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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM67868
Volume:
10 |
10 |
Oct 2026
Pages:
1-11
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

Computer Science
The Robert Gordon University
Large Language Models (LLMs) are increasingly used to generate software tests, yet generated tests are probabilistic artifacts whose validity, relevance, and execution behavior must be verified independently. This paper presents the protocol for QUALTAN, a governed agentic architecture that separates LLM-based reasoning from deterministic test execution. QUALTAN combines specification-driven test intent, canonical test artifacts, policy checks before execution, execution-grounded validation, risk-aware test selection, and intent-preserving autonomous repair. We pre-specify six research questions, six hypotheses with falsification criteria, a four-condition controlled experiment (traditional automation, LLM-only generation, LLM generation with execution feedback, and the full architecture), a six-component ablation study, and a statistical analysis plan with predefined primary outcomes. The study uses open-source and synthetic applications with seeded defects and a public benchmark, and reports paired comparisons with corrected significance tests and effect sizes. Because the protocol is fixed before data collection, the claims it tests can be supported, refined, or rejected by the results. The paper therefore contributes a falsifiable experimental design for studying how governance and execution feedback affect the quality of LLM-generated test evidence.
KEYWORDS
This paper presents a protocol for a controlled study of governed, execution-grounded agentic testing. Its central proposition is that LLM reasoning becomes more useful for software quality when it is constrained by specifications, canonical artifacts, deterministic execution, evidence collection, and intent-preserving repair. The protocol pre-specifies the research questions, hypotheses, conditions, metrics, statistical tests, and falsification criteria under which that proposition will be judged. The results of the study will determine whether the proposition holds.
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Publication Date
10/12/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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The authors declare no conflict of interest related to this research work.
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