Advances in software technologies have promoted the growth of computer-related applications to a great extent. Building quality in terms of reliability of the software has become one of the main issues for software developers. Software testing is necessary to build highly reliable software. Monitoring and controlling the resource utilization, measuring and controlling the progress of testing, efficiency of testing and debugging personals and reliability growth are important for effective management the testing phase and meeting the quality objectives. Over the past 35 years many Software reliability growth models (SRGM) are proposed to accomplish the above-mentioned activities related to the software testing. From the literature it appears that most of the SRGM do not account the changes in the testing effort consumption. During the testing process especially in the beginning and towards the end of the testing frequent changes are observed in testing resource consumption due to changes in testing strategy, team constitution, schedule pressures etc. Apart from this testing efficiency plays a major role determining the progress of the testing process. In this paper we incorporate the important concept of testing resource consumption variations for Weibull type testing effort functions and testing efficiency in software reliability growth modeling. The performance of the proposed models is demonstrated through two real life data sets existing in literature. The experimental result shows fairly accurate estimating capabilities of the proposed models.
A Genetic Algorithm Approach for Optimal Allocation of Software Testing Effort
