Optimisation of software testing technique using genetic algorithm

Abstract

The primary objective of software testing is to develop fault tolerant system with high precision. Software testing ensures that the product is developed as per the user s specification. It plays an important role in improving the quality and efficiency of software. Software testing is expensive and very extensive exercise in thoroughly checking the functional requirement of the system. Therefore, it consumes a lot of time and cost to ensure that the system is as per the specifications. To overcome the time constraint of testing, manual testing is replaced with automated testing. The main emphasis during software testing is to generate the minimum number of test cases for testing the maximum part of the software with respect to minimum time and cost. A test case can be defined as the collection of test inputs. The test cases are said to be complete and regressive, if it can trace the software for each and every user specifications. Test cases can be prioritized according to the execution time, resources and the cost of the software. Software testing can be categorized into two types Functional Testing and Structural Testing. Functional Testing is also known as Black box testing. This testing focuses on functional needs of the software and test the software on the basis of specification. There are numerous techniques which have been used for black box testing, like Boundary value analysis, Cause effect graph, Equivalence class etc. Structural testing is commonly known as white box testing. This testing focuses on pseudo-code of software. The tester analysis the pseudo-code of software and generates the test data for testing the program. There are numerous methodologies available which have been used in testing the software, like control flow testing, data Flow testing, mutation testing etc. The following coverage criteria s must be considered while testing the internal code. To implement software testing (Functional or Structural) various automated testing tools and techniques have been developed to improve the te