Software testing is an activity which is aimed for evaluating quality of a program and also for improving it, by identifying defects and problems. Software testing strives for achieving its goals (both implicit and explicit) but it does have certain limitations, still testing can be done more effectively if certain established principles are be followed. In spite of having limitations, software testing continues to dominate other verification techniques like static analysis, model checking, and proofs. So it is indispensable to understand the goals, principles and limitations of software testing so that the effectiveness of software testing could be maximized. General TermsSoftware Engineering, Software Testing.

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Software reliability growth models (SRGM) are employed to aid us in predicting and estimating reliability in the software development process. Many SRGM proposed in the past claim to be effective over previous models. While some earlier research had raised concern regarding use of delayed S-shaped SRGM, researchers later indicated that the model performs well when appropriate testing-effort function (TEF) is used. This paper proposes and evaluates an approach to incorporate the log-logistic (LL) testing-effort function into delayed S-shaped SRGMs with imperfect debugging based on non-homogeneous Poisson process (NHPP). The model parameters are estimated by weighted least square estimation (WLSE) and maximum likelihood estimation (MLE) methods. The experimental results obtained after applying the model on real data sets and statistical methods for analysis are presented. The results obtained suggest that performance of the proposed model is better than the other existing models. The authors can conclude that the log-logistic TEF is appropriate for incorporating into delayed S-shaped software reliability growth models.

Testing technique selection and evaluation remains a key issue in software testing. Industry practitioners need concrete evidence to select proper testing techniques in STLC. Despite the large number of empirical studies which attempt to study the testing techniques' applicability conditions and allied factors, we are still without realistic and generalized results as studies lack a formal foundation and are not complete in all respects. Additionally, besides varying significantly in terms of parameters they have taken into consideration, many existing studies show contradictory results. Even though the researchers stress on replication of these studies under a common set of guidelines, however, attempts to aggregate results from such replications still has not been fruitful so far. As such, to bridge the gap between researchers and industry professionals, we propose to carry out evaluation of testing techniques on a large scale under a unified framework in an open-source fashion so that the realistic and generalized results are obtained in a shorter span of time.

Cloud computing is rapidly gaining significant attention in our day-to-day life. Cloud computing and software testing is one of the hot research areas for both industry and research. While one aspect of this merger, i.e. cloud testing (STaaS), is on real high and is receiving significant research attention, there is a lack of research addressing the other side, i.e. ‘testing the cloud'. This chapter tries to differentiate between ‘cloud testing' and ‘testing the cloud' and explains why ‘testing the cloud' is so crucial. In addition, it also explains what tests should be done in order to mitigate the challenges and risks of migrating our businesses to the cloud. This chapter provides a comprehensive tutorial to discuss the testing of cloud and also explains the need, objectives, requirements and challenges in ‘testing the cloud'.

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