An Ant Colony Optimization Algorithm Based Automated Generation of Software Test Cases

Abstract

Software testing is an important process of detecting bugs in the software product thereby a quality software product is developed. Verification and Validation (V & V) activities are the effective methods employed to achieve quality. Static and dynamic testing activities are performed during V & V. During static testing, the program code is not executed while in dynamic testing (Black Box and White Box), the execution of the program code is performed. Effective test cases are designed by both these methods. Tables are employed to represent test case documentation. The most beneficial representation - State table based testing, for generating test inputs is explained with the help of state graphs and state tables. This technique is mainly employed in embedded system software testing, real time applications and web application based software product testing where time constraints are a major criteria. Automatic generation of test cases will help to reduce time overhead in testing activities. Our study is to develop optimum test cases by a modified Ant Colony Optimization (ACO) technique in an automated method and it ensures maximum coverage. The prediction model used in this paper ensures better accuracy of the design of test inputs. A comparison of the similar optimization techniques was also discussed that is used in automated test case generation. A case study of the various states during the execution of a task in an operating system has been presented to illustrate our approach.