ISTQB Certifications Under the Lens: Their Contributions to the Software-Testing Profession; and AI-assisted Synthesis of Practitioners' Endorsements and Criticisms
Vehid Geruslu, Alper Bu\u{g}ra Kele\c{s}, Sevde De\u{g}irmenci, Zafar Jafarov, Aytan M\"ovs\"umova, Atif Namazov

TL;DR
This study evaluates the perceived value and criticisms of ISTQB certifications in software testing, using AI-assisted literature review and expert validation to provide an evidence-based assessment of their practical impact and relevance.
Contribution
It introduces an AI-assisted multivocal literature review methodology to systematically analyze practitioner perspectives and expert opinions on ISTQB certifications.
Findings
Endorsements highlight career benefits and improved communication.
Criticisms cite excessive theoretical content and limited relevance.
Expert review confirms some endorsements are precise, criticisms reflect broader discipline tensions.
Abstract
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…
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Taxonomy
TopicsSoftware Engineering Techniques and Practices · Artificial Intelligence in Healthcare and Education · Software Engineering Research
