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Test Design and Review Argumentation in AI-Assisted Test Generation

Authors:

Eduard Paul Enoiu, Robert Feldt

Research groups:

Software Testing Laboratory
Formal Modelling and Analysis of Embedded Systems

Publication Type:

Conference/Workshop Paper

Venue:

The 10th International Workshop on Testing Extra-Functional Properties and Quality Characteristics of Software Systems

Abstract

AI assistants can increasingly generate and evolve test cases. The challenge is no longer merely to produce them, but also to help engineers understand why a generated artefact exists and what supports it. Existing work has focused on classifying testing techniques, linking requirements to tests and structuring system assurance arguments, but it does not explicitly represent the argumentation behind individual test design decisions. We propose a conceptual taxonomy and a structured template for AI-assisted test generation that characterizes a test case by its test goal, claim, reason, and evidence. The taxonomy is intended for both constructive use during test design and retrospective use during review, to assess the quality of the attached argument rather than the plausibility or objective value of the generated test cases.

Bibtex

@inproceedings{Enoiu7368,
author = {Eduard Paul Enoiu and Robert Feldt},
title = {Test Design and Review Argumentation in AI-Assisted Test Generation},
month = {May},
year = {2026},
booktitle = {The 10th International Workshop on Testing Extra-Functional Properties and Quality Characteristics of Software Systems},
url = {http://www.es.mdu.se/publications/7368-}
}