Earticle

초록

영어

Regression testing is an expensive, but important process in software testing. Unfortunately, there may be insufficient resources to allow for the re-execution of all test cases during regression testing. In this situation, test case prioritization techniques aim to improve the effectiveness of regression testing by ordering the test cases so that the most beneficial are executed first. In this paper we propose a new test case prioritization technique using Genetic Algorithm (GA). The proposed technique prioritizes subsequences of the original test suite so that the new suite, which is run within a time-constrained execution environment, will have a superior rate of fault detection when compared to rates of randomly prioritized test suites. This experiment analyzes the genetic algorithm with regard to effectiveness and time overhead by utilizing structurally-based criterion to prioritize test cases. An Average Percentage of Faults Detected (APFD) metric is used to determine the effectiveness of the new test case orderings.

목차

Abstract
 1. Introduction
 2. Related work
 3. Challenges in Time based Prioritization
 4. Proposed Prioritization Technique
  4.1 Overview
  4.2 Genetic Algorithm
 5. Empirical Evaluation
  5.1 Experiment Design
  5.2 Experiments and Results
 6. Conclusions
 References

키워드

저자

• R.Krishnamoorthi [ Department of Computer Science and Engineering ]
• S.A.Sahaaya Arul Mary [ Bharathidasan Institute of Technology Anna University ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Hybrid Information Technology

• 간기

  격월간

• pISSN

  1738-9968

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605