RESEARCH PAPER
A novel test case prioritization method based on problems of numerical software code statement defect prediction
1
School of Reliability and Systems Engineering Beihang University No.37 Xueyuan RD. Haidian, 100191, Beijing, China
2
Ji'an Municipal Industry and Information Technology Bureau 11/F, Block B, Administration Center Building Jizhou District, Ji'an, Jiangxi, 343000, China
Publication date: 2020-09-30
Eksploatacja i Niezawodność – Maintenance and Reliability 2020;22(3):419-431
KEYWORDS
software defect predictiontest case prioritizationcode statement metricsmachine learningsoftware testing
ABSTRACT
Test case prioritization (TCP) has been considerably utilized to arrange the implementation order of test cases, which contributes
to improve the efficiency and resource allocation of software regression testing. Traditional coverage-based TCP techniques, such
as statement-level, method/function-level and class-level, only leverages program code coverage to prioritize test cases without
considering the probable distribution of defects. However, software defect data tends to be imbalanced following Pareto principle.
Instinctively, the more vulnerable the code covered by the test case is, the higher the priority it is. Besides, statement-level coverage is a more fine-grained method than function-level coverage or class-level coverage, which can more accurately formulate
test strategies. Therefore, we present a test case prioritization approach based on statement software defect prediction to tame
the limitations of current coverage-based techniques in this paper. Statement metrics in the source code are extracted and data
pre-processing is implemented to train the defect predictor. And then the defect detection rate of test cases is calculated by combining the prioritization strategy and prediction results. Finally, the prioritization performance is evaluated in terms of average
percentage faults detected in four open source datasets. We comprehensively compare the performance of the proposed method
under different prioritization strategies and predictors. The experimental results show it is a promising technique to improve the
prevailing coverage-based TCP methods by incorporating statement-level defect-proneness. Moreover, it is also concluded that
the performance of the additional strategy is better than that of max and total, and the choice of the defect predictor affects the
efficiency of the strategy.
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