Insights into testing and regression testing global variables
Journal of Software Maintenance: Research and Practice
A methodology for controlling the size of a test suite
ACM Transactions on Software Engineering and Methodology (TOSEM)
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
A Safe, Efficient Algorithm for Regression Test Selection
ICSM '93 Proceedings of the Conference on Software Maintenance
A Comparative Study of Five Regression Testing Algorithms
ASWEC '97 Proceedings of the Australian Software Engineering Conference
A search-based framework for automatic testing of MATLAB/Simulink models
Journal of Systems and Software
Empirical evaluations of regression test selection techniques: a systematic review
Proceedings of the Second ACM-IEEE international symposium on Empirical software engineering and measurement
Evolutionary software engineering, a review
Applied Soft Computing
A systematic review on regression test selection techniques
Information and Software Technology
| Hi-index | 0.00 |
The optimal regression testing problem is that of determining the minimum number of test cases needed for revalidating modified software in the maintenance phase. We present two natural optimization algorithms, namely simulated annealing and genetic algorithms, for solving this problem. The algorithms are based on an integer programming problem formulation and the program's control-flow graph. The main advantage of these algorithms is that they do not suffer from exponential explosion for realistic program sizes. The experimental results show that they find optimal or near-optimal number of retests in a reasonable time.