A Software Reliability Growth Model With Testing Effort Dependent Learning Function for Distributed Systems

Abstract

Effective software process improvement will not start until management insists that product development work be planned and properly managed. This becomes even more challenging in an increasing number of major system developments made up from distributed sub-system software projects. These sub-systems are integrated and validated to provide the final system and product release. The need is growing to estimate, risk assess, plan and manage the development of these distributed sub-systems and the final full system release. In this paper, an attempt has been made to model the software reliability growth phenomenon with testing effort in a distributed development environment. Proposed Non Homogeneous Poisson Process (NHPP) based model assumes that the software system consists of a finite number of reused and newly developed sub-systems. The reused sub-systems do not consider the effect of severity of the faults on the software reliability growth phenomenon because they stabilize over a period of time i.e., the growth is uniform whereas, the newly developed sub-system do consider that. Fault removal phenomenon for reused and newly developed sub-systems have been modeled separately and is summed up to get the total fault removal phenomenon of the software system. The applicability of our model is shown by validating it on software failure data sets obtained from different real software development projects. The comparisons with established models in terms of goodness of fit, the Akaike Information Criterion (AIC), Mean of Squared Errors (MSE) have been presented.

Testing Effort Dependent Software Reliability Growth Model with Dynamic Faults for Debugging Process

“…The proposed model is motivated by the work of Kapur et al [11] and Pachauri et al [12]. In this section, a Software Reliability Growth Model based on Non Homogenous Poisson Process (NHPP) is developed by incorporating two things, one is the testing effort and second one is dynamic fault.…”

“…The present study considered a growth model incorporating test effort and dynamic faults. A number of Software Reliability Growth Models have been constructed with or without testing effort [1][2][3][4][5][6][7][8][9][10][11][12]. Kapur et al [11] proposed Software reliability growth model with testing effort dependent learning function.…”

“…Considering the work of Kapur et al [11], Pachauri et al [12] the focus is to develop a more efficient Software Reliability Growth Model in debugging environment using Generalized Modified Weibull Distribution.…”

Enhancing and measuring the predictive capabilities of testing-effort dependent software reliability models

“…There are many papers that discuss the problems of considering and estimating the amount of testing-effort (TE) consumption during software testing (Kapur et al, 2004(Kapur et al, , 2006Huang and Kuo, 2002;Huang, 2005;Yamada et al, 1993). For example, Musa et al (1987) showed that execution time is a better exposure indicator for software reliability modeling than calendar time.…”

Considering Testing Efficiency and Testing Resource Consumption Variations in Estimating Software Reliability

“…A testing effort function (TEF) describes the distribution of TE (CPU time, manpower, etc) during the testing period. Putnam et al, 11 Yamada et al, 12,13 Bokhari and Ahmad, 14 Kapur et al, 15 Kuo et al 16 and Huang et al 17,18 proposed SRGM describing the relationship among the testing time, TEC and the number of software faults detected. Most existing SRGM belong to exponential-type models.…”