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Software Reliability Models: An In-depth Review of Fault Detection and Correction Processes

by Kaushal Kumar, Jitendra Kumar, Anil Kumar Singh, Md Shahid Iqbal
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 187 - Number 86
Year of Publication: 2026
Authors: Kaushal Kumar, Jitendra Kumar, Anil Kumar Singh, Md Shahid Iqbal
10.5120/ijca2026926492

Kaushal Kumar, Jitendra Kumar, Anil Kumar Singh, Md Shahid Iqbal . Software Reliability Models: An In-depth Review of Fault Detection and Correction Processes. International Journal of Computer Applications. 187, 86 ( Mar 2026), 56-65. DOI=10.5120/ijca2026926492

@article{ 10.5120/ijca2026926492,
author = { Kaushal Kumar, Jitendra Kumar, Anil Kumar Singh, Md Shahid Iqbal },
title = { Software Reliability Models: An In-depth Review of Fault Detection and Correction Processes },
journal = { International Journal of Computer Applications },
issue_date = { Mar 2026 },
volume = { 187 },
number = { 86 },
month = { Mar },
year = { 2026 },
issn = { 0975-8887 },
pages = { 56-65 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume187/number86/software-reliability-models-an-in-depth-review-of-fault-detection-and-correction-processes/ },
doi = { 10.5120/ijca2026926492 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2026-03-20T22:55:06.673756+05:30
%A Kaushal Kumar
%A Jitendra Kumar
%A Anil Kumar Singh
%A Md Shahid Iqbal
%T Software Reliability Models: An In-depth Review of Fault Detection and Correction Processes
%J International Journal of Computer Applications
%@ 0975-8887
%V 187
%N 86
%P 56-65
%D 2026
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The evaluation of software quality relies significantly on software reliability growth modeling (SRGM), where reliability quantifies the probability of uninterrupted system operation within a predetermined duration. Throughout the last four decades, researchers have introduced numerous Software Reliability Growth Models, predominantly utilizing the “Non-homogeneous Poisson process” as their mathematical foundation. These analytical frameworks play an indispensable role in guiding strategic decisions during software development processes, including financial planning, optimization of testing resource deployment, selection of appropriate release timelines, and change point analysis. This paper offers a wide-ranging review of research on SRGMs, addressing techniques for predicting software reliability through Fault Detection Processes and Fault Correction Processes, both crucial for thoughtful and forecasting software performance. Starting with Schneidewind's pioneering work [1] in 1975, various models have been proposed incorporating different delay functions and statistical approaches for analyzing FDP and FCP. Modern approaches account for the relationship between identifying bugs and fixing them, the lag time involved in these processes, and the resources required for testing activities. This creates more accurate forecasts and dependable assessments of system stability. The primary aim is to consolidate key contributions in the field, offering new researchers a valuable reference point for understanding the progression and nuances of SRGM. This review emphasizes fault detection and correction processes, time delay distributions, testing effort functions, and parameter estimation methods. By presenting this body of work cohesively, the review enables a clearer perspective on integrating FDP and FCP within reliability models and discusses recent developments and future directions for enhancing SRGMs.

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Index Terms

Computer Science
Information Sciences

Keywords

Software reliability growth model (SRGM); fault detection process (FCP); fault correction process (FDP); mean value function (MVF); maximum likelihood estimation (MLE); least squares estimation (LSE)

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