Design and Analysis of Cost-Cognizant Test Case Prioritization Using Genetic Algorithm with Test History

Huang, Yu-Chi; Huang, Chin‐Yu; Chang, Jun-Ru; Chen, Tsan-Yuan

doi:10.1109/compsac.2010.66

Cited by 27 publications

(21 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Y.C. Huang in [3] proposed a cost-cognizant prioritization technique that arranged test cases in accordance with their history information using genetic algorithm. The technique performed prioritization of test cases based on their test costs and fault severities, without examining the source code.…”

Section: Related Workmentioning

confidence: 99%

Performance Analysis of Hybrid Approach Comprising Genetic Algorithm and Adaptive Approach on Test Case Prioritization

Walia¹,

Bajaj²

2016

IJCA

View full text Add to dashboard Cite

Regression testing is an important domain of software testing, which attempts to verify all the fixes that had been introduced into the software throughout its development period by means of test suites. In spite of being exorbitant in terms of time and cost, it cannot be evaded. As a result, lot many techniques have been proposed in the past in order to minimize these expenses. One such technique is Test Case Prioritization, which works by scheduling the execution order of test cases with a goal of improving the fault detection rate. This paper introduces a hybrid approach to test case prioritization, by combining Genetic Algorithm and Adaptive approach. Initially, it applies the Adaptive approach for the prioritization of test cases. Further, the left over test cases are prioritized by applying the Genetic Algorithm. Finally, the outcomes obtained from the proposed approach are compared with those of Genetic Algorithm based on two parameters: execution time and average percentage of statement coverage (APSC) values. The evaluation results prove that the proposed approach performs better in terms of both the parameters.

show abstract

Section: Related Workmentioning

confidence: 99%

Performance Analysis of Hybrid Approach Comprising Genetic Algorithm and Adaptive Approach on Test Case Prioritization

Walia¹,

Bajaj²

2016

IJCA

View full text Add to dashboard Cite

show abstract

“…al. proposed a cost cognizant prioritization technique which takes into account test case costs and fault severities in test case prioritization [27]. The work used genetic algorithm and test historical records to prioritize the test cases of regression test suite.…”

Section: Genetic Algorithmsmentioning

confidence: 99%

On the Applicability of Soft Computing Techniques in Regression Testing

Khanna¹,

Khanna²

2017

IJCA

View full text Add to dashboard Cite

Regression testing is required whenever changes are incorporated in software. Regression testing re-executes the test cases to verify that changes made during maintainance phase have not caused any unintended effects. Test case prioritization technique re-orders the test cases in such a way that important test cases are executed within the resources. The work reviews different test case prioritization techniques. The work also presents computational intelligence based test case prioritization techniques. The work reviews test case prioritization based on Neural Networks, Genetic Algorithms and Fuzzy Logic.

show abstract

“…Y.C. Huang in [3] proposed a costcognizant prioritization technique that ordered test cases according to their history information by using genetic algorithm. The technique prioritized test cases on the basis of their test costs and fault severities, without analyzing the source code.…”

Section: Related Workmentioning

confidence: 99%

Performance Enhancement of Test Case Prioritization Using Hybrid Approach

Walia¹,

Bajaj²

2017

IJSEA

View full text Add to dashboard Cite

Regression Testing is an indispensable part of software testing process. It validates all the modifications that have been introduced into the system throughout the development period. Although it is an expensive process in terms of time and cost, yet it cannot be avoided. Therefore, various techniques have been introduced in the past for reducing the expenses involved in this process. Test Case Prioritization is one such technique that schedules the execution order of test cases with an aim to improve the rate of fault detection. In this paper, a hybrid approach has been presented which is a combination of two approaches, Adaptive approach and Genetic algorithm. The approach works by firstly employing an adaptive approach to prioritize the test cases according to their statement coverage. Further, the leftover test cases are prioritized using Genetic Algorithm. Finally, the results of the proposed approach are compared with those of Genetic Algorithm based on two parameters: execution time and average percentage of statement coverage (APSC) values. The results confirm that the proposed approach performs better in terms of both parameters.

show abstract

Design and Analysis of Cost-Cognizant Test Case Prioritization Using Genetic Algorithm with Test History

Cited by 27 publications

References 9 publications

Performance Analysis of Hybrid Approach Comprising Genetic Algorithm and Adaptive Approach on Test Case Prioritization

Performance Analysis of Hybrid Approach Comprising Genetic Algorithm and Adaptive Approach on Test Case Prioritization

On the Applicability of Soft Computing Techniques in Regression Testing

Performance Enhancement of Test Case Prioritization Using Hybrid Approach

Contact Info

Product

Resources

About