Interprocedural slicing using dependence graphs
ACM Transactions on Programming Languages and Systems (TOPLAS)
How well do experienced software developers predict software change?
Journal of Systems and Software
A comparative study of coarse- and fine-grained safe regression test-selection techniques
ACM Transactions on Software Engineering and Methodology (TOSEM)
Software Change Impact Analysis
Software Change Impact Analysis
Preliminary guidelines for empirical research in software engineering
IEEE Transactions on Software Engineering
Impact analysis in the software change process: a year 2000 perspective
ICSM '96 Proceedings of the 1996 International Conference on Software Maintenance
Impact Analysis - Towards a Framework for Comparison
ICSM '93 Proceedings of the Conference on Software Maintenance
An Empirical Comparison of Dynamic Impact Analysis Algorithms
Proceedings of the 26th International Conference on Software Engineering
Incremental Change in Object-Oriented Programming
IEEE Software
Predicting Change Propagation in Software Systems
ICSM '04 Proceedings of the 20th IEEE International Conference on Software Maintenance
A Comparison of Online and Dynamic Impact Analysis Algorithms
CSMR '05 Proceedings of the Ninth European Conference on Software Maintenance and Reengineering
JRipples: A Tool for Program Comprehension during Incremental Change
IWPC '05 Proceedings of the 13th International Workshop on Program Comprehension
Mining Version Histories to Guide Software Changes
IEEE Transactions on Software Engineering
Detecting groups of co-changing files in CVS repositories
IWPSE '05 Proceedings of the Eighth International Workshop on Principles of Software Evolution
Constructing the Call Graph of a Program
IEEE Transactions on Software Engineering
Towards a Benchmark for Evaluating Reverse Engineering Tools
WCRE '08 Proceedings of the 2008 15th Working Conference on Reverse Engineering
Towards a Benchmark for Evaluating Design Pattern Miner Tools
CSMR '08 Proceedings of the 2008 12th European Conference on Software Maintenance and Reengineering
Change impact graphs: Determining the impact of prior codechanges
Information and Software Technology
A taxonomy for software change impact analysis
Proceedings of the 12th International Workshop on Principles of Software Evolution and the 7th annual ERCIM Workshop on Software Evolution
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In change impact analysis, obtaining guidance from automatic tools would be highly desirable since this activity is generally seen as a very difficult program comprehension problem. However, since the notion of an 'impact set' (or dependency set) of a specific change is usually very inexact and context dependent, the approaches and algorithms for computing these sets are also very diverse producing quite different results. The question 'which algorithm finds program dependencies in the most efficient way?' has been preoccupying researchers for a long time, but there are still very few results published on the comparison of the different algorithms to what programmers think are real dependencies. In this work, we report on our experiment conducted with this goal in mind using a compact, easily comprehensible Java experimental software system, simulated program changes, and a group of programmers who were asked to perform impact analysis with the help of different tools and on the basis of their programming experience. We show which algorithms turned out to be the closest to the programmers' opinion in this case study. However, the results also certified that most existing algorithms need to be further enhanced and an effective methodology to use automated tools to support impact analysis still needs to be found.