Estimating Return on Investment for GUI Test Automation Frameworks

Abstract

Automated graphical user interface (GUI) tests can reduce manual testing activities and increase test frequency. This motivates the conversion of manual test cases into automated GUI tests. However, it is not clear whether such automation is cost-effective given that GUI automation scripts add to the code base and demand maintenance as a system evolves. In this paper, we introduce a method for estimating maintenance cost and Return on Investment (ROI) for Automated GUI Testing (AGT). The method utilizes the existing source code change history and has the potential to be used for the evaluation of other testing or quality assurance automation technologies. We evaluate the method for a real-world, industrial software system and compare two fundamentally different AGT frameworks, namely Selenium and EyeAutomate, to estimate and compare their ROI. We also report on their defect-finding capabilities and usability. The quantitative data is complemented by interviews with employees at the company the study has been conducted at. The method was successfully applied, and estimated maintenance cost and ROI for both frameworks are reported. Overall, the study supports earlier results showing that implementation time is the leading cost for introducing AGT. The findings further suggest that, while EyeAutomate tests are significantly faster to implement, Selenium tests require more of a programming background but less maintenance.