aceAI-Driven Software Testing for a Test Center of Excellence: A Systematic Mapping and Evidence Synthesis
Artificial intelligence (AI) is increasingly used to automate and optimize software testing, but the evidence is distributed across heterogeneous testing activities, AI techniques, and evaluation measures. This study maps AI-driven software-testing research and translates the evidence into capabilities relevant to a Test Center of Excellence (TCoE). A systematic evidence workflow was applied to a unified audit corpus of 2,072 records, followed by focused eligibility reconciliation and full-text verification. The…
The evidence synthesis links AI techniques to testing activities, measurable outcomes and reusable capabilities, giving test centers a governed capability model rather than a single automation tool.
The source identifies unresolved gaps in reliability, context awareness, test-oracle support, long-term maintenance, CI/CD integration, reproducibility and standardized evaluation.
Evidence
- Peer-reviewedJURNAL TEKNIK INFORMATIKA2026-10-20
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Truvace Impact Record TRV-2026-2012, v1: “AI-Driven Software Testing for a Test Center of Excellence: A Systematic Mapping and Evidence Synthesis.” Truvace, 2026-10-20. /record/TRV-2026-2012 (accessed at citation time). sha256 fcd45af109ec2964…
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