An Empirical Comparison of Similarity Measures for Abstract Test Case Prioritization

2017 ◽  
Author(s):  
Rubing Huang ◽  
Yunan Zhou ◽  
Weiwen Zong ◽  
Dave Towey ◽  
Jinfu Chen
Keyword(s):  
Similarity Measures ◽  
Test Case ◽  
Test Case Prioritization ◽  
Empirical Comparison ◽  
Abstract Test Case

scholarly journals Empirical Study of the Effects of Different Similarity Measures on Test Case Prioritization

2016 ◽  
Vol 2016 ◽  
pp. 1-19 ◽  
Author(s):  
Rongcun Wang ◽  
Shujuan Jiang ◽  
Deng Chen ◽  
Yanmei Zhang
Keyword(s):  
Euclidean Distance ◽  
Similarity Measures ◽  
Regression Testing ◽  
Test Case ◽  
Test Cases ◽  
Test Case Prioritization ◽  
Distance Information ◽  
The Common ◽  
Global Similarity ◽  
Execution Order

Similarity-based test case prioritization algorithms have been applied to regression testing. The common characteristic of these algorithms is to reschedule the execution order of test cases according to the distances between pair-wise test cases. The distance information can be calculated by different similarity measures. Since the topologies vary with similarity measures, the distances between pair-wise test cases calculated by different similarity measures are different. Similarity measures could significantly influence the effectiveness of test case prioritization. Therefore, we empirically evaluate the effects of six similarity measures on two similarity-based test case prioritization algorithms. The obtained results are statistically analyzed to recommend the best combination of similarity-based prioritization algorithms and similarity measures. The experimental results, confirmed by a statistical analysis, indicate that Euclidean distance is more efficient in finding defects than other similarity measures. The combination of the global similarity-based prioritization algorithm and Euclidean distance could be a better choice. It generates not only higher fault detection effectiveness but also smaller standard deviation. The goal of this study is to provide practical guides for picking the appropriate combination of similarity-based test case prioritization techniques and similarity measures.

scholarly journals Abstract Test Case Prioritization Using Repeated Small-Strength Level-Combination Coverage

2020 ◽  
Vol 69 (1) ◽  
pp. 349-372
Author(s):  
Rubing Huang ◽  
Weifeng Sun ◽  
Tsong Yueh Chen ◽  
Dave Towey ◽  
Jinfu Chen ◽  
...  
Keyword(s):  
Strength Level ◽  
Test Case ◽  
Test Case Prioritization ◽  
Abstract Test Case

scholarly journals Reinforcement Learning for Test Case Prioritization

2021 ◽  
pp. 1-1
Author(s):  
Mojtaba Bagherzadeh ◽  
Nafiseh Kahani ◽  
Lionel Briand
Keyword(s):  
Reinforcement Learning ◽  
Test Case ◽  
Test Case Prioritization
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