Estimation model for software testing

Abstract

Testing of software applications and assurance of compliance have become an essential part of Information Technology (IT) governance of organizations. Over the years, software testing has evolved into a specialization with its own practices and body of knowledge. Test estimation consists of the estimation of effort and working out the cost for a particular level of testing, using various methods, tools, and techniques. An incorrect estimation often leads to inadequate amount of testing which, in turn, can lead to failures of software systems when they are deployed in organizations. This research work has first established the state of the art of software test estimation, followed by the proposal of a Unified Framework for Software Test Estimation. Using this framework, a number of detailed estimation models have been designed next for functional testing. The ISBSG database has been used to investigate the estimation of software testing. The analysis of the ISBSG data has revealed three test productivity patterns representing economies and diseconomies of scale, based on which the characteristics of the corresponding projects were investigated. The three project groups related to the three productivity patterns were found to be statistically significant, and characterised by application domain, team size, elapsed time, and rigour of verification and validation throughout development. Within each project group, the variations in test efforts could be explained by the activities carried out during the development and processes adopted for testing, in addition to functional size. Two new independent variables, the quality of the development processes (DevQ) and the quality of testing processes (TestQ), were identified as influential in the estimation models. Portfolios of estimation models were built for different data sets using combinations of the three independent variables. At estimation time, an estimator could choose the project group by mapping the characteristics of the project to be estimated to the attributes of the project group, in order to choose the model closest to it. The quality of each model has been evaluated using established criteria such as R2, Adj R2, MRE, MedMRE and Maslow’s Cp. Models have been compared using their predictive performance, adopting new criteria proposed in this research work. Test estimation models using functional size measured in COSMIC Function Points have exhibited better quality and resulted in more accurate estimation, compared to functional size measured in IFPUG Function Points. A prototype software is now developed using statistical “R” programming language, incorporating portfolios of estimation models. This test estimation tool can be used by industry and academia for estimating test efforts.

Date	19 Jul 2016
Original language	American English
Awarding Institution	École de technologie supérieure
Supervisor	Alain Abran (Supervisor)