Key points are not available for this paper at this time.
Techniques for test-case prioritization re-order test cases to increase their rate of fault detection. When there is a fixed time budget that does not allow the execution of all the test cases, time-aware techniques for test-case prioritization may achieve a better rate of fault detection than traditional techniques for test-case prioritization. In this paper, we propose a novel approach to time-aware test-case prioritization using integer linear programming. To evaluate our approach, we performed experiments on two subject programs involving four techniques for our approach, two techniques for an approach to time-aware test-case prioritization based on genetic algorithms, and four traditional techniques for test-case prioritization. The empirical results indicate that two of our techniques outperform all the other techniques for the two subjects under the scenarios of both general and version-specific prioritization. The empirical results also indicate that some traditional techniques with lower analysis time cost for test-case prioritization may still perform competitively when the time budget is not quite tight.
Zhang et al. (Sun,) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: