Project description
Teaching computers to debug software
An error, flaw, failure or fault in a computer program or system that causes it to produce an incorrect or unexpected result is called a software bug. Bug detection is the process of finding these bugs, and it usually involves formal techniques and tools that search for instances of bug patterns that recur across projects and application domains. The EU-funded LearnBugs project is seeking to radically change how automated bug detection tools are created. It will replace manually written programs with trained machine learning models. This will transform how software developers find bugs. The project will increase the reliability, security, and efficiency of complex software systems used by millions of people.
Objective
"Learning to Find Software Bugs
Software has become the cornerstone of modern society, economy, and life. Since software is created by humans, though, every non-trivial program contains various bugs, i.e. programming errors that may have disastrous consequences. Traditional approaches to find bugs include automated bug detection tools. Such tools search for instances of bug patterns that recur across projects and application domains. However, automated bug detection currently cannot unleash its full potential because each bug detector addresses one bug pattern and one programming language, while creating new bug detectors is feasible only for program analysis experts.
The objective of this proposal is to radically change the way automated bug detection tools are created. The core idea is to replace manually written program analyses with trained machine learning models. To this end, developers will train a bug detector for a particular bug pattern with examples of buggy and non-buggy code, which the model learns to distinguish. The project will realize this vision by developing a reusable framework that addresses several fundamental challenges at the intersection of software engineering, programming languages, and machine learning, e.g.: (i) How to support developers in creating large amounts of training data of buggy and non-buggy code examples? (ii) How to represent programs in a way suitable for advanced machine learning techniques?
The proposed project has the potential to revolutionize how software developers find bugs. To date, no other research has addressed the problem of automatically learning bug detection tools. If successful, the project will ""democratize"" bug detection by enabling all software developers, instead of a few program analysis experts, to create and share bug detection tools. Ultimately, the project will contribute to increasing the reliability, security, and efficiency of complex software systems used by millions of people."
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.
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.
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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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H2020-EU.1.1. - EXCELLENT SCIENCE - European Research Council (ERC)
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.
ERC-STG - Starting Grant
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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) ERC-2019-STG
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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.
70174 Stuttgart
Germany
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.