Software reliability is considered as a quantifiable metric, which is defined as the probability of a software to operate without failure for a specified period of time in a specific environment. Various software reliability growth models have been proposed to predict the reliability of a software. These models help vendors to predict the behaviour of the software before shipment. The reliabili...

Software reliability growth models only become useful if it is possible to estimate their parameters. However, the parameter estimation is normally done numerically, and hence a substantial amount of data is all too often needed. This need is often not fulfilled by modern development processes, for example incremental development and agile methods. This position paper identifies three alternati...

A Non Homogenous Poisson Process (NHPP) with its mean value function generated by the cumulative distribution function of inverse Rayleigh distribution is considered. It is modeled to assess the failure phenomenon of a developed software. When the failure data is in the form of number of failures in a given interval of time the model parameters are estimated by the maximum likelihood method. Th...

Two fault-tolerant software techniques are investigated: recovery block and N-version programming. For each, the stable reliability model is transformed into a model that considers reliability growth via the transformation approach based on the hyperexponential model. Analytic and numeric processing of the transformed models identify the influence of fault removal on the reliability of the faul...

Finite failure NHPP models proposed in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault, and are inadequate to describe the failure process underlying certain failure data sets. In this paper, we propose the loglogistic reliability growth model, which can capture the increasing=decreasing nature of the failure occurrence rat...

“Software test-coverage measures” quantify the degree of thoroughness of testing. Tools are now available that measure test-coverage in terms of blocks, branches, computation-uses, predicate-uses, etc. that are covered. This paper models the relations among testing time, coverage, and reliability. An LE (logarithmic-exponential) model is presented that relates testing effort to test coverage (b...