Measuring commercial software operational reliability: an interdisciplinary modelling approach

Software reliability is defined as the probability of failure–free software operation for a specified period of time (American National Standards Institute – ANSI). It quantifies the failures of software systems and is the key factor in software quality [19]. It is also a major subject of Software Reliability Engineering (SRE) – a discipline which quantitatively studies the operational behavior of software systems with respect to the reliability requirements of the user. The quantitative study of software systems concerning reliability involves software reliability measurements. Measurement of software reliability includes two activities, i.e., software reliability estimation and software reliability prediction. Software reliability modelsare used to measure a software product's reliability or to estimate the number of latent defects when it is available to the customers. Such an estimate is important for two reasons: 1) as an objective statement of the quality of the product and 2) for resource planning for the software maintenance phase [9]. Research has been conducted in software reliability engineering over the past three decades and many software reliability models have been proposed [4, 12, 19, 20, 23, 29, 30]. The pioneering attempt in non-homogenous Poisson process (NHPP) based on software reliability model was the exponential model [7]. The model describes the failure/removal phenomenon by an exponential curve. There are also software reliability models that describe either S-shaped curves or a mixture of exponential and S-shaped curves (i.e., flexible). Some of the important contributions of these type of models are due to[11, 21, 32] etc. In most of these models it is assumed that whenever an attempt is made to remove a defect, it is removed with certainty i.e., a case of perfect debugging. But the debugging activity is not always Omar ShAtnAwi