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Requirement Aware Optimisation of Test Case Selection (R-OTCS) approach

Vivek Kulkarni, R. Madhanmohan, H. Venkateswara Reddy

Abstract


TCP (test case prioritization) is a difficult problem to solve. Its complexity grows in direct proportion to the addition or update of project modules. Prioritizing an enormous amount of test cases is a complicated task. To optimize test case prioritization, a variety of strategies and techniques are available. It has been noted that eradicating all flaws from a software project is very hard, and even after using several testing methodologies, some flaws remain in the project. The work that is suggested priorities not only the fault detection abilities of test cases across the whole suite, but also the defect degree and commercial relevance of the test case execution. The purpose of this study is to locate all undiscovered faults using a Requirement Aware Optimization of Test Case Selection (R-OTCS) approach. We applied the genetic algorithm (GA) to optimize this proposed approach. We calibrated GA for performance before applying it to a dataset by fine-tuning the algorithm. The proposed technique improves software dependability by finding errors early and detecting serious problems first. Prioritizing test cases that address business critical/major requirements also improves reliability. The average percentage of fault detection (APFD) metric is used to assess all generated sequences. The business criticality value is used to determine the test case score. The suggested ROTCS approach yielded encouraging results in terms of APFD score and fault detection rate.


Keywords


Optimisation; Genetic Algorithm; Testing; Prioritization; Test Cases

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References


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DOI: https://doi.org/10.32629/jai.v7i5.1045

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Copyright (c) 2024 Vivek Kulkarni, R. Madhanmohan, H. Venkateswara Reddy

License URL: https://creativecommons.org/licenses/by-nc/4.0/