AGA: An Accelerated Greedy Additional Algorithm for Test Case Prioritization

In recent years, many test case prioritization (TCP) techniques have been proposed to speed up the process of fault detection. However, little work has taken efficiency problem these into account. this paper, we target Greedy Additional (GA) algorithm, which widely recognized be effective but less efficient, and try improve its while preserving effectiveness. our Accelerated GA (AGA) use some extra data structures reduce redundant accesses in algorithm thus time complexity is reduced from O(m2n) O(kmn) when n > m, where m number cases, program elements, k iteration number. Moreover, observe impact numbers on dataset propose a specific AGA further efficiency. We conducted experiments 55 open-source subjects. particular, implemented each TCP with two kinds widely-used input formats, adjacency matrix list. Since efficient than list, result analysis mainly based algorithms The results show that achieves 5.95X speedup ratio over average, it same average effectiveness as terms Average Percentage Fault Detected (APFD). an industrial study 22 subjects, collected Baidu, find 44.27X, indicates practical usage real-world scenarios.