{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,6]],"date-time":"2026-02-06T08:27:34Z","timestamp":1770366454010,"version":"3.49.0"},"reference-count":128,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:00:00Z","timestamp":1777593600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:00:00Z","timestamp":1777593600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:00:00Z","timestamp":1777593600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:00:00Z","timestamp":1777593600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:00:00Z","timestamp":1777593600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:00:00Z","timestamp":1777593600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:00:00Z","timestamp":1777593600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Journal of Systems and Software"],"published-print":{"date-parts":[[2026,5]]},"DOI":"10.1016\/j.jss.2026.112784","type":"journal-article","created":{"date-parts":[[2026,1,14]],"date-time":"2026-01-14T16:10:30Z","timestamp":1768407030000},"page":"112784","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["Systematic literature review on software code smell detection approaches"],"prefix":"10.1016","volume":"235","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6237-2270","authenticated-orcid":false,"given":"Praveen Singh","family":"Thakur","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0280-7364","authenticated-orcid":false,"given":"Satyendra Singh","family":"Chouhan","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2087-1666","authenticated-orcid":false,"given":"Santosh Singh","family":"Rathore","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8290-7903","authenticated-orcid":false,"given":"Jitendra","family":"Parmar","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"key":"10.1016\/j.jss.2026.112784_bib0001","series-title":"Proceedings of 21th Brazilian Conference on Software, Tools Session","first-page":"109","article-title":"Code smell detection tool for compositional-based software product lines","author":"Abilio","year":"2014"},{"key":"10.1016\/j.jss.2026.112784_bib0002","doi-asserted-by":"crossref","unstructured":"AbuHassan, A., Alshayeb, M., Ghouti, L., 2021. Software smell detection techniques: a systematic literature review.J. Softw. Evol. Process. 33 (3), e2320.","DOI":"10.1002\/smr.2320"},{"key":"10.1016\/j.jss.2026.112784_bib0003","doi-asserted-by":"crossref","first-page":"129536","DOI":"10.1109\/ACCESS.2023.3334258","article-title":"Research trends, detection methods, practices, and challenges in code smell: SLR","volume":"11","author":"Al Hilmi","year":"2023","journal-title":"IEEE Access"},{"issue":"4","key":"10.1016\/j.jss.2026.112784_bib0004","doi-asserted-by":"crossref","first-page":"2341","DOI":"10.1007\/s13369-019-04311-w","article-title":"Bad smell detection using machine learning techniques: a systematic literature review","volume":"45","author":"Al-Shaaby","year":"2020","journal-title":"Arabian J. Sci. Eng."},{"key":"10.1016\/j.jss.2026.112784_bib0005","doi-asserted-by":"crossref","DOI":"10.1016\/j.infsof.2021.106648","article-title":"Code smell detection using feature selection and stacking ensemble: an empirical investigation","volume":"138","author":"Alazba","year":"2021","journal-title":"Inf. Softw. Technol."},{"key":"10.1016\/j.jss.2026.112784_bib0006","series-title":"20th IEEE International Conference on Machine Learning and Applications (ICMLA)","first-page":"897","article-title":"Voting heterogeneous ensemble for code smell detection","author":"Aljamaan","year":"2021"},{"key":"10.1016\/j.jss.2026.112784_bib0007","series-title":"Proceedings of the 29th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering","first-page":"1560","article-title":"csdetector: an open source tool for community smells detection","author":"Almarimi","year":"2021"},{"key":"10.1016\/j.jss.2026.112784_bib0008","series-title":"5th International Conference on Computer and Communication Systems (ICCCS)","first-page":"172","article-title":"Code smell detection tool for java script programs","author":"Almashfi","year":"2020"},{"issue":"3","key":"10.1016\/j.jss.2026.112784_bib0009","doi-asserted-by":"crossref","first-page":"1143","DOI":"10.1007\/s10664-015-9378-4","article-title":"Comparing and experimenting machine learning techniques for code smell detection","volume":"21","author":"Arcelli Fontana","year":"2016","journal-title":"Empirical Softw. Eng."},{"key":"10.1016\/j.jss.2026.112784_bib0010","series-title":"IEEE\/ACM International Conference on Technical Debt (TechDebt)","first-page":"88","article-title":"Architectural smells detected by tools: a catalogue proposal","author":"Azadi","year":"2019"},{"key":"10.1016\/j.jss.2026.112784_bib0011","series-title":"IEEE International Conference on Software Maintenance and Evolution (ICSME)","first-page":"114","article-title":"Deep learning anti-patterns from code metrics history","author":"Barbez","year":"2019"},{"key":"10.1016\/j.jss.2026.112784_bib0012","doi-asserted-by":"crossref","DOI":"10.1016\/j.jss.2019.110486","article-title":"A machine-learning based ensemble method for anti-patterns detection","volume":"161","author":"Barbez","year":"2020","journal-title":"J. Syst. Softw."},{"key":"10.1016\/j.jss.2026.112784_bib0013","series-title":"Refactoring: Improving the design of existing code","first-page":"75","article-title":"Bad smells in code","volume":"1","author":"Beck","year":"1999"},{"key":"10.1016\/j.jss.2026.112784_bib0014","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2020.114076","article-title":"Code smell detection and identification in imbalanced environments","volume":"166","author":"Boutaib","year":"2021","journal-title":"Expert Syst. Appl."},{"key":"10.1016\/j.jss.2026.112784_bib0015","doi-asserted-by":"crossref","DOI":"10.1016\/j.asoc.2022.109620","article-title":"Uncertainty-wise software anti-patterns detection: a possibilistic evolutionary machine learning approach","volume":"129","author":"Boutaib","year":"2022","journal-title":"Appl. Soft Comput."},{"key":"10.1016\/j.jss.2026.112784_bib0016","series-title":"IEEE 21st International Conference on Software Quality, Reliability and Security (QRS)","first-page":"574","article-title":"A possibilistic evolutionary approach to handle the uncertainty of software metrics thresholds in code smells detection","author":"Boutaib","year":"2021"},{"issue":"6","key":"10.1016\/j.jss.2026.112784_bib0017","doi-asserted-by":"crossref","first-page":"124","DOI":"10.1007\/s10664-022-10142-5","article-title":"Handling uncertainty in SBSE: a possibilistic evolutionary approach for code smells detection","volume":"27","author":"Boutaib","year":"2022","journal-title":"Empirical Softw. Eng."},{"key":"10.1016\/j.jss.2026.112784_bib0018","series-title":"Proceedings of the 44th International Conference on Software Engineering","first-page":"1317","article-title":"Less is more: supporting developers in vulnerability detection during code review","author":"Braz","year":"2022"},{"issue":"02","key":"10.1016\/j.jss.2026.112784_bib0019","doi-asserted-by":"crossref","first-page":"285","DOI":"10.1142\/S021819401950013X","article-title":"Machine learning techniques for code smells detection: a systematic mapping study","volume":"29","author":"Caram","year":"2019","journal-title":"Int. J. Softw. Eng. Knowl. Eng."},{"key":"10.1016\/j.jss.2026.112784_bib0020","series-title":"40th EUROMICRO Conference on Software Engineering and Advanced Applications","first-page":"369","article-title":"Automated prioritization of metrics-based design flaws in UML class diagrams","author":"Chaudron","year":"2014"},{"key":"10.1016\/j.jss.2026.112784_bib0021","series-title":"7th International Conference on Dependable Systems and Their Applications (DSA)","first-page":"78","article-title":"Adaboost-based refused bequest code smell detection with synthetic instances","author":"Chen","year":"2020"},{"key":"10.1016\/j.jss.2026.112784_bib0022","doi-asserted-by":"crossref","first-page":"14","DOI":"10.1016\/j.infsof.2017.09.011","article-title":"Understanding metric-based detectable smells in python software: a comparative study","volume":"94","author":"Chen","year":"2018","journal-title":"Inf. Softw. Technol."},{"issue":"1","key":"10.1016\/j.jss.2026.112784_bib0023","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/2539117","article-title":"A survey of software aging and rejuvenation studies","volume":"10","author":"Cotroneo","year":"2014","journal-title":"J. Emerg. Technol. Comput. Syst."},{"key":"10.1016\/j.jss.2026.112784_bib0024","series-title":"Proceedings of the 5th International Workshop on Machine Learning Techniques for Software Quality Evolution","first-page":"1","article-title":"Comparing within-and cross-project machine learning algorithms for code smell detection","author":"De Stefano","year":"2021"},{"issue":"5","key":"10.1016\/j.jss.2026.112784_bib0025","doi-asserted-by":"crossref","first-page":"564","DOI":"10.1007\/s42979-023-01979-8","article-title":"Severity classification of code smells using machine-learning methods","volume":"4","author":"Dewangan","year":"2023","journal-title":"SN Comput. Sci."},{"key":"10.1016\/j.jss.2026.112784_bib0026","doi-asserted-by":"crossref","first-page":"162869","DOI":"10.1109\/ACCESS.2021.3133810","article-title":"A novel approach for code smell detection: an empirical study","volume":"9","author":"Dewangan","year":"2021","journal-title":"IEEE Access"},{"issue":"20","key":"10.1016\/j.jss.2026.112784_bib0027","doi-asserted-by":"crossref","DOI":"10.3390\/app122010321","article-title":"Code smell detection using ensemble machine learning algorithms","volume":"12","author":"Dewangan","year":"2022","journal-title":"Appl. Sci."},{"key":"10.1016\/j.jss.2026.112784_bib0028","series-title":"IEEE 25th International Conference on Software Analysis, Evolution and Reengineering (SANER)","first-page":"612","article-title":"Detecting code smells using machine learning techniques: are we there yet?","author":"Di Nucci","year":"2018"},{"issue":"2","key":"10.1016\/j.jss.2026.112784_bib0029","doi-asserted-by":"crossref","first-page":"1919","DOI":"10.32604\/cmc.2021.015586","article-title":"Code smell detection using whale optimization algorithm","volume":"68","author":"Draz","year":"2021","journal-title":"CMC-Comput. Mater. Continua"},{"key":"10.1016\/j.jss.2026.112784_bib0030","series-title":"Data Science: From Research to Application","first-page":"299","article-title":"Adversarial samples for improving performance of software defect prediction models","volume":"Vol. 45","author":"Eivazpour","year":"2020"},{"key":"10.1016\/j.jss.2026.112784_bib0031","series-title":"IEEE 13th International Working Conference on Source Code Analysis and Manipulation (SCAM)","first-page":"116","article-title":"Jsnose: detecting javascript code smells","author":"Fard","year":"2013"},{"key":"10.1016\/j.jss.2026.112784_bib0032","series-title":"Proceedings of the 20th International Conference on Evaluation and Assessment in Software Engineering","first-page":"1","article-title":"A review-based comparative study of bad smell detection tools","author":"Fernandes","year":"2016"},{"key":"10.1016\/j.jss.2026.112784_bib0033","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1016\/j.knosys.2017.04.014","article-title":"Code smell severity classification using machine learning techniques","volume":"128","author":"Fontana","year":"2017","journal-title":"Knowl. Based Syst."},{"key":"10.1016\/j.jss.2026.112784_bib0034","series-title":"2013 IEEE International Conference on Software Maintenance","first-page":"396","article-title":"Code smell detection: towards a machine learning-based approach","author":"Fontana","year":"2013"},{"issue":"2","key":"10.1016\/j.jss.2026.112784_bib0035","doi-asserted-by":"crossref","first-page":"34","DOI":"10.4018\/IJRSDA.2019040103","article-title":"Detection of shotgun surgery and message chain code smells using machine learning techniques","volume":"6","author":"Guggulothu","year":"2019","journal-title":"Int. J. Rough Sets Data Anal."},{"key":"10.1016\/j.jss.2026.112784_bib0036","doi-asserted-by":"crossref","first-page":"1063","DOI":"10.1007\/s11219-020-09498-y","article-title":"Code smell detection using multi-label classification approach","volume":"28","author":"Guggulothu","year":"2020","journal-title":"Softw. Qual. J."},{"key":"10.1016\/j.jss.2026.112784_bib0037","series-title":"Proceedings of the 13th International Conference on Evaluation of Novel Approaches to Software Engineering (ENASE)","first-page":"137","article-title":"A hybrid approach to detect code smells using deep learning","author":"Hadj-Kacem","year":"2018"},{"key":"10.1016\/j.jss.2026.112784_bib0038","series-title":"International Conference on Software Technologies (ICSOFT)","first-page":"198","article-title":"Towards a taxonomy of bad smells detection approaches","author":"Hadj-Kacem","year":"2018"},{"key":"10.1016\/j.jss.2026.112784_bib0039","series-title":"International Joint Conference on Neural Networks (IJCNN)","first-page":"1","article-title":"Deep representation learning for code smells detection using variational auto-encoder","author":"Hadj-Kacem","year":"2019"},{"issue":"14","key":"10.1016\/j.jss.2026.112784_bib0040","first-page":"2684","article-title":"Deep hybrid features for code smells detection","volume":"98","author":"Hamdy","year":"2020","journal-title":"J. Theor. Appl. Inf. Technol."},{"key":"10.1016\/j.jss.2026.112784_bib0041","series-title":"Proceedings of the 27th International Conference on Evaluation and Assessment in Software Engineering","first-page":"229","article-title":"Fusion of deep convolutional and LSTM recurrent neural networks for automated detection of code smells","author":"Ho","year":"2023"},{"key":"10.1016\/j.jss.2026.112784_bib0042","doi-asserted-by":"crossref","DOI":"10.1016\/j.scico.2022.102778","article-title":"Hbsniff: a static analysis tool for java hibernate object-relational mapping code smell detection","volume":"217","author":"Huang","year":"2022","journal-title":"Sci. Comput. Program."},{"issue":"3","key":"10.1016\/j.jss.2026.112784_bib0043","doi-asserted-by":"crossref","first-page":"367","DOI":"10.1016\/j.jksuci.2018.06.005","article-title":"Reducing redundancy of test cases generation using code smell detection and refactoring","volume":"32","author":"Ibrahim","year":"2020","journal-title":"J. King Saud Univ. Comput. Inf. Sci."},{"key":"10.1016\/j.jss.2026.112784_bib0044","doi-asserted-by":"crossref","DOI":"10.1016\/j.scico.2021.102713","article-title":"Improving performance with hybrid feature selection and ensemble machine learning techniques for code smell detection","volume":"212","author":"Jain","year":"2021","journal-title":"Sci. Comput. Program."},{"issue":"1","key":"10.1016\/j.jss.2026.112784_bib0045","doi-asserted-by":"crossref","first-page":"609","DOI":"10.1007\/s12065-020-00536-z","article-title":"Rank-based univariate feature selection methods on machine learning classifiers for code smell detection","volume":"15","author":"Jain","year":"2022","journal-title":"Evol. Intell."},{"key":"10.1016\/j.jss.2026.112784_bib0046","series-title":"International Conference on Machine Learning and Data Science (MLDS)","first-page":"9","article-title":"A support vector machine based approach for code smell detection","author":"Kaur","year":"2017"},{"key":"10.1016\/j.jss.2026.112784_bib0047","doi-asserted-by":"crossref","first-page":"8695","DOI":"10.1109\/ACCESS.2021.3049823","article-title":"A novel four-way approach designed with ensemble feature selection for code smell detection","volume":"9","author":"Kaur","year":"2021","journal-title":"IEEE Access"},{"issue":"3","key":"10.1016\/j.jss.2026.112784_bib0048","first-page":"1725","article-title":"Deep convolutional neural network model for bad code smells detection based on oversampling method","volume":"26","author":"Khleel","year":"2022","journal-title":"Indones. J. Electr. Eng. Comput. Sci."},{"issue":"1","key":"10.1016\/j.jss.2026.112784_bib0049","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1016\/j.infsof.2008.09.009","article-title":"Systematic literature reviews in software engineering\u2013a systematic literature review","volume":"51","author":"Kitchenham","year":"2009","journal-title":"Inf. Softw. Technol."},{"key":"10.1016\/j.jss.2026.112784_bib0050","series-title":"Evidence-Based Software Engineering and Systematic Reviews","author":"Kitchenham","year":"2015"},{"key":"10.1016\/j.jss.2026.112784_bib0051","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2022.117607","article-title":"Automatic detection of long method and god class code smells through neural source code embeddings","volume":"204","author":"Kova\u010devi\u0107","year":"2022","journal-title":"Expert Syst. Appl."},{"key":"10.1016\/j.jss.2026.112784_bib0052","series-title":"Proceedings of the IEEE\/ACM 42nd International Conference on Software Engineering Workshops","first-page":"315","article-title":"Recommendation of move method refactoring using path-based representation of code","author":"Kurbatova","year":"2020"},{"issue":"10","key":"10.1016\/j.jss.2026.112784_bib0053","doi-asserted-by":"crossref","first-page":"1902","DOI":"10.1002\/spe.3235","article-title":"On the relative value of imbalanced learning for code smell detection","volume":"53","author":"Li","year":"2023","journal-title":"Softw. Pract. Exper."},{"key":"10.1016\/j.jss.2026.112784_bib0054","series-title":"Proceedings International Symposium on Empirical Software Engineering","first-page":"91","article-title":"An approach for estimation of software aging in a web server","author":"Li","year":"2002"},{"issue":"7","key":"10.1016\/j.jss.2026.112784_bib0055","doi-asserted-by":"crossref","first-page":"1120","DOI":"10.1016\/j.jss.2006.10.018","article-title":"An empirical study of the bad smells and class error probability in the post-release object-oriented system evolution","volume":"80","author":"Li","year":"2007","journal-title":"J. Syst. Softw."},{"key":"10.1016\/j.jss.2026.112784_bib0056","series-title":"SEKE","first-page":"42","article-title":"Multi-label code smell detection with hybrid model based on deep learning","author":"Li","year":"2022"},{"key":"10.1016\/j.jss.2026.112784_bib0057","series-title":"Applied Cryptography in Computer and Communications: First EAI International Conference","first-page":"171","article-title":"A novel approach for code smells detection based on deep leaning","author":"Lin","year":"2021"},{"issue":"9","key":"10.1016\/j.jss.2026.112784_bib0058","first-page":"1811","article-title":"Deep learning based code smell detection","volume":"47","author":"Liu","year":"2019","journal-title":"IEEE Trans. Softw. Eng."},{"key":"10.1016\/j.jss.2026.112784_bib0059","series-title":"Proceedings of the 33rd ACM\/IEEE International Conference on Automated Software Engineering","first-page":"385","article-title":"Deep learning based feature envy detection","author":"Liu","year":"2018"},{"issue":"1","key":"10.1016\/j.jss.2026.112784_bib0060","doi-asserted-by":"crossref","first-page":"438","DOI":"10.1109\/TDSC.2020.2984505","article-title":"Cd-vuld: cross-domain vulnerability discovery based on deep domain adaptation","volume":"19","author":"Liu","year":"2020","journal-title":"IEEE Trans. Dependable Secure Comput."},{"key":"10.1016\/j.jss.2026.112784_bib0061","series-title":"Proceedings of 5th International Conference on Machinery, Materials and Computing Technology (ICMMCT)","first-page":"560","article-title":"The detection of code smell on software development: a mapping study","author":"Liu","year":"2017"},{"key":"10.1016\/j.jss.2026.112784_bib0062","series-title":"Proceedings of the International Conference on Geoinformatics and Data Analysis","first-page":"6","article-title":"Dt: an upgraded detection tool to automatically detect two kinds of code smell: duplicated code and feature envy","author":"Liu","year":"2018"},{"key":"10.1016\/j.jss.2026.112784_bib0063","doi-asserted-by":"crossref","DOI":"10.1016\/j.infsof.2022.107112","article-title":"Detecting code smells using industry-relevant data","volume":"155","author":"Madeyski","year":"2023","journal-title":"Inf. Softw. Technol."},{"key":"10.1016\/j.jss.2026.112784_bib0064","series-title":"International Conference on Infocom Technologies and Unmanned Systems (Trends and Future Directions)(ICTUS)","first-page":"400","article-title":"Vulnerability prediction through self-learning model","author":"Majumder","year":"2017"},{"key":"10.1016\/j.jss.2026.112784_bib0065","series-title":"International Conference on Software Maintenance, 2003. ICSM 2003. Proceedings.","first-page":"381","article-title":"A taxonomy and an initial empirical study of bad smells in code","author":"Mantyla","year":"2003"},{"key":"10.1016\/j.jss.2026.112784_bib0066","unstructured":"Martin fowlerMartin fowler, \u201ccode smell\u201d [online]. available:. https:\/\/martinfowler.com\/bliki\/CodeSmell.html. Accessed: 2024-07-28."},{"key":"10.1016\/j.jss.2026.112784_bib0067","series-title":"Proceedings of the Companion Publication of the 2014 ACM SIGPLAN Conference on Systems, Programming, and Applications: Software for Humanity","first-page":"25","article-title":"An approach to safely evolve program families in c","author":"Medeiros","year":"2014"},{"key":"10.1016\/j.jss.2026.112784_bib0068","doi-asserted-by":"crossref","first-page":"1428","DOI":"10.1007\/s11390-020-0323-7","article-title":"Predicting code smells and analysis of predictions: using machine learning techniques and software metrics","volume":"35","author":"Mhawish","year":"2020","journal-title":"J. Comput. Sci. Technol."},{"key":"10.1016\/j.jss.2026.112784_bib0069","series-title":"Proceedings of the 5th International Symposium on Software Visualization","first-page":"5","article-title":"An interactive ambient visualization for code smells","author":"Murphy-Hill","year":"2010"},{"key":"10.1016\/j.jss.2026.112784_bib0070","series-title":"Proceedings of the 17th International Conference on Mining Software Repositories","first-page":"327","article-title":"On the prevalence, impact, and evolution of sql code smells in data-intensive systems","author":"Muse","year":"2020"},{"key":"10.1016\/j.jss.2026.112784_bib0071","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2021.116217","article-title":"Empirical investigation of hyperparameter optimization for software defect count prediction","volume":"191","author":"Nevendra","year":"2022","journal-title":"Expert Syst. Appl."},{"key":"10.1016\/j.jss.2026.112784_bib0072","series-title":"Proceedings of the 11th International Symposium on Information and Communication Technology","first-page":"368","article-title":"ml-codesmell: a code smell prediction dataset for machine learning approaches","author":"Nguyen Thanh","year":"2022"},{"key":"10.1016\/j.jss.2026.112784_bib0073","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s40411-017-0041-1","article-title":"On the evaluation of code smells and detection tools","volume":"5","author":"Paiva","year":"2017","journal-title":"J. Softw. Eng. Res. Dev."},{"key":"10.1016\/j.jss.2026.112784_bib0074","series-title":"IEEE\/ACM 37th IEEE International Conference on Software Engineering","first-page":"769","article-title":"Textual analysis for code smell detection","author":"Palomba","year":"2015"},{"key":"10.1016\/j.jss.2026.112784_bib0075","series-title":"IEEE International Conference on Software Maintenance and Evolution","first-page":"101","article-title":"Do they really smell bad? A study on developers\u2019 perception of bad code smells","author":"Palomba","year":"2014"},{"key":"10.1016\/j.jss.2026.112784_bib0076","series-title":"28th IEEE\/ACM International Conference on Automated Software Engineering (ASE)","first-page":"268","article-title":"Detecting bad smells in source code using change history information","author":"Palomba","year":"2013"},{"issue":"5","key":"10.1016\/j.jss.2026.112784_bib0077","doi-asserted-by":"crossref","first-page":"462","DOI":"10.1109\/TSE.2014.2372760","article-title":"Mining version histories for detecting code smells","volume":"41","author":"Palomba","year":"2014","journal-title":"IEEE Trans. Softw. Eng."},{"key":"10.1016\/j.jss.2026.112784_bib0078","series-title":"IEEE Workshop on Machine Learning Techniques for Software Quality Evaluation (MaLTeSQuE)","first-page":"8","article-title":"Investigating code smell co-occurrences using association rule learning: a replicated study","author":"Palomba","year":"2017"},{"key":"10.1016\/j.jss.2026.112784_bib0079","series-title":"IEEE 24th International Conference on Program Comprehension (ICPC)","first-page":"1","article-title":"A textual-based technique for smell detection","author":"Palomba","year":"2016"},{"issue":"1","key":"10.1016\/j.jss.2026.112784_bib0080","doi-asserted-by":"crossref","first-page":"108","DOI":"10.1109\/TSE.2018.2883603","article-title":"Beyond technical aspects: how do community smells influence the intensity of code smells?","volume":"47","author":"Palomba","year":"2018","journal-title":"IEEE Trans. Softw. Eng."},{"key":"10.1016\/j.jss.2026.112784_bib0081","series-title":"Proceedings of the 40th International Conference on Software Engineering: Companion Proceeedings","first-page":"240","article-title":"How do community smells influence code smells?","author":"Palomba","year":"2018"},{"key":"10.1016\/j.jss.2026.112784_bib0082","series-title":"IEEE International Conference on Software Maintenance and Evolution (ICSME)","first-page":"244","article-title":"Smells like teen spirit: improving bug prediction performance using the intensity of code smells","author":"Palomba","year":"2016"},{"issue":"2","key":"10.1016\/j.jss.2026.112784_bib0083","doi-asserted-by":"crossref","first-page":"194","DOI":"10.1109\/TSE.2017.2770122","article-title":"Toward a smell-aware bug prediction model","volume":"45","author":"Palomba","year":"2017","journal-title":"IEEE Trans. Softw. Eng."},{"key":"10.1016\/j.jss.2026.112784_bib0084","series-title":"Proceedings of the 3rd ACM SIGSOFT International Workshop on Machine Learning Techniques for Software Quality Evaluation","first-page":"19","article-title":"On the role of data balancing for machine learning-based code smell detection","author":"Pecorelli","year":"2019"},{"issue":"3","key":"10.1016\/j.jss.2026.112784_bib0085","doi-asserted-by":"crossref","first-page":"64","DOI":"10.1007\/s10664-022-10126-5","article-title":"On the adequacy of static analysis warnings with respect to code smell prediction","volume":"27","author":"Pecorelli","year":"2022","journal-title":"Empirical Softw. Eng."},{"key":"10.1016\/j.jss.2026.112784_bib0086","series-title":"IEEE\/ACM 27th International Conference on Program Comprehension (ICPC)","first-page":"93","article-title":"Comparing heuristic and machine learning approaches for metric-based code smell detection","author":"Pecorelli","year":"2019"},{"key":"10.1016\/j.jss.2026.112784_bib0087","series-title":"Proceedings of the 17th International Conference on Mining Software Repositories","first-page":"220","article-title":"Developer-driven code smell prioritization","author":"Pecorelli","year":"2020"},{"key":"10.1016\/j.jss.2026.112784_bib0088","series-title":"IEEE International Symposium on Software Reliability Engineering Workshops (ISSREW)","first-page":"123","article-title":"Techniques and tools for advanced software vulnerability detection","author":"Pereira","year":"2020"},{"key":"10.1016\/j.jss.2026.112784_bib0089","series-title":"IEEE 37th International Performance Computing and Communications Conference (IPCCC)","first-page":"1","article-title":"Software rejuvenation in computer systems: an automatic forecasting approach based on time series","author":"Pereira","year":"2018"},{"issue":"4","key":"10.1016\/j.jss.2026.112784_bib0090","doi-asserted-by":"crossref","first-page":"765","DOI":"10.1109\/TSE.2024.3363223","article-title":"DynAMICS: a tool-based method for the specification and dynamic detection of android behavioural code smells","volume":"50","author":"Prestat","year":"2024","journal-title":"IEEE Trans. Softw. Eng."},{"key":"10.1016\/j.jss.2026.112784_bib0091","series-title":"44th International Convention on Information, Communication and Electronic Technology (MIPRO)","first-page":"1601","article-title":"Clean code and design educational tool","author":"Proki\u0107","year":"2021"},{"key":"10.1016\/j.jss.2026.112784_bib0092","series-title":"IEEE International Symposium on Software Reliability Engineering Workshops (ISSREW)","first-page":"271","article-title":"An empirical study on software aging indicators prediction in android mobile","author":"Qiao","year":"2018"},{"key":"10.1016\/j.jss.2026.112784_bib0093","series-title":"Technical Report","article-title":"On Transfer Learning in Code Smells Detection","author":"Ramos","year":"2022"},{"issue":"1","key":"10.1016\/j.jss.2026.112784_bib0094","doi-asserted-by":"crossref","DOI":"10.1038\/s41598-023-43380-8","article-title":"A study of dealing class imbalance problem with machine learning methods for code smell severity detection using PCA-based feature selection technique","volume":"13","author":"Rao","year":"2023","journal-title":"Sci. Rep."},{"key":"10.1016\/j.jss.2026.112784_bib0095","doi-asserted-by":"crossref","first-page":"3289","DOI":"10.1007\/s13369-020-04365-1","article-title":"Recovering android bad smells from android applications","volume":"45","author":"Rasool","year":"2020","journal-title":"Arabian J. Sci. Eng."},{"issue":"2","key":"10.1016\/j.jss.2026.112784_bib0096","doi-asserted-by":"crossref","first-page":"255","DOI":"10.1007\/s10462-017-9563-5","article-title":"A study on software fault prediction techniques","volume":"51","author":"Rathore","year":"2019","journal-title":"Artif. Intell. Rev."},{"issue":"5","key":"10.1016\/j.jss.2026.112784_bib0097","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s10664-025-10676-4","article-title":"When code smells meet ML: on the lifecycle of ML-specific code smells in ML-enabled systems","volume":"30","author":"Recupito","year":"2025","journal-title":"Empirical Softw. Eng."},{"key":"10.1016\/j.jss.2026.112784_bib0098","unstructured":"Reis, J. P. d., de Figueiredo, C. G., Anslow, C., et al., 2020. Code smells detection and visualization: a systematic literature review. arxiv: 2012.08842."},{"key":"10.1016\/j.jss.2026.112784_bib0099","series-title":"IEEE 45th Annual Computers, Software, and Applications Conference (COMPSAC)","first-page":"864","article-title":"Exploiting multi-aspect interactions for god class detection with dataset fine-tuning","author":"Ren","year":"2021"},{"key":"10.1016\/j.jss.2026.112784_bib0100","series-title":"Object-Oriented Design Heuristics","author":"Riel","year":"1996"},{"key":"10.1016\/j.jss.2026.112784_bib0101","series-title":"IEEE\/ACM 6th International Conference on Mobile Software Engineering and Systems (MOBILESoft)","first-page":"123","article-title":"Sniffing android code smells: an association rules mining-based approach","author":"Rubin","year":"2019"},{"key":"10.1016\/j.jss.2026.112784_bib0102","series-title":"International Conference on Advancements in Computing (ICAC)","first-page":"186","article-title":"Code vulnerability identification and code improvement using advanced machine learning","author":"Ruggahakotuwa","year":"2019"},{"issue":"1","key":"10.1016\/j.jss.2026.112784_bib0103","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/2675067","article-title":"Code-smell detection as a bilevel problem","volume":"24","author":"Sahin","year":"2014","journal-title":"ACM Trans. Softw. Eng. Methodol."},{"key":"10.1016\/j.jss.2026.112784_bib0104","doi-asserted-by":"crossref","DOI":"10.7717\/peerj-cs.1370","article-title":"Python code smells detection using conventional machine learning models","volume":"9","author":"Sandouka","year":"2023","journal-title":"PeerJ Comput. Sci."},{"key":"10.1016\/j.jss.2026.112784_bib0105","series-title":"Anais Do XIX Encontro Nacional De Intelig\u00eancia Artificial E Computacional","first-page":"13","article-title":"Random forest for code smell detection in javascript","author":"Sarafim","year":"2022"},{"key":"10.1016\/j.jss.2026.112784_bib0106","doi-asserted-by":"crossref","DOI":"10.1016\/j.jss.2021.110936","article-title":"Code smell detection by deep direct-learning and transfer-learning","volume":"176","author":"Sharma","year":"2021","journal-title":"J. Syst. Softw."},{"key":"10.1016\/j.jss.2026.112784_bib0107","doi-asserted-by":"crossref","unstructured":"Sharma, T., Efstathiou, V., Louridas, P., Spinellis, D. D., 2021. Code smell detection by deep direct-learning and transfer-learning. Journal of Systems and Software, 176, 110936.https:\/\/doi.org\/10.1016\/j.jss.2021.110936.","DOI":"10.1016\/j.jss.2021.110936"},{"key":"10.1016\/j.jss.2026.112784_bib0108","doi-asserted-by":"crossref","first-page":"158","DOI":"10.1016\/j.jss.2017.12.034","article-title":"A survey on software smells","volume":"138","author":"Sharma","year":"2018","journal-title":"J. Syst. Softw."},{"key":"10.1016\/j.jss.2026.112784_bib0109","series-title":"27th Asia-Pacific Software Engineering Conference (APSEC)","first-page":"276","article-title":"Improving machine learning-based code smell detection via hyper-parameter optimization","author":"Shen","year":"2020"},{"key":"10.1016\/j.jss.2026.112784_bib0110","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2023.122855","article-title":"Automatic detection of feature envy and data class code smells using machine learning","volume":"243","author":"\u0160kipina","year":"2024","journal-title":"Expert Syst. Appl."},{"issue":"12","key":"10.1016\/j.jss.2026.112784_bib0111","doi-asserted-by":"crossref","first-page":"1253","DOI":"10.1109\/TSE.2018.2836442","article-title":"A comprehensive investigation of the role of imbalanced learning for software defect prediction","volume":"45","author":"Song","year":"2018","journal-title":"IEEE Trans. Softw. Eng."},{"key":"10.1016\/j.jss.2026.112784_bib0112","series-title":"IEEE 15th International Working Conference on Source Code Analysis and Manipulation (SCAM)","first-page":"253","article-title":"FaultBuster: an automatic code smell refactoring toolset","author":"Sz\u0151ke","year":"2015"},{"issue":"1","key":"10.1016\/j.jss.2026.112784_bib0113","first-page":"41","article-title":"Code sniffer: a risk based smell detection framework to enhance code quality using static code analysis","volume":"2","author":"Tahmid","year":"2017","journal-title":"Int. J. Softw. Eng. Technol. Appl."},{"issue":"7","key":"10.1016\/j.jss.2026.112784_bib0114","doi-asserted-by":"crossref","first-page":"683","DOI":"10.1109\/TSE.2018.2794977","article-title":"The impact of automated parameter optimization on defect prediction models","volume":"45","author":"Tantithamthavorn","year":"2019","journal-title":"IEEE Trans. Softw. Eng."},{"key":"10.1016\/j.jss.2026.112784_bib0115","series-title":"Proceedings of the 4th ACM SIGSOFT International Workshop on Software Analytics","first-page":"19-25","article-title":"Is one hyperparameter optimizer enough?","author":"Tu","year":"2018"},{"key":"10.1016\/j.jss.2026.112784_bib0116","series-title":"26th International Computer Science and Engineering Conference (ICSEC)","first-page":"128","article-title":"Python code smell detection using machine learning","author":"Vatanapakorn","year":"2022"},{"key":"10.1016\/j.jss.2026.112784_bib0117","first-page":"1","article-title":"Jspirit: a flexible tool for the analysis of code smells","author":"Vidal","year":"2015","journal-title":"34th International Conference of the Chilean Computer Science Society (SCCC)"},{"issue":"10","key":"10.1016\/j.jss.2026.112784_bib0118","doi-asserted-by":"crossref","first-page":"12898","DOI":"10.1007\/s11227-022-04389-4","article-title":"Docker platform aging: a systematic performance evaluation and prediction of resource consumption","volume":"78","author":"Vin\u00edcius","year":"2022","journal-title":"J. Supercomput."},{"key":"10.1016\/j.jss.2026.112784_bib0119","series-title":"IEEE Intl Conf on Parallel & Distributed Processing with Applications, Big Data & Cloud Computing, Sustainable Computing & Communications, Social Computing & Networking (ISPA\/BDCloud\/SocialCom\/SustainCom)","first-page":"448","article-title":"Feature envy detection based on bi-LSTM with self-attention mechanism","author":"Wang","year":"2020"},{"key":"10.1016\/j.jss.2026.112784_bib0120","series-title":"Proceedings of the 33rd International Conference on Software Engineering and Knowledge Engineering (SEKE)","first-page":"503","article-title":"Multi-granularity code smell detection using deep learning method based on abstract syntax tree","volume":"Vol. 7","author":"Xu","year":"2021"},{"issue":"1","key":"10.1016\/j.jss.2026.112784_bib0121","doi-asserted-by":"crossref","first-page":"6","DOI":"10.26634\/jse.17.1.19106","article-title":"Feature reduction techniques based code smell prediction","volume":"17","author":"Yadav","year":"2022","journal-title":"i-Manager\u2019s J. Softw. Eng."},{"issue":"14","key":"10.1016\/j.jss.2026.112784_bib0122","doi-asserted-by":"crossref","first-page":"6149","DOI":"10.3390\/app14146149","article-title":"Machine learning-based methods for code smell detection: a survey","volume":"14","author":"Yadav","year":"2024","journal-title":"Appl. Sci."},{"issue":"10","key":"10.1016\/j.jss.2026.112784_bib0123","doi-asserted-by":"crossref","first-page":"2639","DOI":"10.1016\/j.jss.2013.05.007","article-title":"Code smells as system-level indicators of maintainability: an empirical study","volume":"86","author":"Yamashita","year":"2013","journal-title":"J. Syst. Softw."},{"key":"10.1016\/j.jss.2026.112784_bib0124","series-title":"Proceedings of the 19th International Conference on Mining Software Repositories","first-page":"156","article-title":"How to improve deep learning for software analytics: (a case study with code smell detection)","author":"Yedida","year":"2022"},{"issue":"1","key":"10.1016\/j.jss.2026.112784_bib0125","doi-asserted-by":"crossref","DOI":"10.1002\/smr.2403","article-title":"Mars: detecting brain class\/method code smell based on metric\u2013attention mechanism and residual network","volume":"36","author":"Zhang","year":"2024","journal-title":"J. Softw. Evol. Process"},{"key":"10.1016\/j.jss.2026.112784_bib0126","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2022.109737","article-title":"Delesmell: code smell detection based on deep learning and latent semantic analysis","volume":"255","author":"Zhang","year":"2022","journal-title":"Knowl. Based Syst."},{"key":"10.1016\/j.jss.2026.112784_bib0127","series-title":"Proceedings of the 2nd International Conference on Algorithms, Computing and Artificial Intelligence","first-page":"160","article-title":"Recurrent neural network based binary code vulnerability detection","author":"Zheng","year":"2019"},{"issue":"11","key":"10.1016\/j.jss.2026.112784_bib0128","doi-asserted-by":"crossref","first-page":"2296","DOI":"10.1002\/spe.3257","article-title":"Security-based code smell definition, detection, and impact quantification in android","volume":"53","author":"Zhong","year":"2023","journal-title":"Softw. Pract. Exper."}],"container-title":["Journal of Systems and Software"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S016412122600018X?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S016412122600018X?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,2,5]],"date-time":"2026-02-05T17:49:02Z","timestamp":1770313742000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S016412122600018X"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,5]]},"references-count":128,"alternative-id":["S016412122600018X"],"URL":"https:\/\/doi.org\/10.1016\/j.jss.2026.112784","relation":{},"ISSN":["0164-1212"],"issn-type":[{"value":"0164-1212","type":"print"}],"subject":[],"published":{"date-parts":[[2026,5]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Systematic literature review on software code smell detection approaches","name":"articletitle","label":"Article Title"},{"value":"Journal of Systems and Software","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.jss.2026.112784","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"112784"}}