Project description
The logic of bug hunting
Debugging is often the most expensive and time-consuming phase of software development. However, reliable automated tools for Python remain scarce. Supported by the Marie Skłodowska-Curie Actions programme, the Sherlock4Py project is building a new framework for detecting and localising faults in Python code. By adapting techniques originally designed for C, the project uses bounded model checking and scalable MaxSAT algorithms to navigate Python’s structure. Additionally, the project aims to integrate symbolic reasoning with large language models through inductive synthesis loops. This approach seeks to improve the accuracy of bug detection, paving the way for more reliable automated program repair in the vital fields of AI and data science.
Objective
Debugging remains one of the most costly and time-consuming phases of software development. Formula-based fault localisation (FBFL), which leverages bounded model checking and logical reasoning through Maximum Satisfiability (MaxSAT), to identify faulty program statements, has shown strong potential for languages such as C, but remains under-explored for Python, which is the dominant language in artificial intelligence, data science, and education.
The aim of this project is to design and implement Sherlock4Py, a MaxSAT-based misbehaviour verification and localisation framework for Python. First, Sherlock4Py will implement FBFL to Python by incorporating bounded model checking with ESBMC-Python, and will develop scalable MaxSAT algorithms tailored to program-derived formulas. These algorithms will exploit structural features of Python, such as loop iterations and branching constructs, to achieve greater scalability and more precise diagnoses than existing approaches. Second, Sherlock4Py will demonstrate the synergy between FBFL and Large Language Models (LLMs) by embedding MaxSAT-based bug localisation into counterexample-guided inductive synthesis (CEGIS) loops, thereby enabling LLMs to synthesise and repair faulty Python programs more reliably, with greater accuracy and efficiency.
By bridging Automated Reasoning and Machine Learning, Sherlock4Py will advance the state of the art in both MaxSAT-based fault localisation and trustworthy AI. The project is ambitious in delivering the first MaxSAT-based toolchain for Python, advancing MaxSAT algorithms with program-specific heuristics, and integrating symbolic verification with LLM-driven code synthesis. The expected outcome is a step change in software reliability, with direct benefits for AI research, software engineering practice, and computer science education.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
This project's classification has been human-validated.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
This project's classification has been human-validated.
- natural sciences computer and information sciences data science
- natural sciences computer and information sciences software software development
- natural sciences computer and information sciences artificial intelligence machine learning
- natural sciences computer and information sciences artificial intelligence heuristic programming
Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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HORIZON.1.2 - Marie Skłodowska-Curie Actions (MSCA)
MAIN PROGRAMME
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Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
HORIZON-TMA-MSCA-PF-EF - HORIZON TMA MSCA Postdoctoral Fellowships - European Fellowships
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) HORIZON-MSCA-2025-PF
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
28006 Madrid
Spain
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.