ProDebug: An Automated Debugging System for Prolog

Fuente: arXiv
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Main Authors: Brancas, Ricardo, Manquinho, Vasco, Martins, Ruben
Format: Preprint
Published: 2026
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author Brancas, Ricardo
Manquinho, Vasco
Martins, Ruben
author_facet Brancas, Ricardo
Manquinho, Vasco
Martins, Ruben
contents Prolog is a well-known declarative programming language commonly used in introductory courses on logic and reasoning. However, many students find Prolog challenging because it lacks the familiar debugging mechanisms found in imperative languages. In large classes, this difficulty is exacerbated by the challenge of providing timely and personalized feedback to students. In this work, we introduce ProDebug, the first tool to combine Large Language Models (LLMs) with spectrum-based and mutation-based techniques for automated debugging of Prolog assignments. ProDebug automatically identifies faults and proposes bug repairs for student Git submissions. Faults are detected using three approaches--spectrum-based, mutation-based, and LLM reasoning--while repairs are generated using mutation-based techniques and LLMs. Our evaluation on 1499 buggy student submissions from a bachelor's level programming class demonstrates the potential of automated, LLM-augmented feedback systems to scale support for declarative programming education.
format Preprint
id arxiv_https___arxiv_org_abs_2605_27124
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle ProDebug: An Automated Debugging System for Prolog
Brancas, Ricardo
Manquinho, Vasco
Martins, Ruben
Programming Languages
Software Engineering
Prolog is a well-known declarative programming language commonly used in introductory courses on logic and reasoning. However, many students find Prolog challenging because it lacks the familiar debugging mechanisms found in imperative languages. In large classes, this difficulty is exacerbated by the challenge of providing timely and personalized feedback to students. In this work, we introduce ProDebug, the first tool to combine Large Language Models (LLMs) with spectrum-based and mutation-based techniques for automated debugging of Prolog assignments. ProDebug automatically identifies faults and proposes bug repairs for student Git submissions. Faults are detected using three approaches--spectrum-based, mutation-based, and LLM reasoning--while repairs are generated using mutation-based techniques and LLMs. Our evaluation on 1499 buggy student submissions from a bachelor's level programming class demonstrates the potential of automated, LLM-augmented feedback systems to scale support for declarative programming education.
title ProDebug: An Automated Debugging System for Prolog
topic Programming Languages
Software Engineering
url https://arxiv.org/abs/2605.27124