Evolutionary algorithm based faults optimization of multi-modular software

Abstract

Computer systems characteristically comprise of hardware and either system or application software. In software developing environment, to accomplish precision is a great thought-provoking task. As there exists every probability that a mistake can be introduced and can persist in software during its established phase. Occurrence of fault cannot be predicted it may be due to human’s mistake which gets noticed during execution of a software activity and at times these faults can lead to failures with disastrous results. Hence, software organizations put emphasis on evading introduction of faults during software development before software gets released. A single software is a combination of several segments each segment has its specific functionality. When all these segments come together, the reliability of the software becomes of utmost importance as it quantifies software failures during the development process and also in operational phase. In order to increase the reliability, an all-inclusive test plan should be included which ensures that all requirements are covered and tested accurately. The main purpose is to maximize the number of faults removed within time constraint during the development phase of software. Each segment may consist of finite number of subparts. These subparts may have errors of different severity depending upon the factors like quality of manpower involved, computer time consumed, etc. The objective of this work is to maximize the number of faults removed in different modules using the Genetic Algorithm and optimized time while removing them; hence find out the faults of different severity and time devoted to removing them in various modules with a predefined reliability.