SIGMMA: Skill-Based Multi-Agent Generation of Test Cases from Multimodal User Manuals

SIGMMA generates test cases from use cases in two phases. Phase 1 extracts use cases page by page from a PDF user manual with a vision-language model. Phase 2 generates one test case per use case and refines it in a loop between a generator agent and a validator agent until the test case satisfies four criteria: completeness, atomicity, clarity, and traceability. The domain rules of each agent are packaged as SKILL.md files following the Agent Skills standard.

Authors

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-10-06
DOI
https://doi.org/10.5281/zenodo.23187390
Primary Topic
Software Testing and Debugging Techniques
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

SIGMMA: Skill-Based Multi-Agent Generation of Test Cases from Multimodal User Manuals

Soares Yan, Hallyson Melo, Andrés D. Peralta, André Carvalho et al.
Zenodo (CERN European Organization for Nuclear Research)
Software Testing and Debugging Techniques
article

SIGMMA: Skill-Based Multi-Agent Generation of Test Cases from Multimodal User Manuals

Soares Yan, Hallyson Melo, Andrés D. Peralta, André Carvalho, Bruno Gadelha, Carvalho Gabriel, Lima Igor, Ferreira Nikson
article en

Abstract

SIGMMA generates test cases from use cases in two phases. Phase 1 extracts use cases page by page from a PDF user manual with a vision-language model. Phase 2 generates one test case per use case and refines it in a loop between a generator agent and a validator agent until the test case satisfies four criteria: completeness, atomicity, clarity, and traceability. The domain rules of each agent are packaged as SKILL.md files following the Agent Skills standard.

Zenodo (CERN European Organization for Nuclear Research)
Universidade Federal do Amazonas (BR)
Openalex Percentile: Top 3%
Software Testing and Debugging Techniques
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.