A Parallel Early Binding Recursive Ant Colony Optimization (PEB-RAC) Approach for Generating Optimized Auto Test Cases from programming Inputs

Dubey, Yogita; Singh, Divakar; Singh, Anju

doi:10.5120/ijca2016908420

Cited by 2 publications

(5 citation statements)

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“…According to [8], many types of coverage criteria can be used with the UML state chart diagram, such as all-states coverage, all-configurations coverage, all-transitions coverage, all-transition-pairs coverage, all-loop-free-paths coverage, all-one-loop-paths coverage, all-round-trips coverage, and all-paths coverage. Therefore, there are advantages in developing such mechanism that increases the coverage and diversity of test cases, while minimize and prioritize the generated test cases [9]. MBT is used to validate requirements, check the requirement's consistencies, and generate test cases that are focused on the behavioural aspects of the software (Society, 2014).…”

Section: Introductionmentioning

confidence: 99%

“…However, many researchers used a number of methods to reach optimal possible test cases. The most commonly used methods used by researchers to minimize the number of test cases include ant colony optimization, bee colony optimization, genetic algorithm, and firefly algorithm [2,9,[19][20][21]. These methods try to generate test data in an automated manner to facilitate the task of software testing [24].…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, this study uses a firefly algorithm to minimize and prioritize test cases. Prioritization of test sequence generation [38] Firefly algorithm Prioritization of generated test paths [9] Ant colony optimization Test case optimization for automated testing [23] Firefly algorithm…”

Section: Introductionmentioning

confidence: 99%

“…An optimized test case system for the automated testing using ant colony optimization [9]. To improve the performance of the testing process, they used data mining techniques to reduce the size of the test cases.…”

Section: Introductionmentioning

confidence: 99%

“…The previous studies [9,14,23,24,36] focused on minimization and prioritization for the test sequence, where they only generate the paths and didn't generate the test cases. They used many types of methods and techniques to achieve their objectives.…”

Section: Introductionmentioning

confidence: 99%

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Test Case Minimization Applying Firefly Algorithm

Hashim¹,

Dawood²

2018

Int. J. Adv. Sci. Eng. Inf. Technol.

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The objective of this study is to propose a test case minimization method performed on UML statechart to produce test cases that are optimal while considering higher coverage criteria. Current test case generation techniques consume a large amount of time and cost with less testing coverage, while generating large number or test cases, what results in difficulties in detecting the faults and errors in the tested systems. Many approaches on test case minimization use genetic algorithms, model checking, or graph search algorithms to reduce the number of generated test cases, also the using of UML diagrams to test the system requirements and design before implementing it in the coding phase. However, these studies lack concentration in achieving higher coverage criteria and minimization in the generated test cases in the same time. The proposed test case minimization method has the following steps: provide weight to the paths, calculate path coverage for each path, transform an immediate graph into an adjacency matrix, which later is used to apply firefly algorithm and generate optimal test cases. A review on of the previous similar research in this domain has been presented and analysed to identify the issues and gaps in this domain. The steps use to perform the test case minimization have been presented together with some example and formula used. Findings from this study shows that this test case minimization has successful covered more types of test coverage which are all state, all transition, all transition pairs and all-one-loop paths. At the same time, it is capable of minimizing the number of test cases.

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Section: Introductionmentioning

confidence: 99%