2019
DOI: 10.1007/978-3-030-26630-1_3
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A Genetic Algorithm-Based Approach for Test Case Prioritization

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Cited by 5 publications
(3 citation statements)
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“…Other researchers used individual ML techniques for reliability prediction and fault detection [17,18]. A detailed literature review was carried out by Habtemariam and Mohapatra [25] and they elaborately discussed the kinds of literature available and their limitations Habtemariam, et al [26]. Habtemariam and Mohapatra [25] and Getachew, et al [27] use different machine learning and softcomputingtechineques in software testing for ensuring the reliability of the software [4,[27][28][29].…”
Section: Literature Surveymentioning
confidence: 99%
“…Other researchers used individual ML techniques for reliability prediction and fault detection [17,18]. A detailed literature review was carried out by Habtemariam and Mohapatra [25] and they elaborately discussed the kinds of literature available and their limitations Habtemariam, et al [26]. Habtemariam and Mohapatra [25] and Getachew, et al [27] use different machine learning and softcomputingtechineques in software testing for ensuring the reliability of the software [4,[27][28][29].…”
Section: Literature Surveymentioning
confidence: 99%
“…In the obtained results, they have claimed that the proposed technique reduces the cost of regression testing. In [Habtemariam and Mohapatra 2019], have classified test cases' prioritisation as one of the NP-hard class of problems. They have proposed a solution based on a genetic algorithm.…”
Section: Semantic-based Retrieval Using Metadatamentioning
confidence: 99%
“…The underpinnings of GA include genetic decoding, fitness evaluation, and biologically inspired operators. In addition, Holland added a new element, reversal, which is widely utilized in GA approaches [8]. As a result, an effective strategy is required that has the ability to improve the efficacy of test cases by increasing the rate of defect identification.…”
Section: Introductionmentioning
confidence: 99%