Abstract

This paper presents a general testing coverage software reliability modeling framework that covers imperfect debugging and considers not only fault detection processes (FDP) but also fault correction processes (FCP). Numerous software reliability growth models have evaluated the reliability of software over the last few decades, but most of them attached importance to modeling the fault detection process rather than modeling the fault correction process. Previous studies analyzed the time dependency between the fault detection and correction processes and modeled the fault correction process as a delayed detection process with a random or deterministic time delay. We study the quantitative dependency between dual processes from the viewpoint of fault amount dependency instead of time dependency, then propose a generalized modeling framework along with imperfect debugging and testing coverage. New models are derived by adopting different testing coverage functions. We compared the performance of these proposed models with existing models under the context of two kinds of failure data, one of which only includes observations of faults detected, and the other includes not only fault detection but also fault correction data. Different parameter estimation methods and performance comparison criteria are presented according to the characteristics of different kinds of datasets. No matter what kind of data, the comparison results reveal that the proposed models generally give improved descriptive and predictive performance than existing models.

Highlights

  • Software reliability growth models (SRGMs) based on the nonhomogeneous Poisson process (NHPP) have been provided to describe the software reliability in previous eras [1].One common assumption of most models is that faults will be instantaneously removed after the failure caused by the faults being observed

  • We develop a general framework for modeling both fault detection and correction processes from the viewpoint of fault amount dependency instead of time dependency in the context of different testing coverage and imperfect debugging

  • Relationship between the mean value functions of detected faults and corrected faults is with incorporation of both fault detection processes and fault correction processes

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Summary

Introduction

Software reliability growth models (SRGMs) based on the nonhomogeneous Poisson process (NHPP) have been provided to describe the software reliability in previous eras [1]. Chatterjee et al presented a unified approach to model the reliability growth of software with imperfect debugging and three types of testing coverage curves, such as the exponential, Weibull, and S-shaped [30] They proposed a SRGM considering the effects of uncertain testing environment and testing coverage of multi-release software in the presence of two different types of faults [31]. We develop a general framework for modeling both fault detection and correction processes from the viewpoint of fault amount dependency instead of time dependency in the context of different testing coverage and imperfect debugging.

Assumptions
Framework and New Testing Coverage Models
Parameter Estimation Methods and Model Comparison Criteria
Parameter Estimation Method for Paired FDP and FCP Models
Parameter Estimation Method for Single Process Models
Criteria for a Comparison of the Descriptive Power of Models with Single
Case Study 1
Comparisons ofofthe results based on M1-M5 and M17-M19
Case Study 3
Findings
Conclusions
Full Text
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