A Complexity Based Regression Test Selection Strategy

Falah, Bouchaib; Magel, Kenneth; Ariss, Omar El

doi:10.5121/cseij.2012.2501

Cited by 3 publications

(5 citation statements)

References 11 publications

(11 reference statements)

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“…Several researchers have worked on developing mutation software that automates these processes. As part of our research, we have used a mutation testing tool, MuClipse [1,2,3]. This tool was based on an implementation of the mutation tool MuJava, developed by Offutt [22] and his team.MuClipse is a plug-in for Eclipse IDE.…”

Section: Automated Mutation Toolmentioning

confidence: 99%

“…Mutation testing is a powerful fault-based testing technique used to ensure software quality and evaluate the effectiveness of test cases [1,2,3]. It is based on seeding faults into the source code by making some syntactic deviations.It uses mutation operators that substitutes sections of the programs to perform slight changes to the original source code [4].…”

Section: Introductionmentioning

confidence: 99%

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RSM: Reducing Mutation Testing Cost Using Random Selective Mutation Technique

Falah

Akour

Bouriat³

2015

MJCS

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Mutation testing has been neglected by researchers because of the high cost associated with the technique. To manage this issue, researchers have developed cost reduction strategies that aim to reduce the overall cost of mutation, while maintaining the effectiveness and the efficiency of testing. The purpose of this research paper is to present a new cost reduction strategy that cuts the cost of mutation testing through reducing the number of mutation operators used. The experimental part of the paper focuses on the implementation of this strategy on five different java applications. The results of the experiment areused to evaluate the efficiency and quantify the savings of our approach compared to two other existing mutation testing strategies.

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Section: Automated Mutation Toolmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

RSM: Reducing Mutation Testing Cost Using Random Selective Mutation Technique

Falah

Akour

Bouriat³

2015

MJCS

Self Cite

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“…Noting that we can have multiple APFD values for the same applied technique; thus, we represent the results in box plot diagram showing minimum and maximum APFD thresholds for each technique [1]. Fig.…”

Section: B Comparative Study Using Apfdmentioning

confidence: 99%

“…It is an intellectually challenging activity aimed at evaluating the capability of a program or system to determine whether or not it meets requirements [1]. It is an activity that should be done throughout the whole development process [2].…”

Section: Introductionmentioning

confidence: 99%

Towards Regression Testing Constraints

Falah¹,

Marghabi²

2014

IJMO

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Abstract-Regression testing is one of the most crucial and expensive testing process used to validate modified software and detect new faults introduced by into previously modified and tested code. To reduce the cost of regression testing, software testers may choose to prioritize their test cases to run the "important" ones, chosen by some metrics and constraints, earlier in the testing process. Various approaches have been introduced by previous researches in the form of prioritization technique focusing on specific goals of regression testing. One goal of prioritization is to increase a test suite's rate of fault detection. In this context, previous studies have shown that several prioritization techniques can significantly improve rate of fault detection, but these studies have also shown that the effectiveness of these techniques is relative to the assumptions made by the researchers concerning the testing environment. The variations observed in these experiments have mostly been linked to the subject program, test suites characteristics. This makes it difficult for testers to appropriately choose the correct prioritization technique for their testing scenarios. In this paper, regression prioritization techniques are described. Their performance, in fault detection rate, is assessed and the metrics used to assess the effect of variation through discussing experiments done in this context are specified. Then, the results are analyzed and insight about prioritization techniques selection under these constraints is provided.

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“…It is an intellectually challenging activity aimed at evaluating the capability of a program or system to determine whether or not it meets requirements [1].…”

Section: Introductionmentioning

confidence: 99%

ADBT Frame Work as a Testing Technique: An Improvement in Comparison with Traditional Model Based Testing

Akour¹,

Falah²,

Kaddouri³

2016

ijacsa

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Abstract-Software testing is an embedded activity in all software development life cycle phases. Due to the difficulties and high costs of software testing, many testing techniques have been developed with the common goal of testing software in the most optimal and cost-effective manner. Model-based testing (MBT) is used to direct testing activities such as test verification and selection. MBT is employed to encapsulate and understand the behavior of the system under test, which supports and helps software engineers to validate the system with various likely actions. The widespread usage of models has influenced the usage of MBT in the testing process, especially with UML. In this research, we proposed an improved model based testing strategy, which involves and uses four different diagrams in the testing process. This paper also discusses and explains the activities in the proposed model with the finite state model (FSM). The comparisons have been done with traditional model based testings in terms of test case generation and result.

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A Complexity Based Regression Test Selection Strategy

Cited by 3 publications

References 11 publications

RSM: Reducing Mutation Testing Cost Using Random Selective Mutation Technique

RSM: Reducing Mutation Testing Cost Using Random Selective Mutation Technique

Towards Regression Testing Constraints

ADBT Frame Work as a Testing Technique: An Improvement in Comparison with Traditional Model Based Testing

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