Regression Testing based on Genetic Algorithms

Khanna, Esha

doi:10.5120/ijca2016912201

Cited by 7 publications

(4 citation statements)

References 16 publications

(17 reference statements)

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“…Researchers are also attracted towards the adaptive behavior of ACO in which they tried to modify the algorithm based on some parameters to get better results in case of test case selection as done by [12][13][14][15]. Similarly many researchers and practitioners are more attracted towards genetic algorithm for software testing and applied the same at various phases of testing as in [16,17].…”

Section: Related Workmentioning

confidence: 99%

Hybrid swarm and GA based approach for software test case selection

Palak¹,

Gulia²

2019

IJECE

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<span>Being a crucial step and deciding factor for software reliability, software testing has evolved a long way and always attracted researchers due to various inherent challenges. The quality of a software application depends on the effectiveness of the testing carried out during development and maintenance phase. Testing is a crucial but time consuming activity that influences the overall cost of software development. Thus a minimal but efficient test suite selection is the need of the hour. This paper presents a hybrid technique based on swarm based search technique and GA (Genetic Algorithm) for selection of promising test cases to reduce the overall development cost and time of the application. We took component based software into consideration as they offer some inherent advantages over traditional software development paradigms.</span>

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Section: Related Workmentioning

confidence: 99%

Hybrid swarm and GA based approach for software test case selection

Palak¹,

Gulia²

2019

IJECE

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“…Regression testing is an important process in software testing because it ensures the developers that the changed application will not introduce new errors [1], [2]. However, time, cost and resource constraints make it hard to execute all test cases [3]- [5]. Time is limited because of the quick release cycles for modified software which limits the time for performing regression testing [6].…”

Section: Introductionmentioning

confidence: 99%

The Application Of Machine Learning In Test Case Prioritization - A Review

Meçe

Paci

Binjaku

2020

EJECE

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Regression testing is very important but also a very costly and time-consuming activity that ensures the developers that changes in the application will not bring new errors. Retest all, selection of test cases and prioritization of test cases (TCP) approaches are used to enhance the efficiency and effectiveness in regression testing. While test case selection techniques decrease testing time and cost, it can exclude some critical test cases that can detect the faults. On the other hand, test case prioritization considers all test cases and execute them until resources are exhausted or all test cases are executed, while always focusing on the most important ones. Over the years, machine learning has found wide usage in solving different problems in software engineering. Software development and maintenance problems can be defined as learning problems and machine learning techniques have shown to be very effective in solving these problems. In the range of application of machine learning, machine learning techniques have also found usage in solving the test case prioritization problem. In this paper, we investigate the application of machine learning techniques in test case prioritization. We survey some of the most recent studies made in this field and provide information like techniques of machine learning used in TCP process, metrics used to measure the effectiveness of the proposed methods, data used to define the priority of test cases and some advantages or limitations of application of machine learning in TCP.

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“…In the work by Khanna, E., genetic algorithm reorders regression test cases on criteria of maximum fault detection [25]. Fitness value of test cases is evaluated using number of fault covered.…”

Section: Genetic Algorithmsmentioning

confidence: 99%

On the Applicability of Soft Computing Techniques in Regression Testing

Khanna¹,

Khanna²

2017

IJCA

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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.

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Regression Testing based on Genetic Algorithms

Cited by 7 publications

References 16 publications

Hybrid swarm and GA based approach for software test case selection

Hybrid swarm and GA based approach for software test case selection

The Application Of Machine Learning In Test Case Prioritization - A Review

On the Applicability of Soft Computing Techniques in Regression Testing

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