Optimization of Test Case Prioritization through Calibration of Genetic Algorithm

Authors

  • Priyanka Paygude , Dr. Shashank Joshi

Abstract

Changes are planned and are an inevitable part of the life cycle of software growth.
Regression testing is the costly time-consuming but critical testing activity that guarantees that the
improvements made in code have not changed features already in use. After any code update,
running the entire test suite is just an infeasible task due to time constraints. In order to achieve the
early fault detection goal, the test case prioritization technique encourages deciding on the test case
execution sequence. Ordering entire test suite is an NP hard optimization problem. This paper is the
solution to the problem of test case prioritization using the genetic algorithm optimization method.
The calibration of the parameters of the genetic algorithm plays a critical role in the performance of
the optimum solution. In this paper, we present a parametric study of genetic algorithm to solve the
problem of test case prioritization.

Published

2020-10-16

Issue

Section

Articles