We are thrilled to announce that Laura Kovács, who is Professor and Head of the Research Unit Formal Methods in Systems Engineering, as well as Research Focus Coordinator for Logic and Computation, has received an ERC Proof of Concept grant for her project Learning Efficient Automated Reasoning on the Net (LEARN)! The ERC Proof of Concept grant is endowed with 150,000 Euros and is set to run for up to 18 months.

LEARN investigates how rigorous code reviews can help discover errors in software logic to prevent incidents like the CrowdStrike IT outage in the Summer of 2024. This mass outage was triggered by a logic flaw in a software update, affecting millions of users and companies around the world. The damage caused by this uncertified update is now estimated to be over 5 billion Euros; something that could have been prevented by rigorous code reviews. Certified computer systems are becoming more and more essential in our everyday lives, because they ensure the accuracy and security in complex decision-making systems like Artificial Intelligence (AI), Autonomous Systems, Big Data, Blockchains, Decentralized Finance (DeFi), Cloud Computing, or Machine Learning (ML). However, many systems are uncertified and prone to errors, which can lead to serious issues, as the Crowdstrike incident shows.

“Nowadays, we rely on computer systems in our daily lives despite the fact that we do not trust computers: There are too many real-world examples showcasing that computer systems do have errors. Research in Automated Reasoning has, therefore, boomed in the past years, and domain-specific solutions have been developed to find certain software errors and/or certify software systems. Understanding and applying automated reasoning techniques is, however, hard and requires highly qualified researchers with solid expertise in logic, math, and software engineering. Such combined expertise is rarely met in the everyday landscape of software development.”, says Laura Kovács.

LEARN addresses a critical gap in the software development process by making certification more accessible and by automating error prevention. The approach that LEARN takes improves the reliability of digital systems by offering a simple, web-based platform that helps developers ensure their software is safe and reliable. It automates the process of checking software logic, finding proof strategies, and preventing errors, and this is wehere LEARN will help, as Laura Kovács explains:

“We will make automated reasoning accessible to non-experts, using an interactive interface with a minimal barrier of entry to use. LEARN will provide learning and practice material for reasoning-based software certification, in particular using our Vampire theorem prover. The LEARN benefits range from helping students in introductory computer science courses to understand the basics of theorem proving capabilities to assisting researchers and professionals with an entry point to understand the utility of reasoning features and applying more advanced proving techniques on demand. Developing a proper online learning system requires a deliberate investment of resources, which is why I am excited by this project.”

About Laura Kovács

Laura Kovács is Professor and Head of the Research Unit Formal Methods in Systems Engineering at TU Wien Informatics, where she leads the Automated Program Reasoning (APRe) group. Her research focuses on the design and development of new theories, technologies, and tools for program analysis, with a particular focus on automated assertion generation, symbolic summation, computer algebra, and automated theorem proving.

She is the co-developer of the Vampire theorem prover and a Wallenberg Academy Fellow of Sweden. Her research has been awarded with an ERC Starting Grant (2014), an ERC Proof of Concept Grant (2018), an ERC Consolidator Grant (2020), and two Amazon Research Awards (2020 and 2023). She receives financial support from LEA (Let’s empower Austria) to promote and organize unplugged computer science workshops for elementary school children as part of TU Wien’s eduLAB.

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