Testing Sufficiency Test (TST) - Evolving a New Model for Estimating Software Test Cases

摘要

One of the major challenges faced by project managers is to control huge testing efforts being spent on testing of the software, and thus controlling cost and quality of software. For controlling cost & quality, One of the key project objectives is to plan for optimum testing efforts, so that software produced is of high quality, and this has to be achieved by applying the right amount of testing efforts, if less testing efforts are applied quality of software suffers, and if more efforts are applied then cost of the software increases, so it becomes very important to strike a right balance between cost & quality of software and thus needed to arrive at optimum amount of testing, which becomes a major challenge for managers as it requires a good prediction model to predict the right amount of testing. It is proven that the software testing phase is one of the most critical and important phases in the software development life cycle. In general, the software-testing phase takes around 40-65% of the effort, time and cost. This area has been well researched over a long period of time. Unfortunately, while many researchers have found methods of reducing time and cost of the testing phase, there are still a number of important related issues that need to be researched. This study introduces a new prediction model for estimating number of required test cases and thereby maintaining the right balance between quality & cost, using empirical approach which establishes a relationship between software size & testing efforts using the defect data, productivities for various technologies can also be used for making the testing efforts technology specific for various projects. Predicting optimum number of required test cases or steps and thus total efforts required for testing and thereby controlling overall cost of quality.