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Browsing by Subject "Test Automation"

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  • Heikkinen, Juuso (2021)
    Telecommunication companies are moving towards even more digitalized and agile ways of working. They are expanding their business in other fields, such as television, thus moving further away from the traditional telecommunications model. Recently, Telia has become the largest television company in the Nordics. One of the their main products in the field of television is channel packages, which allow customers to access specific television content. In this study, a benefit analysis for Telia Finland Oyj was conducted to inspect the benefits that test automation brings for the channel package testing process. 8 interviews in total were conducted with Telia employees with knowledge on channel packages. To receive both a business and a technical perspective, the interviewees were divided into two groups fitting their expertise. In general, test automation was seen as a useful tool. The main business related benefits of test automation mentioned were a faster and cheaper testing process, and a faster time-to-market. It was also seen that test automation could help achieve a more efficient testing process, and increase confidence in test automation. Based on the interview results, an epic was defined and analyzed according to the principles of Scaled Agile Framework (SAFe). This included describing the solution in detail and defining a Minimum Viable Product (MVP). By using example variables and generalized values, several calculations were made to present a framework on the costs of implementing the MVP and the estimated reduction of channel package testing costs. By utilizing the MVP as a part of the channel package testing process, the return on investment (ROI) was not as desirable as expected. With more automated tests compared to the number of test cases, combined with regular use of test automation, the investment would pay itself back and start generating additional savings faster. Based on the epic analysis, a Lean Business Case was defined.
  • Rohamo, Paavo (2024)
    The fast development cycles of Web User Interfaces (UI) create challenges for test automation to keep up with the changes in web elements. Test automation may suffer from test breakages after developers update the UIs of the System Under Test (SUT). Test breakages are not defects or bugs in the SUT, but a failure in test automation code. Failing to correctly locate web element from the UI, is one of the key reasons for test breakages to occur. Prior work to gain self-healing of element locators, has been traditionally done with different algorithms and recently with the help of Large Language Models (LLMs). This thesis aims to discover how to enable self-healing locators for Robot Framework Web UI tests, are there some web element locator types that are more easily repaired than others, and which LLMs should be used for this task. An experimental study was conducted for enabling self-healing locators for Robot Framework. Custom Robot Framework library was created with Python, which was tested for eight different locator strategies raised from locator breakage taxonomy. Results show that the best performance in self-healing locators is gained by using the bigger LLMs. GPT-4 Turbo and Mistral Large showed the best performance accuracy by repairing 87,5% of the locators in the Robot Framework test cases. The worst performer was Mistral 7B Instruct which was not able to correct any locators. Using LLMs for self-healing locators in Robot Framework tests is possible. To get the best results for self-healing locators, my results suggest that practitioners should focus on LLM prompt designing, in the usage of candidate algorithm with locator version history and use the biggest LLMs available if possible.