Paper Info
Title
A similarity-based approach for test case prioritization using historical failure data
Abstract
Test case prioritization is a crucial element in software quality assurance in practice, specially, in the context of regression testing. Typically, test cases are prioritized in a way that they detect the potential faults earlier. The effectiveness of test cases, in terms of fault detection, is estimated using quality metrics, such as code coverage, size, and historical fault detection. Prior studies have shown that previously failing test cases are highly likely to fail again in the next releases, therefore, they are highly ranked, while prioritizing. However, in practice, a failing test case may not be exactly the same as a previously failed test case, but quite similar, e.g., when the new failing test is a slightly modified version of an old failing one to catch an undetected fault. In this paper, we define a class of metrics that estimate the test cases quality using their similarity to the previously failing test cases. We have conducted several experiments with five real world open source software systems, with real faults, to evaluate the effectiveness of these quality metrics. The results of our study show that our proposed similarity-based quality measure is significantly more effective for prioritizing test cases compared to existing test case quality measures.
Year
DOI
Venue
2015
10.1109/ISSRE.2015.7381799
International Symposium on Software Reliability Engineering
Keywords
Field
DocType
Test case prioritization, Test quality metric, Similarity, Execution trace, Distance function, Historical data, Code coverage, Test size
Test suite,Code coverage,Test method,Data mining,Fuzz testing,Test Management Approach,Computer science,Regression testing,Test case,Reliability engineering,Test data generation
Conference
Citations 
PageRank 
References 
13
0.60
17
Authors
2
Name
Order
Citations
PageRank
Tanzeem Bin Noor1130.60
Hadi Hemmati262227.54