Earl T. Barr

Earl T. Barr is a Professor of Software Engineering at University College London (UCL), where he heads the System Software Engineering Group and is a member of the Centre for Research on Evolution, Search and Testing (CREST). His academic journey began with a Ph.D. in Computer Science from the University of California, Davis in 2009, after which he joined UCL as faculty.

His research spans multiple domains within software engineering, with particular focus on program analysis, type systems, automated program repair, and the emerging field of dual channel analysis that examines the interplay between natural language and formal programming language in source code. Barr's work on the 'naturalness of software' has been influential in understanding how code differs from natural language while exhibiting statistical regularities.

Barr's publication record shows a strong trend toward integrating machine learning with traditional software engineering techniques, particularly in type inference (Typilus), program repair, and code understanding. His recent work increasingly focuses on dual channel analysis, exploring how the natural language elements in code (identifiers, comments) interact with the formal programming language to create a richer communication channel for developers.

• MSR 2019 Most Influential Paper Award
• Multiple ACM SIGSOFT Distinguished Paper Awards
• Best Paper Award at IEEE Conference on E-Commerce Technology (2005)

Barr actively supervises numerous Ph.D. students and postdocs, with current projects focusing on dual channel program analysis, AI for code, and software security applications. He has established long-term collaborations with researchers at institutions including Royal Holloway and the University of Luxembourg. His teaching portfolio at UCL includes core courses in Malware, Compilers, and Validation and Verification, reflecting his broad expertise across the software engineering spectrum.

Barr leads the System Software Engineering Group at UCL, which focuses on practical applications of software engineering research with strong connections to industry problems. The group's work bridges theoretical foundations with real-world software development challenges, particularly in the areas of program analysis and automated software maintenance.