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Studia Universitatis Babes-Bolyai: Series Informatica
Article . 2020 . Peer-reviewed
License: CC BY NC ND
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Defect Prediction-Based Test Case Prioritization

Authors: Cristina Maria TIUTIN; Marc-Titus TRIFAN; Andreea VESCAN;

Defect Prediction-Based Test Case Prioritization

Abstract

Changes in the software necessitate confirmation testing and regression testing to be applied since new errors may be introduced with the modification. Test case prioritization is one method that could be applied to optimize which test cases should be executed first, involving how to schedule them in a certain order that detect faults as soon as possible.The main aim of our paper is to propose a test case prioritization technique by considering defect prediction as a criteria for prioritization in addition to the standard approach which considers the number of discovered faults. We have performed several experiments, considering only faults and the defect prediction values for each class. We compare our approach with random test case execution (for a theoretical example) and with the fault-based approach (for the Mockito project). The results are encouraging, for several class changes we obtained better results with our proposed hybrid approach.

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Keywords

Test Case Prioritization, Regression Testing, Defect Prediction, Average Percentage of Faults Detected (APFD)., Electronic computers. Computer science, QA75.5-76.95

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
gold