Abstract

Testing life cycle poses a problem of achieving a high level of software reliability while achieving an optimal release time for the software. To enhance the reliability of the software, retain the market potential for the software and reduce the testing cost, the enterprise needs to know when to release the software and when to stop testing. To achieve this, enterprises usually release their product earlier in market and then release patches subsequently. Software patching is a process through which enterprises debug, update, or enhance their software. Software patching when used as a debugging process ensures an optimal release for the product, increasing the reliability of the software while reducing the economic overhead of testing. Today, due to the diverse and distributed nature of software, its journey in the market is dynamic, making patching an inherent aspect of testing. A patch is a piece of software designed to update a computer program or its supporting data to fix or improve it. Researchers have worked in the field to minimize the testing cost, but so far, reliability has not been considered in the models for optimal time scheduling using patching. In this paper, we discuss reliability, which is a major attribute of the quality of software. Thus, to address the issues of testing cost, release time of software, and a desirable reliability level, we propose a reliability growth model implementing software patching to make the software system reliable and cost effective. The numeric illustration has been implemented using real-life software failure data set.

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