Entropy based enhanced particle swarm optimization on multi‐objective software reliability modelling for optimal testing resources allocation. (5th February 2021)

• Record Type: Journal Article
• Authors: Rani, Pooja; Mahapatra, G. S.
• Is Part Of: Software testing, verification & reliability. Volume 31:Number 6(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-02-05
• Subjects: entropy -- imperfect debugging -- modular testing -- particle swarm optimization -- resource allocation -- software reliability; Computer software -- Testing -- Periodicals; Computer software -- Verification -- Periodicals; Computer software -- Reliability -- Periodicals; 005.14
• DOI: 10.1002/stvr.1765
• Languages: English
• ISSNs: 0960-0833

Abstract

Summary: This paper proposes a generalization of the exponential software reliability model to characterize several factors including fault introduction and time‐varying fault detection rate. The software life cycle is designed based on module structure such as testing effort spent during module testing and detected software faults etc. The resource allocation problem is a critical phase in the testing stage of software reliability modelling. It is required to make decisions for optimal resource allocation among the modules to achieve the desired level of reliability. We formulate a multi‐objective software reliability model of testing resources for a new generalized exponential reliability function to characterizes dynamic allocation of total expected cost and testing effort. An enhanced particle swarm optimization (EPSO) is proposed to maximize software reliability and minimize allocation cost. We perform experiments with randomly generated testing‐resource sets and varying the performance using the entropy function. The multi‐objective model is compared with modules according to weighted cost function and testing effort measures in a typical modular testing environment.