RELIABILITY ANALYSIS OF PROJECT AND PRODUCT TYPE SOFTWARE IN OPERATIONAL PHASE INCORPORATING THE EFFECT OF FAULT REMOVAL EFFICIENCY

Abstract

Since the early 1970's numerous Software Reliability Growth Models (SRGM) have been proposed in the literature to estimate the software reliability measures such as the remaining number of faults, failure rate and reliability growth during the testing phase. These models are applied to the software testing data collected during the testing phase and then are often used to predict the software failures in operational phase. In practice simulating mirror image of the diverse testing environment representative of the operational environment is difficult in practice and hence the simulated testing environment during the testing phase may not be similar to the conditions that exist in the operational phase. During testing phase testing is performed under a controlled environment whereas during the operational phase failure phenomenon depends on the operational environment and usage of software. Therefore an SRGM developed for the testing phase is not suitable for estimating the reliability growth during the operational phase. In this paper, we propose a generalized Software Reliability Growth Model, which can be used to estimate number of faults during the testing phase and can be easily extended to the operation phase. In the testing phase, it is appropriate to estimate the reliability growth with respect to the amount of testing resources spent on testing whereas in the operational phase the amount of effort to be spent on removing a fault reported by a user is fixed by the developer. The number of failures detected and hence the reliability growth during the user phase depends on the usage of software. The proposed model appropriately incorporates these changes. Further we categorize the software into two-categories- (a) project and (b) product type software. Appropriate usage functions are linked to both project and product type software. To describe the fault removal phenomenon, imperfect debugging environment is incorporated into the model building. The paper highlights an interdisciplinary mathematical modeling approach in Software Reliability Engineering and Marketing. The proposed model is validated for both phases using the software failure data sets obtained from different sources. Model describes the failure phenomenon for these data sets fairly.