Thomas Zimmermann
Sunghun Kim
Andreas Zeller
ABSTRACT
Files, classes, or methods have frequently been investigated in recent research on co-change. In this paper, we present a first study at the level of lines. To identify line changes across several versions, we define the annotation graph which captures how lines evolve over time. The annotation graph provides more fine-grained software evolution information such as life cycles of each line and related changes: "Whenever a developer changed line 1 of version.txt she also changed line 25 of Library.java."
- R. Agrawal and R. Srikant. Fast algorithms for mining association rules in large databases. In J. B. Bocca, M. Jarke, and C. Zaniolo, editors, Proceedings of 20th International Conference on Very Large Data Bases (VLDB 1994), pages 487--499. Morgan Kaufmann, September 1994. Google Scholar
Digital Library
- J. Bevan and E. J. Whitehead Jr. Identification of software instabilities. In Proceedings of the 10th Working Conference on Reverse Engineering (WCRE 2003), pages 134--145, Victoria, Canada, 2003. IEEE Computer Society. Google ScholarDigital Library
- D. Beyer and A. Noack. Clustering software artifacts based on frequent common changes. In Proceedings of the 13th IEEE International Workshop on Program Comprehension (IWPC 2005), pages 259--268. IEEE Computer Society Press, Los Alamitos (CA), 2005. Google ScholarDigital Library
- M. Burch, S. Diehl, and P. Weißgerber. Visual data mining in software archives. In Proceedings of the 2005 ACM symposium on Software visualization (SoftVis 2005), pages 37--46, New York, NY, USA, 2005. ACM Press. Google ScholarDigital Library
- A. Chen, E. Chou, J. Wong, A. Y. Yao, Q. Zhang, S. Zhang, and A. Michail. CVSSearch: Searching through source code using CVS comments. In Proceedings of the IEEE International Conference on Software Maintenance (ICSM 2001), pages 364--373, Florence, Italy, 2001. IEEE Computer Society. Google ScholarDigital Library
- M. D'Ambros, M. Lanza, and H. Gall. Fractal figures: Visualizing development effort for cvs entities. In Proceedings of the International Workshop on Visualizing Software for Understanding and Analysis (VISSOFT), pages 46--51. IEEE Computer Society, Sept. 2005. Google ScholarDigital Library
- H. Gall, K. Hajek, and M. Jazayeri. Detection of logical coupling based on product release history. In Proceedings of the International Conference on Software Maintenance (ICSM 1998), pages 190--197, Bethesda, Maryland, USA, 1998. IEEE Computer Society. Google ScholarDigital Library
- H. Gall, M. Jazayeri, and J. Krajewski. Cvs release history data for detecting logical couplings. In Proceedings of the 6th International Workshop on Principles of Software Evolution (IWPSE 2003), pages 13--23, Helsinki, Finland, 2003. IEEE Computer Society. Google ScholarDigital Library
- M. W. Godfrey and L. Zou. Using origin analysis to detect merging and splitting of source code entities. IEEE Transactions on Software Engineering, 31(2):166--181, 2005. Google ScholarDigital Library
- S. Kim, K. Pan, and E. J. Whitehead Jr. When functions change their names: Automatic detection of origin relationships. In Proceedings of the 12th Working Conference on Reverse Engineering (WCRE 2005), pages 143--152, Pittsburgh, Pennsylvania, USA, 2005. IEEE Computer Society. Google ScholarDigital Library
- R. Purushothaman and D. E. Perry. Toward understanding the rhetoric of small source code changes. IEEE Transactions on Software Engineering, 31(6):511--526, 2005. Google ScholarDigital Library
- J. Śliwerski, T. Zimmermann, and A. Zeller. When do changes induce fixes? In Proceedings of the 2005 International Workshop on Mining Software Repositories (MSR 2005), St. Louis, Missouri, USA, 2005. ACM Press. Google ScholarDigital Library
- A. T. T. Ying, G. C. Murphy, R. T. Ng, and M. Chu-Carroll. Predicting source code changes by mining change history. IEEE Transactions on Software Engineering, 30(9):574--586, 2004. Google ScholarDigital Library
- T. Zimmermann, S. Diehl, and A. Zeller. How history justifies system architecture (or not). In IWPSE '03: Proceedings of the 6th International Workshop on Principles of Software Evolution, pages 73--84, Helsinki, Finland, 2003. IEEE Computer Society. Google ScholarDigital Library
- T. Zimmermann, S. Kim, A. Zeller, and E. J. Whitehead Jr. Mining version archives for co-changed lines. Technical report, Saarland University, Saarbrücken, Germany, March 2006. Available at urlhttp://www.st.cs.uni-sb.de/softevo/.Google Scholar
- T. Zimmermann, P. Weißgerber, S. Diehl, and A. Zeller. Mining version histories to guide software changes. IEEE Transactions on Software Engineering, 31(6):429--445, 2005. Google ScholarDigital Library
Index Terms
- Mining version archives for co-changed lines
Recommendations
Identifying Changed Source Code Lines from Version Repositories
MSR '07: Proceedings of the Fourth International Workshop on Mining Software RepositoriesObserving the evolution of software systems at different levels of granularity has been a key issue for a number of studies, aiming at predicting defects or at studying certain phenomena, such as the presence of clones or of crosscutting concerns. ...
Interpretation of Lines in Distributing Frame Drawings
ICDAR '97: Proceedings of the 4th International Conference on Document Analysis and RecognitionThis paper describes a method for interpretation of lines in distributing frame drawings of a telephone company. The lines are composed of hierarchical components: intersections, segments and line links. First, intersections are located. Segments of ...
Finding straight lines in drawings
ICDAR '97: Proceedings of the 4th International Conference on Document Analysis and RecognitionWe have developed an efficient method to extract straight lines at any orientation from a line drawing. The method works by extracting the horizontal and vertical lines using the FAST method, detecting the angles of the other lines and applying the FAST ...
Comments