{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2022,4,19]],"date-time":"2022-04-19T21:11:41Z","timestamp":1650402701949},"reference-count":32,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2021,2,7]],"date-time":"2021-02-07T00:00:00Z","timestamp":1612656000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,2,7]],"date-time":"2021-02-07T00:00:00Z","timestamp":1612656000000},"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":["Sci. China Inf. Sci."],"published-print":{"date-parts":[[2021,3]]},"DOI":"10.1007\/s11432-019-2902-5","type":"journal-article","created":{"date-parts":[[2021,2,14]],"date-time":"2021-02-14T08:37:00Z","timestamp":1613291820000},"update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Toward accurate detection on change barriers"],"prefix":"10.1007","volume":"64","author":[{"given":"Tingting","family":"Lv","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhilei","family":"Ren","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaochen","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guojun","family":"Gao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"He","family":"Jiang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2021,2,7]]},"reference":[{"key":"2902_CR1","volume-title":"Refactoring: Improving the Design of Existing Code","author":"M Fowler","year":"2018","unstructured":"Fowler M. Refactoring: Improving the Design of Existing Code. Hoboken: Addison-Wesley Professional, 2018"},{"key":"2902_CR2","unstructured":"Fontana F A, Ferme V, Zanoni M, et al. Automatic metric thresholds derivation for code smell detection. In: Proceedings of the 6th International Workshop on Emerging Trends in Software Metrics, Florence, 2015. 44\u201353"},{"key":"2902_CR3","doi-asserted-by":"publisher","first-page":"603","DOI":"10.1109\/TSC.2015.2502595","volume":"10","author":"A Ouni","year":"2017","unstructured":"Ouni A, Kessentini M, Inoue K, et al. Search-based web service antipatterns detection. IEEE Trans Serv Comput, 2017, 10: 603\u2013617","journal-title":"IEEE Trans Serv Comput"},{"key":"2902_CR4","doi-asserted-by":"crossref","unstructured":"Palomba F. Textual analysis for code smell detection. In: Proceedings of the 37th International Conference on Software Engineering-Volume 2, 2015. 769\u2013771","DOI":"10.1109\/ICSE.2015.244"},{"key":"2902_CR5","first-page":"020301","volume":"58","author":"C W Deng","year":"2015","unstructured":"Deng C W, Huang G B, Xu J, et al. Extreme learning machines: new trends and applications. Sci China Inf Sci, 2015, 58: 020301","journal-title":"Sci China Inf Sci"},{"key":"2902_CR6","doi-asserted-by":"publisher","first-page":"076101","DOI":"10.1007\/s11432-018-9801-4","volume":"62","author":"Z-H Zhou","year":"2019","unstructured":"Zhou Z-H. Abductive learning: towards bridging machine learning and logical reasoning. Sci China Inf Sci, 2019, 62: 076101","journal-title":"Sci China Inf Sci"},{"key":"2902_CR7","doi-asserted-by":"crossref","unstructured":"Khomh F, Vaucher S, Gu\u00e9h\u00e9neuc Y G, et al. A Bayesian approach for the detection of code and design smells. In: Proceedings of the 9th International Conference on Quality Software, 2009. 305\u2013314","DOI":"10.1109\/QSIC.2009.47"},{"key":"2902_CR8","doi-asserted-by":"publisher","first-page":"1143","DOI":"10.1007\/s10664-015-9378-4","volume":"21","author":"F A Fontana","year":"2016","unstructured":"Fontana F A, M\u00e4ntyl\u00e4 M V, Zanoni M, et al. Comparing and experimenting machine learning techniques for code smell detection. Empir Softw Eng, 2016, 21: 1143\u20131191","journal-title":"Empir Softw Eng"},{"key":"2902_CR9","doi-asserted-by":"crossref","unstructured":"Kaur A, Jain S, Goel S. A support vector machine based approach for code smell detection. In: Proceedings of International Conference on Machine Learning and Data Science (MLDS), 2017. 9\u201314","DOI":"10.1109\/MLDS.2017.8"},{"key":"2902_CR10","doi-asserted-by":"publisher","first-page":"117","DOI":"10.1016\/j.entcs.2005.02.059","volume":"141","author":"J Kreimer","year":"2005","unstructured":"Kreimer J. Adaptive detection of design flaws. Electron Notes Theor Comput Sci, 2005, 141: 117\u2013136","journal-title":"Electron Notes Theor Comput Sci"},{"key":"2902_CR11","doi-asserted-by":"crossref","unstructured":"Vaucher S, Khomh F, Moha N, et al. Tracking design smells: lessons from a study of God classes. In: Proceedings of the 16th Working Conference on Reverse Engineering, 2009. 145\u2013154","DOI":"10.1109\/WCRE.2009.23"},{"key":"2902_CR12","unstructured":"Linders B. Refactoring and Code Smells \u2014 A Journey Toward Cleaner Code. 2016. https:\/\/www.infoq.com\/news\/2016\/09\/refactoring-code-smells\/"},{"key":"2902_CR13","unstructured":"Cristina M, Radu M, Mihancea F, et al. iPlasma: an integrated platform for quality assessment of object-oriented design. In: Proceedings of the 21st IEEE International Conference on Software Maintenance, 2005. 77\u201380"},{"key":"2902_CR14","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/1449603.1449614","volume":"33","author":"P Singh","year":"2008","unstructured":"Singh P, Singh H. DynaMetrics: a runtime metric-based analysis tool for object-oriented software systems. SIGSOFT Softw Eng Notes, 2008, 33: 1\u20136","journal-title":"SIGSOFT Softw Eng Notes"},{"key":"2902_CR15","doi-asserted-by":"crossref","unstructured":"Eaddy M, Aho A, Murphy G C. Identifying, assigning, and quantifying crosscutting concerns. In: Proceedings of the 1st International Workshop on Assessment of Contemporary Modularization Techniques, 2007. 2","DOI":"10.1109\/ACOM.2007.4"},{"key":"2902_CR16","doi-asserted-by":"publisher","first-page":"476","DOI":"10.1109\/32.295895","volume":"20","author":"S R Chidamber","year":"1994","unstructured":"Chidamber S R, Kemerer C F. A metrics suite for object oriented design. IEEE Trans Softw Eng, 1994, 20: 476\u2013493","journal-title":"IEEE Trans Softw Eng"},{"key":"2902_CR17","doi-asserted-by":"crossref","unstructured":"Padilha J, Pereira J, Figueiredo E, et al. On the effectiveness of concern metrics to detect code smells: an empirical study. In: Proceedings of International Conference on Advanced Information Systems Engineering, 2014. 656\u2013671","DOI":"10.1007\/978-3-319-07881-6_44"},{"key":"2902_CR18","volume-title":"Data Mining: Practical Machine Learning Tools and Techniques","author":"I H Witten","year":"2016","unstructured":"Witten I H, Frank E, Hall M A, et al. Data Mining: Practical Machine Learning Tools and Techniques. San Fransisco: Morgan Kaufmann, 2016"},{"key":"2902_CR19","unstructured":"Staelin C. Parameter Selection for Support Vector Machines. Hewlett-Packard Company, Technical Report HPL-2002-354R1, 2003"},{"key":"2902_CR20","doi-asserted-by":"crossref","unstructured":"Palomba F, Di Nucci D, Tufano M, et al. Landfill: an open dataset of code smells with public evaluation. In: Proceedings of 2015 IEEE\/ACM 12th Working Conference on Mining Software Repositories, 2015. 482\u2013485","DOI":"10.1109\/MSR.2015.69"},{"key":"2902_CR21","doi-asserted-by":"crossref","unstructured":"Amorim L, Costa E, Antunes N, et al. Experience report: evaluating the effectiveness of decision trees for detecting code smells. In: Proceedings of IEEE 26th International Symposium on Software Reliability Engineering (ISSRE), 2015. 261\u2013269","DOI":"10.1109\/ISSRE.2015.7381819"},{"key":"2902_CR22","unstructured":"Reshi J A, Singh S. Predicting software defects through SVM: an empirical approach. 2018. ArXiv: 1803.03220"},{"key":"2902_CR23","doi-asserted-by":"crossref","unstructured":"Soltanifar B, Akbarinasaji S, Caglayan B, et al. Software analytics in practice: a defect prediction model using code smells. In: Proceedings of the 20th International Database Engineering & Applications Symposium, 2016. 148\u2013155","DOI":"10.1145\/2938503.2938553"},{"key":"2902_CR24","doi-asserted-by":"publisher","first-page":"20","DOI":"10.1109\/TSE.2009.50","volume":"36","author":"N Moha","year":"2010","unstructured":"Moha N, Gueheneuc Y G, Duchien L, et al. DECOR: a method for the specification and detection of code and design smells. IEEE Trans Softw Eng, 2010, 36: 20\u201336","journal-title":"IEEE Trans Softw Eng"},{"key":"2902_CR25","doi-asserted-by":"crossref","unstructured":"Fokaefs M, Tsantalis N, Chatzigeorgiou A. Jdeodorant: identification and removal of feature envy bad smells. In: Proceedings of 2007 IEEE International Conference on Software Maintenance, 2007. 519\u2013520","DOI":"10.1109\/ICSM.2007.4362679"},{"key":"2902_CR26","doi-asserted-by":"publisher","first-page":"50","DOI":"10.1007\/978-3-642-39742-4_6","volume-title":"Proceedings of International Symposium on Search Based Software Engineering","author":"M Boussaa","year":"2013","unstructured":"Boussaa M, Kessentini W, Kessentini M, et al. Competitive coevolutionary code-smells detection. In: Proceedings of International Symposium on Search Based Software Engineering. Berlin: Springer, 2013. 50\u201365"},{"key":"2902_CR27","doi-asserted-by":"publisher","first-page":"186","DOI":"10.1504\/IJBIC.2018.094624","volume":"12","author":"G Saranya","year":"2018","unstructured":"Saranya G, Nehemiah H K, Kannan A. Hybrid particle swarm optimisation with mutation for code smell detection. Int J Bio-Inspired Comput, 2018, 12: 186\u2013195","journal-title":"Int J Bio-Inspired Comput"},{"key":"2902_CR28","doi-asserted-by":"crossref","unstructured":"Kessentini M, Kessentini W, Sahraoui H, et al. Design defects detection and correction by example. In: Proceedings of IEEE 19th International Conference on Program Comprehension, 2011. 81\u201390","DOI":"10.1109\/ICPC.2011.22"},{"key":"2902_CR29","doi-asserted-by":"publisher","first-page":"559","DOI":"10.1016\/j.jss.2010.11.921","volume":"84","author":"F Khomh","year":"2011","unstructured":"Khomh F, Vaucher S, Gu\u00e9h\u00e9neuc Y G, et al. BDTEX: a GQM-based Bayesian approach for the detection of antipatterns. J Syst Softw, 2011, 84: 559\u2013572","journal-title":"J Syst Softw"},{"key":"2902_CR30","unstructured":"Dario D N, Fabio P, Damian A T, et al. Detecting code smells using machine learning techniques: Are we there yet? In: Proceedings of IEEE 25th International Conference on Software Analysis Evolution and Reengineering (SANER), 2018. 612\u2013621"},{"key":"2902_CR31","doi-asserted-by":"crossref","unstructured":"Maneerat N, Muenchaisri P. Bad-smell prediction from software design model using machine learning techniques. In: Proceedings of the 8th International Joint Conference on Computer Science and Software Engineering (JCSSE), 2011. 331\u2013336","DOI":"10.1109\/JCSSE.2011.5930143"},{"key":"2902_CR32","doi-asserted-by":"crossref","unstructured":"Hassaine S, Khomh F, Gu\u00e9h\u00e9neuc Y G, et al. IDS: an immune-inspired approach for the detection of software design smells. In: Proceedings of the 7th International Conference on the Quality of Information and Communications Technology, 2010. 343\u2013348","DOI":"10.1109\/QUATIC.2010.61"}],"container-title":["Science China Information Sciences"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11432-019-2902-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11432-019-2902-5\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11432-019-2902-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,4,19]],"date-time":"2022-04-19T20:30:02Z","timestamp":1650400202000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11432-019-2902-5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,2,7]]},"references-count":32,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2021,3]]}},"alternative-id":["2902"],"URL":"https:\/\/doi.org\/10.1007\/s11432-019-2902-5","relation":{},"ISSN":["1674-733X","1869-1919"],"issn-type":[{"value":"1674-733X","type":"print"},{"value":"1869-1919","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,2,7]]},"assertion":[{"value":"4 August 2019","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"19 November 2019","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"3 April 2020","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"7 February 2021","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}],"article-number":"132102"}}