Program evolution: processes of software change
Program evolution: processes of software change
Software Change Impact Analysis
Software Change Impact Analysis
Information Retrieval
Whole program Path-Based dynamic impact analysis
Proceedings of the 25th International Conference on Software Engineering
Supporting Impact Analysis and Change Propagation in Software Engineering Environments
STEP '97 Proceedings of the 8th International Workshop on Software Technology and Engineering Practice (STEP '97) (including CASE '97)
The Role of Concepts in Program Comprehension
IWPC '02 Proceedings of the 10th International Workshop on Program Comprehension
Leveraging field data for impact analysis and regression testing
Proceedings of the 9th European software engineering conference held jointly with 11th ACM SIGSOFT international symposium on Foundations of software engineering
Chianti: a tool for change impact analysis of java programs
OOPSLA '04 Proceedings of the 19th annual ACM SIGPLAN conference on Object-oriented programming, systems, languages, and applications
PASTE '07 Proceedings of the 7th ACM SIGPLAN-SIGSOFT workshop on Program analysis for software tools and engineering
Using information retrieval based coupling measures for impact analysis
Empirical Software Engineering
Change Impact Analysis Based on a Taxonomy of Change Types
COMPSAC '10 Proceedings of the 2010 IEEE 34th Annual Computer Software and Applications Conference
Blending Conceptual and Evolutionary Couplings to Support Change Impact Analysis in Source Code
WCRE '10 Proceedings of the 2010 17th Working Conference on Reverse Engineering
Using lattice of class and method dependence for change impact analysis of object oriented programs
Proceedings of the 2011 ACM Symposium on Applied Computing
Hi-index | 0.00 |
Software change impact analysis (CIA) is a key technique to identify the potential effects caused by software changes. In this paper, a new graph mining based CIA technique is proposed, which takes the interference among multiple proposed changes into account to improve the precision of the impact results. Empirical evaluations on two real-world software projects demonstrate the effectiveness of our CIA technique.