Reliability Analysis for Upgraded Software with Updates

In today’s continuous fluctuation market scenario, no software comes in single version. Competition and survival requirement has led firms to come up with upgraded version of the parent software as soon as possible. Testing these software(s) for reliability has been a cumbersome task for their developers, and the task is all the more tedious when dealing with successive versions. Highly reliable software requires thorough debugging throughout the testing as well as in the operational phase, and as a consequence, the role of updating (patching) implicitly comes in picture. With patching, the overall testing period definitely increases, but it also results in enhanced usability and overall performance of the system. Consequently, a large number of firms are employing updating strategies to gain competitive advantage over its rival firms. These updates help the firms to look after any ambiguity (if present) and overcome the functional issues of the software. In this paper, making use of convolution methodology, we have proposed a mathematical approach for keeping a check on the reliability of the upgraded software incorporating the concept of update. The proposed model incorporates this varied aspect in the fault removal under multi-releases, and thereby a procedural approach based on differing performance during the testing and operational environment is the unique aspect of the article. Further to supplement the results, numerical analysis has been done on real software failure data.