Alper Buğra Keleş

Vahid Garousi, Alper Buğra Keleş, Yunus Balaman et al.

In the context of a large software testing company, we have deployed the model-based testing (MBT) approach to take the company's test automation practices to higher levels of maturity /and capability. We have chosen, from a set of open-source/commercial MBT tools, an open-source tool named GraphWalker, and have pragmatically used MBT for end-to-end test automation of several large web and mobile applications under test. The MBT approach has provided, so far in our project, various tangible and intangible benefits in terms of improved test coverage (number of paths tested), improved test-design practices, and also improved real-fault detection effectiveness. The goal of this experience report (applied research report), done based on "action research", is to share our experience of applying and evaluating MBT as a software technology (technique and tool) in a real industrial setting. We aim at contributing to the body of empirical evidence in industrial application of MBT by sharing our industry-academia project on applying MBT in practice, the insights that we have gained, and the challenges and questions that we have faced and tackled so far. We discuss an overview of the industrial setting, provide motivation, explain the events leading to the outcomes, discuss the challenges faced, summarize the outcomes, and conclude with lessons learned, take-away messages, and practical advices based on the described experience. By learning from the best practices in this paper, other test engineers could conduct more mature MBT in their test projects.

Vehid Geruslu, Alper Buğra Keleş, Sevde Değirmenci et al.

Objective: This study investigates the perceived value and critique of ISTQB certifications, the most widely recognized testing qualifications worldwide. While the certifications aim to standardize the software testing body of knowledge, debates persist about their practical relevance and impact. Our objective was to systematically capture practitioner perspectives and assess the precision of endorsements and fairness of criticisms through expert review. Method: We conducted an AI-assisted Multivocal Literature Review (MLR), combining academic and grey literature to synthesize practitioner endorsements (RQ1) and criticisms (RQ2). ChatGPT's deep research capability was employed under continuous human oversight, with QA strategies ensuring transparency and reliability. As another analysis, we asked a panel of four independent experts to evaluate the precision of endorsements and fairness of criticisms. Results: Practitioner endorsements emphasized career benefits, improved communication, and a shared vocabulary as the main values of ISTQB certifications. Criticisms focused on excessive theoretical content, limited relevance in agile and automation-intensive contexts, and weak support for real testing skills. Expert review confirmed that while many endorsements were precise, several criticisms reflected broader tensions in the discipline, including contrasting schools of thought in testing practice. Conclusions: ISTQB certifications provide recognizable career and communication value but remain contested in terms of practical utility. By triangulating practitioner voices with expert validation, this study delivers an evidence-based reflection on the strengths and weaknesses of ISTQB in shaping the software testing body of knowledge. The AI-assisted MLR also demonstrates how GenAI tools can support systematic evidence synthesis when coupled with rigorous human oversight.