Observability and Fault Injection for LLM-Based Multi-Agent Systems in Software Engineering

Conference Paper (2026)
Author(s)

Zahra Seyedghorban (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Egor Klimov (TU Delft - Electrical Engineering, Mathematics and Computer Science, JetBrains Research)

Arie Van Deursen (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Annibale Panichella (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Burcu Kulahcioglu Ozkan (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Research Group
Software Engineering
DOI related publication
https://doi.org/10.1109/ICST69053.2026.00037 Final published version
More Info
expand_more
Publication Year
2026
Language
English
Research Group
Software Engineering
Pages (from-to)
211-215
Publisher
IEEE
ISBN (electronic)
9798319533081
Event
19th IEEE International Conference on Software Testing, Verification and Validation, ICST 2026 (2026-05-18 - 2026-05-22), Daejeon, South Korea
Page Views
158
Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Abstract

Large Language Model-based multi-agent systems are increasingly explored for software engineering tasks, but they remain difficult to inspect, debug, and evaluate under controlled failures. We present llmmas-otel, a lightweight and framework-agnostic tool that combines OpenTelemetrybased distributed tracing with fault injection for LLM-based multi-agent systems in software engineering workflows. The tool instruments agent executions with trace-aligned telemetry across workflow phases, agent steps, inter-agent communication, tool calls, and LLM invocations, and supports targeted fault injection at selected interaction points. This makes it possible to compare baseline and faulty executions in a reproducible way and inspect the effects through aligned traces and run artifacts. We describe the motivation, architecture, implementation, current capabilities, and initial validation of the tool on a minimal demo workflow and a real LLM-based multi-agent system for software development. A screencast is available at: {https://youtu.be/tyQh2xO-flo}.

Files

– Personal use only – Dutch Copyright Act (Article 25fa)
warning

File under embargo until 18-01-2027