Optimum bug fixing rate and bug fixing time detection by software reliability modelling

Abstract

Purpose

Software reliability growth models (SRGMs) are used to assess and predict reliability of a software system. Many of these models are effective in predicting future failures unless the software evolves.

Design/methodology/approach

This objective of this paper is to identify the best path for rectifying the BFT (bug fixing time) and BFR (bug fixing rate). Moreover, the flexible software project has been examined while materializing the BFR. To enhance the BFR, the traceability of bug is lessened by the version tag virtue in every software deliverable component. The release time of software build is optimized with the utilization of mathematical optimization mechanisms like ‘software reliability growth’ and ‘non-homogeneous Poisson process methods.’

Findings

In current market scenario, this is most essential. The automation and variation of build is also resolved in this contribution. Here, the software, which is developed, is free from the bugs or defects and enhances the quality of software by increasing the BFR.

Originality/value

In current market scenario, this is most essential. The automation and variation of build is also resolved in this contribution. Here, the software, which is developed, is free from the bugs or defects and enhances the quality of software by increasing the BFR.

Citation

Narvaneni, R.R. and Suresh Babu, K. (2022), "Optimum bug fixing rate and bug fixing time detection by software reliability modelling", International Journal of Intelligent Unmanned Systems, Vol. 10 No. 1, pp. 240-254. https://doi.org/10.1108/IJIUS-07-2021-0065