Comparing and experimenting machine learning techniques for code smell detection
Author:
Publisher
Springer Science and Business Media LLC
Subject
Software
Link
http://link.springer.com/content/pdf/10.1007/s10664-015-9378-4.pdf
Reference71 articles.
1. Aggarwal KK, Singh Y, Kaur A, Malhotra R (2006) Empirical study of object-oriented metrics. J Object Technol 5(8):149
2. Arcelli Fontana F, Braione P, Zanoni M (2012) Automatic detection of bad smells in code: an experimental assessment. J Object Technol 11(2), p. 5:1
3. Arcelli Fontana F, Ferme V, Marino A, Walter B, Martenka P (2013a) Investigating the impact of code smells on system’s quality: an empirical study on systems of different application domains. Proceedings of the 29th IEEE International Conference on Software Maintenance (ICSM 2013), 260–269
4. Arcelli Fontana F, Zanoni M, Marino A, Mantyla MV (2013b) Code smell detection: towards a machine learning-based approach. In: Fontana A (ed) Proceedings of the 29th IEEE International Conference on Software Maintenance (ICSM 2013), IEEE, Eindhoven, The Netherlands, 396–399. doi: 10.1109/ICSM.2013.56
5. Bansiya J, Davis CG (2002) A hierarchical model for object-oriented design quality assessment. IEEE Trans Softw Eng 28(1):4–17. doi: 10.1109/32.979986
Cited by 297 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Prescriptive procedure for manual code smell annotation;Science of Computer Programming;2024-12
2. Feature envy detection based on cross-graph local semantics matching;Information and Software Technology;2024-10
3. Data preparation for Deep Learning based Code Smell Detection: A systematic literature review;Journal of Systems and Software;2024-10
4. Improving and comparing performance of machine learning classifiers optimized by swarm intelligent algorithms for code smell detection;Science of Computer Programming;2024-10
5. Detecting refactoring type of software commit messages based on ensemble machine learning algorithms;Scientific Reports;2024-09-12
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3