Estimating Return on Investment for GUI Test Automation Tools
This work addresses the practical challenge for software developers and testers in deciding whether to automate GUI tests, though it is incremental as it builds on existing ROI estimation methods.
The authors tackled the problem of estimating the cost-effectiveness of automated GUI testing tools by introducing a method to calculate maintenance cost and ROI, applying it to Selenium and EyeAutomate in an industrial case study. They found that EyeAutomate tests are faster to implement but Selenium tests require less maintenance, with implementation time being the leading cost.
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 can be used for evaluation also 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 tools, 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 case company. The method was successfully applied and estimated maintenance cost and ROI for both tools 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.