Software Change Management: a Quantified Perspective
Keywords:Change Impact Analysis, Software Metrics.
A systematic Change Impact Analysis (CIA) is being used for better change management of software. Also, CIA process is evolved continuously to make it more effective. Software metrics play an important role to evaluate CIA process. Two types of metrics are used to evaluate CIA. First types of metrics are the standard metrics used to evaluate the performance of CIA techniques for example Precision, Recall, F-measure etc. These are most commonly used by researchers. Second types of metrics are those which are used to quantify the change impact which is based on the code/design features. This paper is aimed at identification of these second types of metrics available in literature.
 Bohner SA. Software change impactsâ€”an evolving perspective. Proceedings of the International Conference on Software Maintenance, MontrÃ©al, Canada, 2002; 263â€“272.
 De-Lucia A, Fasano F, Oliveto R. Traceability management for impact analysis. Proceedings of the International Conference on Software Maintainence, Beijing, China, 2008; 21â€“30.
 M. Kilpinen. The Emergence of Change at the Systems Engineering and Software Design Interface - An Investigation of Impact Analysis. PhD thesis, Cambridge University, Engineering Department, 2008.
 Badri L, Badri M, Yves SD. Supporting predictive change impact analysis: a control call graph based technique. Proceedings of the Asia-Pacific Software Engineering Conference, Taipei, Taiwan, China, 2005; 167â€“175.
 Mund GB, Mall R. An efficient interprocedural dynamic slicing method. Journal of Systems and Software 2006; 79(6):791 806.
 Hewitt J, Rilling J. A light-weight proactive software change impact analysis using use case maps. Proceedings of the International Workshop on Software Evolvability, Budapest, Hungary, 2005; 41â€“46.
 Huang LL, Song YT. Precise dynamic impact analysis with dependency analysis for object-oriented programs. Proceedings of the International Conference on Advanced Software Engineering and Its Applications, Hainan Island, China, 2008; 217â€“220.
 Apiwattanapong T, Orso A, Harrold MJ. Efficient and precise dynamic impact analysis using execute-after sequences. Proceedings of the International Conference on Software Engineering, St. Louis, Missouri, USA, 2005; 432â€“441.
 W. Frakes and C. Terry. Software reuse: Metrics and models. ACM Computing Surveys, 28(2):415â€“435, 1996.
 Pfleeger SL, Bohner SA. A Framework for software maintenance metrics. Proceedings of the International Conference on Software Maintenance, Washington, DC, 1990; 320â€“327.
 Zhang, S., Shen, H., and Zhao, J. 2008. Metrics for Measuring Change Impacts in AspectJ Software Maintenance and Reuse. Technical Report. Center for Software Engineering, SJTU.
 W.E. Wong, S.S. Gokhale, "Static and Dynamic Distance Metrics for Feature-Based Code Analysis", J. Systems and Software, vol. 74, no. 3, pp. 283-295, 2005.
 B. Isong, O. Ifeoma and M. Mbodila, "Supplementing Object-Oriented software change impact analysis with fault-proneness prediction", 15th International Conference on Computer and Information Science (ICIS' 16), IEEE Computer Society, pp. 1--8, Okayama, Japan, 26-29 June 2016.
 Hamzeh Eyal Salman, Abdelhak-Djamel Seriai, and Christophe Dony, Int. J. Soft. Eng. Knowl. Eng. 25, 69 (2015).
 Gustavo Ansaldi Oliva, Marco AurÃ©lio Gerosa, Fabio Kon, Virginia Smith and Dejan Milojicic, â€œA Static Change Impact Analysis Approach based on Metrics and Visualizations to Support the Evolution of Workflow Repositoriesâ€, International Journal of Web Services Research Volume 13 â€¢ Issue 2 â€¢ April-June 2016, pp 74-103.
 Jihen MaÃ¢zoun, Nadia Bouassida, and HanÃªne Ben-Abdallah. Change impact analysis for software product lines. J. King Saud Univ. Comput. Inf. Sci., 28:364â€“ 380, Oct 2016.
 Chen Zhifei, Chen Lin, Ma Wanwangying, Zhou Xiaoyu, Zhou Yuming, Xu Baowen, â€œUnderstanding metric-based detectable smells in Python software: A comparative study, Information and Software Technology 94 (2018) pp 14â€“29
 Garvit Rajesh Choudhary, Sandeep Kumar, Kuldeep Kumar, Alok Mishra, Cagatay Catal, â€œEmpirical analysis of change metrics for software fault predictionâ€, Computers and Electrical Engineering 67 (2018) pp 15â€“24.
 Lov Kumar, Santanu Kumar rath, Ashish Sureka, â€œEmpirical Analysis on Effectiveness of Source Code Metrics for Predicting Change-Pronenessâ€, ISEC â€™17, February 05-07, 2017, Jaipur, India.
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