Earl T. Barr

Earl T. Barr

University College London

H-index: 34

Europe-United Kingdom

About Earl T. Barr

Earl T. Barr, With an exceptional h-index of 34 and a recent h-index of 29 (since 2020), a distinguished researcher at University College London, specializes in the field of software engineering, computer security, programming languages.

His recent articles reflect a diverse array of research interests and contributions to the field:

The Fact Selection Problem in LLM-Based Program Repair

A Comprehensive Study of the Capabilities of Large Language Models for Vulnerability Detection

Aide-mémoire: Improving a Project’s Collective Memory via Pull Request–Issue Links

Program transformation landscapes for automated program modification using Gin

Precise Data-Driven Approximation for Program Analysis via Fuzzing

Model validation using mutated training labels: an exploratory study

Epicure: Distilling Sequence Model Predictions into Patterns

Rete: Learning namespace representation for program repair

Earl T. Barr Information

University

Position

Professor

Citations(all)

8606

Citations(since 2020)

5534

Cited By

5211

hIndex(all)

34

hIndex(since 2020)

29

i10Index(all)

62

i10Index(since 2020)

50

Email

University Profile Page

University College London

Google Scholar

View Google Scholar Profile

Earl T. Barr Skills & Research Interests

software engineering

computer security

programming languages

Top articles of Earl T. Barr

Title

Journal

Author(s)

Publication Date

The Fact Selection Problem in LLM-Based Program Repair

arXiv preprint arXiv:2404.05520

Nikhil Parasaram

Huijie Yan

Boyu Yang

Zineb Flahy

Abriele Qudsi

...

2024/4/8

A Comprehensive Study of the Capabilities of Large Language Models for Vulnerability Detection

arXiv preprint arXiv:2403.17218

Benjamin Steenhoek

Md Mahbubur Rahman

Monoshi Kumar Roy

Mirza Sanjida Alam

Earl T Barr

...

2024/3/25

Aide-mémoire: Improving a Project’s Collective Memory via Pull Request–Issue Links

ACM Transactions on Software Engineering and Methodology

Profir-Petru Pârțachi

David R. White

Earl T. Barr

2022/5

Program transformation landscapes for automated program modification using Gin

Empirical Software Engineering

Justyna Petke

Brad Alexander

Earl T Barr

Alexander EI Brownlee

Markus Wagner

...

2023/7

Precise Data-Driven Approximation for Program Analysis via Fuzzing

Nikhil Parasaram

Earl T Barr

Sergey Mechtaev

Marcel Böhme

2023/9/11

Model validation using mutated training labels: an exploratory study

Neurocomputing

Jie M Zhang

Mark Harman

Benjamin Guedj

Earl T Barr

John Shawe-Taylor

2023/6/28

Epicure: Distilling Sequence Model Predictions into Patterns

arXiv preprint arXiv:2308.08203

Miltiadis Allamanis

Earl T Barr

2023/8/16

Rete: Learning namespace representation for program repair

Nikhil Parasaram

Earl T Barr

Sergey Mechtaev

2023/5/14

Software Product Line Engineering via Software Transplantation

arXiv preprint arXiv:2307.10896

Leandro O Souza

Earl T Barr

Justyna Petke

Eduardo S Almeida

Paulo Anselmo Neto

2023/7/20

Continuously Accelerating Research

Earl Barr

Jonathan Bell

Michael Hilton

Sergey Mechtaev

Christopher Timperley

2023/5/14

CodeGrid: A Grid Representation of Code

Abdoul Kader Kaboré

Earl T Barr

Jacques Klein

Tegawendé F Bissyandé

2023/7/12

Improving few-shot prompts with relevant static analysis products

arXiv preprint arXiv:2304.06815

Toufique Ahmed

Kunal Suresh Pai

Premkumar Devanbu

Earl T Barr

2023/4/13

June: A Type Testability Transformation for Improved ATG Performance

Dan Bruce

David Kelly

Hector Menendez

Earl T Barr

David Clark

2023/7/12

Summary of the 1st Interpretability and Robustness in Neural Software Engineering (InteNSE 2023)

ACM SIGSOFT Software Engineering Notes

Reyhaneh Jabbarvand

Saeid Tizpaz-Niari

Earl T Barr

Satish Chandra

2023/12/27

Modus: a Datalog dialect for building container images

Chris Tomy

Tingmao Wang

Earl T Barr

Sergey Mechtaev

2022/11/7

PopArt: Ranked Testing Efficiency

IEEE Transactions on Software Engineering

Iason Papapanagiotakis Bousy

Earl T Barr

David Clark

2022/10/17

Is Surprisal in Issue Trackers Actionable?

arXiv preprint arXiv:2204.07363

James Caddy

Markus Wagner

Christoph Treude

Earl T Barr

Miltiadis Allamanis

2022/4/15

High assurance software for financial regulation and business platforms

Stephen Goldbaum

Attila Mihaly

Tosha Ellison

Earl T Barr

Mark Marron

2022/1/14

Trident: Controlling side effects in automated program repair

IEEE Transactions on Software Engineering

Nikhil Parasaram

Earl T Barr

Sergey Mechtaev

2021/11/11

Type inference as optimization

Eirene V Pandi

Earl T Barr

Andrew D Gordon

Charles Sutton

2021/10/22

See List of Professors in Earl T. Barr University(University College London)

Co-Authors

H-index: 102
Mark Harman

Mark Harman

University College London

H-index: 66
Prem  Devanbu

Prem Devanbu

University of California, Davis

H-index: 45
Abram Hindle

Abram Hindle

University of Alberta

H-index: 37
Federica Sarro

Federica Sarro

University College London

H-index: 27
Justyna Petke

Justyna Petke

University College London

H-index: 11
Santanu Dash

Santanu Dash

University of Surrey

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