efforts for software development projects. Asian J. Comput. Sci. Inf. Technol. 5(5), 33\u201337 (2015)","journal-title":"Asian J. Comput. Sci. Inf. Technol."},{"key":"14_CR5","doi-asserted-by":"publisher","unstructured":"Biesiada, J., Duch, W.: Feature selection for high-dimensional data\u2019a pearson redundancy based filter. In: Computer recognition systems, vol. 2, pp. 242\u2013249. Springer, Heidelberg (2007). https:\/\/doi.org\/10.1007\/978-3-540-75175-5_30","DOI":"10.1007\/978-3-540-75175-5_30"},{"issue":"3","key":"14_CR6","doi-asserted-by":"publisher","first-page":"385","DOI":"10.1260\/1748-3018.6.3.385","volume":"6","author":"EC Blessie","year":"2012","unstructured":"Blessie, E.C., Karthikeyan, E.: Sigmis: a feature selection algorithm using correlation based method. J. Algorithms Comput. Technol. 6(3), 385\u2013394 (2012)","journal-title":"J. Algorithms Comput. Technol."},{"issue":"2","key":"14_CR7","doi-asserted-by":"publisher","first-page":"82","DOI":"10.1049\/iet-sen.2018.5332","volume":"14","author":"S Cer\u00f3n-Figueroa","year":"2019","unstructured":"Cer\u00f3n-Figueroa, S., L\u00f3pez-Mart\u00edn, C., Y\u00e1\u00f1ez-M\u00e1rquez, C.: Stochastic gradient boosting for predicting the maintenance effort of software-intensive systems. IET Software 14(2), 82\u201387 (2019)","journal-title":"IET Software"},{"issue":"3","key":"14_CR8","first-page":"273","volume":"20","author":"C Cortes","year":"1995","unstructured":"Cortes, C., Vapnik, V.: Support-vector networks. Mach. Learn. 20(3), 273\u2013297 (1995)","journal-title":"Mach. Learn."},{"key":"14_CR9","doi-asserted-by":"crossref","unstructured":"Di Martino, S., Ferrucci, F., Gravino, C., Sarro, F.: Web effort estimation: function point analysis vs. cosmic. Inf. Software Technol. 72, 90\u2013109 (2016)","DOI":"10.1016\/j.infsof.2015.12.001"},{"key":"14_CR10","doi-asserted-by":"crossref","unstructured":"Di Martino, S., Ferrucci, F., Gravino, C., Sarro, F.: Assessing the effectiveness of approximate functional sizing approaches for effort estimation. Inf. Softw. Technol. 106308 (2020)","DOI":"10.1016\/j.infsof.2020.106308"},{"issue":"5","key":"14_CR11","doi-asserted-by":"publisher","first-page":"849","DOI":"10.1111\/j.1467-9868.2008.00674.x","volume":"70","author":"J Fan","year":"2008","unstructured":"Fan, J., Lv, J.: Sure independence screening for ultrahigh dimensional feature space. J. Royal Stat. Soc. Ser. B (Statistical Methodology) 70(5), 849\u2013911 (2008)","journal-title":"J. Royal Stat. Soc. Ser. B (Statistical Methodology)"},{"key":"14_CR12","doi-asserted-by":"publisher","first-page":"99","DOI":"10.1016\/j.infsof.2018.01.003","volume":"97","author":"A Garc\u00eda-Floriano","year":"2018","unstructured":"Garc\u00eda-Floriano, A., L\u00f3pez-Mart\u00edn, C., Y\u00e1\u00f1ez-M\u00e1rquez, C., Abran, A.: Support vector regression for predicting software enhancement effort. Inf. Softw. Technol. 97, 99\u2013109 (2018)","journal-title":"Inf. Softw. Technol."},{"key":"14_CR13","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"196","DOI":"10.1007\/978-3-540-89403-2_17","volume-title":"Software Process and Product Measurement","author":"C Gencel","year":"2008","unstructured":"Gencel, C.: How to use COSMIC functional size in effort estimation models? In: Dumke, R.R., Braungarten, R., B\u00fcren, G., Abran, A., Cuadrado-Gallego, J.J. (eds.) IWSM\/Mensura\/MetriKon -2008. LNCS, vol. 5338, pp. 196\u2013207. Springer, Heidelberg (2008). https:\/\/doi.org\/10.1007\/978-3-540-89403-2_17"},{"key":"14_CR14","doi-asserted-by":"crossref","unstructured":"Ghotra, B., McIntosh, S., Hassan, A.E.: A large-scale study of the impact of feature selection techniques on defect classification models. In: 2017 IEEE\/ACM 14th International Conference on Mining Software Repositories (MSR), pp. 146\u2013157. IEEE (2017)","DOI":"10.1109\/MSR.2017.18"},{"key":"14_CR15","unstructured":"Group, I.I.F.P.U.: Cosmic and IFPUG glossary of terms. A Functional Size Measurement Method (2011)"},{"key":"14_CR16","unstructured":"Group, I.I.F.P.U.: Cosmic and IFPUG glossary of terms. Common Software Measurement International Consortium (2015)"},{"key":"14_CR17","unstructured":"Group, S., et al.: Chaos summary 2009. Online report. Accessed 20 June 2009"},{"key":"14_CR18","doi-asserted-by":"publisher","first-page":"188","DOI":"10.1016\/j.jss.2015.11.040","volume":"113","author":"F Gonz\u00e1lez-Ladr\u00f3n-de Guevara","year":"2016","unstructured":"Gonz\u00e1lez-Ladr\u00f3n-de Guevara, F., Fern\u00e1ndez-Diego, M., Lokan, C.: The usage of ISBSG data fields in software effort estimation: a systematic mapping study. J. Syst. Softw. 113, 188\u2013215 (2016)","journal-title":"J. Syst. Softw."},{"key":"14_CR19","unstructured":"Hall, M.A.: Correlation-based feature selection for machine learning (1999)"},{"key":"14_CR20","doi-asserted-by":"publisher","first-page":"78","DOI":"10.1016\/j.infsof.2019.02.004","volume":"110","author":"M Haoues","year":"2019","unstructured":"Haoues, M., Sellami, A., Ben-Abdallah, H.: Towards functional change decision support based on cosmic FSM method. Inf. Softw. Technol. 110, 78\u201391 (2019)","journal-title":"Inf. Softw. Technol."},{"key":"14_CR21","doi-asserted-by":"crossref","unstructured":"Hira, A., Boehm, B.: Function point analysis for software maintenance. In: Proceedings of the 10th ACM\/IEEE International Symposium on Empirical Software Engineering and Measurement, pp. 1\u20136 (2016)","DOI":"10.1145\/2961111.2962613"},{"key":"14_CR22","doi-asserted-by":"crossref","unstructured":"Hira, A., Boehm, B.: Cosmic function points evaluation for software maintenance. In: Proceedings of the 11th Innovations in Software Engineering Conference, pp. 1\u201311 (2018)","DOI":"10.1145\/3172871.3172874"},{"key":"14_CR23","doi-asserted-by":"crossref","unstructured":"Hosni, M., Idri, A., Abran, A.: Investigating heterogeneous ensembles with filter feature selection for software effort estimation. In: Proceedings of the 27th International Workshop on Software Measurement and 12th International Conference on Software Process and Product Measurement, pp. 207\u2013220 (2017)","DOI":"10.1145\/3143434.3143456"},{"key":"14_CR24","doi-asserted-by":"publisher","first-page":"206","DOI":"10.1016\/j.infsof.2014.07.013","volume":"58","author":"A Idri","year":"2015","unstructured":"Idri, A., Azzahra Amazal, F., Abran, A.: Analogy-based software development effort estimation: a systematic mapping and review. Inf. Softw. Technol. 58, 206\u2013230 (2015)","journal-title":"Inf. Softw. Technol."},{"key":"14_CR25","unstructured":"IFPUG: International function point users group (IFPUG) function point counting practices manual (2000)"},{"key":"14_CR26","unstructured":"ISBSG: Repository data release 12\u2019field descriptions, e.field descriptions -data release 12.document provided as a part of data set, International Software Benchmarking and Standards Group (2013)"},{"key":"14_CR27","unstructured":"ISO\/IEC: International standard-iso\/iec 14764 ieee std 14764\u20132006 software engineering; software life cycle processes & ; maintenance (2006)"},{"key":"14_CR28","unstructured":"ISO\/IEC: ISO\/IEC 20926: Software and systems engineering - software measurement - IFPUG functional size measurement method. In: International Organization for Standardization, Geneva, Switzerland (2009)"},{"key":"14_CR29","unstructured":"Jayakumar, K.: why you must change to cosmic for sizing and estimation (2011)"},{"key":"14_CR30","doi-asserted-by":"crossref","unstructured":"Kaur, A., Kaur, K.: A cosmic function points based test effort estimation model for mobile applications. J. King Saud Univ. Comput. Inf. Sci. (2019)","DOI":"10.1016\/j.jksuci.2019.03.001"},{"issue":"16","key":"14_CR31","first-page":"69","volume":"1","author":"A Kaur","year":"2010","unstructured":"Kaur, A., Kaur, K., Malhotra, R.: Soft computing approaches for prediction of software maintenance effort. Int. J. Comput. Appl. 1(16), 69\u201375 (2010)","journal-title":"Int. J. Comput. Appl."},{"issue":"1","key":"14_CR32","first-page":"41","volume":"4","author":"S Kumari","year":"2013","unstructured":"Kumari, S., Pushkar, S.: Comparison and analysis of different software cost estimation methods. Int. J. Adv. Comput. Sci. Appl. 4(1), 41 (2013)","journal-title":"Int. J. Adv. Comput. Sci. Appl."},{"key":"14_CR33","doi-asserted-by":"publisher","first-page":"434","DOI":"10.1016\/j.asoc.2014.10.033","volume":"27","author":"C L\u00f3pez-Mart\u00edn","year":"2015","unstructured":"L\u00f3pez-Mart\u00edn, C.: Predictive accuracy comparison between neural networks and statistical regression for development effort of software projects. Appl. Soft Comput. 27, 434\u2013449 (2015)","journal-title":"Appl. Soft Comput."},{"key":"14_CR34","unstructured":"Bourque, R.F.: Guide to the software engineering body of knowledge. In: SWEBOK V3.0. IEEE Computer Society (2014)"},{"key":"14_CR35","unstructured":"Quesada-L\u00f3pez, C., Jenkins, M.: An evaluation of functional size measurement methods, pp. 151\u2013165 (2015)"},{"key":"14_CR36","unstructured":"Sangwan, O.P., et al.: Software effort estimation using machine learning techniques. In: 2017 7th International Conference on Cloud Computing, Data Science & Engineering-Confluence, pp. 92\u201398. IEEE (2017)"},{"issue":"8","key":"14_CR37","doi-asserted-by":"publisher","first-page":"820","DOI":"10.1016\/j.infsof.2011.12.008","volume":"54","author":"M Shepperd","year":"2012","unstructured":"Shepperd, M., MacDonell, S.: Evaluating prediction systems in software project estimation. Inf. Softw. Technol. 54(8), 820\u2013827 (2012)","journal-title":"Inf. Softw. Technol."},{"key":"14_CR38","unstructured":"Shepperd, M., Schofield, C.: Estimating software project effort using analogies. In: Series on Software Engineering and Knowledge Engineering, 16, 64 (2005)"},{"key":"14_CR39","unstructured":"Symons, C.: A comparison of the key differences between the IFPUG and cosmic functional size measurement methods. In: Common Software Measurement International Consortium (2011)"},{"key":"14_CR40","unstructured":"Tran-Cao, D., Levesque, G.: Maintenance effort and cost estimation using software functional sizes. In: International Workshop on Software Measurement, Montreal, Canada (2003)"},{"issue":"2","key":"14_CR41","doi-asserted-by":"publisher","first-page":"135","DOI":"10.1023\/A:1009872202035","volume":"4","author":"F Walkerden","year":"1999","unstructured":"Walkerden, F., Jeffery, R.: An empirical study of analogy-based software effort estimation. Empirical Softw. Eng. 4(2), 135\u2013158 (1999)","journal-title":"Empirical Softw. Eng."},{"key":"14_CR42","doi-asserted-by":"crossref","unstructured":"Xu, Z., Liu, J., Yang, Z., An, G., Jia, X.: The impact of feature selection on defect prediction performance: an empirical comparison. In: 2016 IEEE 27th International Symposium on Software Reliability Engineering (ISSRE), pp. 309\u2013320. IEEE (2016)","DOI":"10.1109\/ISSRE.2016.13"}],"container-title":["Lecture Notes in Computer Science","Reuse in Emerging Software Engineering Practices"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-64694-3_14","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,12,3]],"date-time":"2020-12-03T16:15:53Z","timestamp":1607012153000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-64694-3_14"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9783030646936","9783030646943"],"references-count":42,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-64694-3_14","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2020]]},"assertion":[{"value":"1 December 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICSR","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Software and Software Reuse","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Hammamet","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Tunisia","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2020","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2 December 2020","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"4 December 2020","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"19","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icsr2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/icsr2020.wordpress.com\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Easychair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"60","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":"16","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":"2","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":"27% - 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":"3.35","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":"3","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":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}