Study of Test Case Selection and Prioritization

Kire, Kevilienuo; Malhotra, Neha

doi:10.5120/14838-3100

Cited by 3 publications

(5 citation statements)

References 11 publications

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“…Untimely union is the impediment of Particle Swarm Optimization (PSO) and GA [21] . 4) ACO calculations, has been to a great extent connected into the field of administration and modern to acquire the ideal arrangement.…”

Section: Methodsmentioning

confidence: 99%

A novel algorithm to moderate the cost of scrutinized paths

Prasuna¹,

Raju²,

Kishan³

2017

IJET

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Software testing is all too often simply a bug hunt rather than a well-considered exercise in ensuring quality. More methodical models than a simple cycle of system-level test-fail-patch-test will be required to deploy safe autonomous vehicles at scale. There are many types of software testing is used to test software. Efferent systems and procedure are proposed for dealing with these issues. Utilization of transformative calculations for programmed test generation has been a territory of intrigue. This assignment should be possible on a premise of the Ant Colony Optimization method (ACO) of Swarm Intelligence as it isn't profoundly contemplated yet. Intends to locate the most limited way and Resolve the time issue. We are building up extra particular way to deal with testing by concentrating on those parts that are most critical so these ways can be tried first recognizing the most huge ways, the testing productivity can be expanded. Great results are discovered astoundingly expediently when GA is actualized. Producing an improved test suite (TS) is meta-heuristic issue, which can be settled by GA. The only objective of programming is not to determine the algorithm to accomplish a result but relevance and correctness of the result. Also, Furthermore, to be ascertained. Genetic Algorithm is a meta-heuristic algorithm, is employed for optimizing path testing to achieve total code coverage.

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Section: Methodsmentioning

confidence: 99%

A novel algorithm to moderate the cost of scrutinized paths

Prasuna¹,

Raju²,

Kishan³

2017

IJET

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show abstract

“…4. ACO algorithms, has been largely applied in the field of management and industrial to obtain the optimal solution .But its application in the field of software testing for generating test data has not been deeply studied until today [22].…”

Section: Research Methodology 31 Strategymentioning

confidence: 99%

“…In real time the ACO can adapt to changes and it is better than Simulated Annealing and Genetic Algorithm for problems like Travelling Salesman Problem where the graph changes dynamically [22]. 2.…”

Section: Research Methodology 31 Strategymentioning

confidence: 99%

“…2. ACO outperforms simulated annealing and genetic algorithm for the metrics namely average coverage (AC), successful rate (SR) and average convergence generation (AG) [22]. 3.…”

Section: Research Methodology 31 Strategymentioning

confidence: 99%

“…The limitation of Bee Colony Optimization is that it is complicated to map the waggle dance to the solution, it requires deep knowledge of mathematics and one must have the knowledge of factors such as waggle dance, food source quality etc. Premature convergence is the limitation of Particle Swarm Optimization (PSO) and GA [22]. 4.…”

Section: Research Methodology 31 Strategymentioning

confidence: 99%

See 2 more Smart Citations

Ants Optimization for Minimal Test Case Selection and Prioritization as to Reduce the Cost of Regression Testing

Sethi¹,

Rani²,

Singh³

2014

IJCA

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Software testing is the major process in software development life cycle. Regression testing is very costly and inevitable activity that is to be performed in a restricted environment to ensure the validity of modified software. It is inefficient to rerun every test case from test suite when some kind of modification is done in the software. Test case selection and prioritization techniques select and organize the test cases in a test suite based on some criteria such that the faults are covered quickly with minimum execution time. This task can be done on basis of the Ant Colony Optimization technique (ACO) of Swarm Intelligence as it is not deeply studied yet. The main objective of this thesis is to solve the path problem: Means to find the shortest path and Resolve the time problem: Means to minimize the time of finding shortest path. Because of time and cost constraint, it is not possible to perform extensive regression testing. Techniques such as test case selection and prioritization are used to solve the problem of time and cost constraints. In this paper we are modifying the previous technique to get better results in case of execution time and then the Effectiveness of techniques is checked with the help of APFD metric.

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A Survey on Test Case Prioritization Techniques for Regression Testing

Sagar

Prasad

2017

Indian Journal of Science and Technology

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Study of Test Case Selection and Prioritization

Cited by 3 publications

References 11 publications

A novel algorithm to moderate the cost of scrutinized paths

A novel algorithm to moderate the cost of scrutinized paths

Ants Optimization for Minimal Test Case Selection and Prioritization as to Reduce the Cost of Regression Testing

A Survey on Test Case Prioritization Techniques for Regression Testing

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