SEFeb 3, 2016

Maintenance of Automated Test Suites in Industry: An Empirical study on Visual GUI Testing

arXiv:1602.01226v172 citations
Originality Synthesis-oriented
AI Analysis

It addresses the lack of empirical data on maintenance costs for automated GUI testing in industrial practice, which is incremental as it builds on previous work with a cost model.

This paper investigates the maintenance costs and influencing factors of automated GUI-based testing in industry, finding that developing new test scripts is costlier than maintenance, and frequent maintenance is less costly than infrequent, big bang maintenance.

Context: Verification and validation (V&V) activities make up 20 to 50 percent of the total development costs of a software system in practice. Test automation is proposed to lower these V&V costs but available research only provides limited empirical data from industrial practice about the maintenance costs of automated tests and what factors affect these costs. In particular, these costs and factors are unknown for automated GUI-based testing. Objective: This paper addresses this lack of knowledge through analysis of the costs and factors associated with the maintenance of automated GUI-based tests in industrial practice. Method: An empirical study at two companies, Siemens and Saab, is reported where interviews about, and empirical work with, Visual GUI Testing is performed to acquire data about the technique's maintenance costs and feasibility. Results: 13 factors are observed that affect maintenance, e.g. tester knowledge/experience and test case complexity. Further, statistical analysis shows that developing new test scripts is costlier than maintenance but also that frequent maintenance is less costly than infrequent, big bang maintenance. In addition a cost model, based on previous work, is presented that estimates the time to positive return on investment (ROI) of test automation compared to manual testing. Conclusions: It is concluded that test automation can lower overall software development costs of a project whilst also having positive effects on software quality. However, maintenance costs can still be considerable and the less time a company currently spends on manual testing, the more time is required before positive, economic, ROI is reached after automation.

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