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Earl T. Barr
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2020 – today
- 2024
- [j20]Reyhaneh Jabbarvand, Saeid Tizpaz-Niari, Earl T. Barr, Satish Chandra:
Summary of the 1st Interpretability and Robustness in Neural Software Engineering (InteNSE 2023). ACM SIGSOFT Softw. Eng. Notes 49(1): 30-33 (2024) - [c56]Toufique Ahmed
, Kunal Suresh Pai
Automatic Semantic Augmentation of Language Model Prompts (for Code Summarization). ICSE 2024: 220:1-220:13 - [i24]Benjamin Steenhoek, Md Mahbubur Rahman, Monoshi Kumar Roy, Mirza Sanjida Alam, Earl T. Barr, Wei Le:
A Comprehensive Study of the Capabilities of Large Language Models for Vulnerability Detection. CoRR abs/2403.17218 (2024) - [i23]Nikhil Parasaram, Huijie Yan, Boyu Yang, Zineb Flahy, Abriele Qudsi, Damian Ziaber, Earl T. Barr, Sergey Mechtaev:
The Fact Selection Problem in LLM-Based Program Repair. CoRR abs/2404.05520 (2024) - 2023
- [j19]Justyna Petke
Program transformation landscapes for automated program modification using Gin. Empir. Softw. Eng. 28(4): 104 (2023) - [j18]Jie M. Zhang, Mark Harman, Benjamin Guedj
Model validation using mutated training labels: An exploratory study. Neurocomputing 539: 126116 (2023) - [j17]Profir-Petru Pârtachi
Aide-mémoire: Improving a Project's Collective Memory via Pull Request-Issue Links. ACM Trans. Softw. Eng. Methodol. 32(2): 32:1-32:36 (2023) - [j16]Iason Papapanagiotakis-Bousy
PopArt: Ranked Testing Efficiency. IEEE Trans. Software Eng. 49(4): 2221-2238 (2023) - [c55]Earl T. Barr, Jonathan Bell, Michael Hilton, Sergey Mechtaev, Christopher Steven Timperley:
Continuously Accelerating Research. ICSE (NIER) 2023: 123-128 - [c54]Nikhil Parasaram, Earl T. Barr, Sergey Mechtaev:
Rete: Learning Namespace Representation for Program Repair. ICSE 2023: 1264-1276 - [c53]Dan Bruce, David A. Kelly, Héctor D. Menéndez, Earl T. Barr, David Clark
June: A Type Testability Transformation for Improved ATG Performance. ISSTA 2023: 274-284 - [c52]Abdoul Kader Kaboré, Earl T. Barr, Jacques Klein, Tegawendé F. Bissyandé:
CodeGrid: A Grid Representation of Code. ISSTA 2023: 1357-1369 - [c51]Nikhil Parasaram, Earl T. Barr, Sergey Mechtaev, Marcel Böhme:
Precise Data-Driven Approximation for Program Analysis via Fuzzing. ASE 2023: 611-623 - [i22]Toufique Ahmed, Kunal Suresh Pai, Premkumar T. Devanbu, Earl T. Barr:
Improving Few-Shot Prompts with Relevant Static Analysis Products. CoRR abs/2304.06815 (2023) - [i21]Leandro O. Souza, Earl T. Barr, Justyna Petke, Eduardo Santana de Almeida, Paulo Anselmo da Mota Silveira Neto:
Software Product Line Engineering via Software Transplantation. CoRR abs/2307.10896 (2023) - [i20]Miltiadis Allamanis, Earl T. Barr:
Epicure: Distilling Sequence Model Predictions into Patterns. CoRR abs/2308.08203 (2023) - 2022
- [j15]Nikhil Parasaram, Earl T. Barr
Trident: Controlling Side Effects in Automated Program Repair. IEEE Trans. Software Eng. 48(12): 4717-4732 (2022) - [c50]Chris Tomy, Tingmao Wang, Earl T. Barr, Sergey Mechtaev:
Modus: a Datalog dialect for building container images. ESEC/SIGSOFT FSE 2022: 595-606 - [c49]Stephen Goldbaum, Attila Mihály, Tosha Ellison, Earl T. Barr, Mark Marron:
High Assurance Software for Financial Regulation and Business Platforms. VMCAI 2022: 108-126 - [i19]James Caddy, Markus Wagner, Christoph Treude
Is Surprisal in Issue Trackers Actionable? CoRR abs/2204.07363 (2022) - 2021
- [j14]Héctor D. Menéndez
Getting Ahead of the Arms Race: Hothousing the Coevolution of VirusTotal with a Packer. Entropy 23(4): 395 (2021) - [j13]André N. Meyer
Today Was a Good Day: The Daily Life of Software Developers. IEEE Trans. Software Eng. 47(5): 863-880 (2021) - [j12]Carlos Gavidia-Calderon
The Assessor's Dilemma: Improving Bug Repair via Empirical Game Theory. IEEE Trans. Software Eng. 47(10): 2143-2161 (2021) - [c48]Robert White, Jens Krinke, Earl T. Barr
Artefact Relation Graphs for Unit Test Reuse Recommendation. ICST 2021: 137-147 - 2020
- [j11]Nadia Alshahwan, Earl T. Barr, David Clark
Detecting Malware with Information Complexity. Entropy 22(5): 575 (2020) - [j10]Carlos Gavidia-Calderon
Game-theoretic analysis of development practices: Challenges and opportunities. J. Syst. Softw. 159 (2020) - [c47]Dan Bruce, Héctor D. Menéndez, Earl T. Barr
Ant Colony Optimization for Object-Oriented Unit Test Generation. ANTS Conference 2020: 29-41 - [c46]Annie Louis, Santanu Kumar Dash
Where should I comment my code?: a dataset and model for predicting locations that need comments. ICSE (NIER) 2020: 21-24 - [c45]Casey Casalnuovo, Earl T. Barr
A theory of dual channel constraints. ICSE (NIER) 2020: 25-28 - [c44]Profir-Petru Pârtachi
POSIT: simultaneously tagging natural and programming languages. ICSE 2020: 1348-1358 - [c43]Miltiadis Allamanis, Earl T. Barr
Typilus: neural type hints. PLDI 2020: 91-105 - [c42]Profir-Petru Pârtachi
Flexeme: untangling commits using lexical flows. ESEC/SIGSOFT FSE 2020: 63-74 - [i18]Irene Vlassi Pandi, Earl T. Barr, Andrew D. Gordon, Charles Sutton:
OptTyper: Probabilistic Type Inference by Optimising Logical and Natural Constraints. CoRR abs/2004.00348 (2020) - [i17]Miltiadis Allamanis, Earl T. Barr, Soline Ducousso, Zheng Gao:
Typilus: Neural Type Hints. CoRR abs/2004.10657 (2020)
2010 – 2019
- 2019
- [j9]Héctor D. Menéndez
The arms race: Adversarial search defeats entropy used to detect malware. Expert Syst. Appl. 118: 246-260 (2019) - [j8]Bobby R. Bruce
Approximate Oracles and Synergy in Software Energy Search Spaces. IEEE Trans. Software Eng. 45(11): 1150-1169 (2019) - [c41]Alexander E. I. Brownlee, Justyna Petke
Gin: genetic improvement research made easy. GECCO 2019: 985-993 - [c40]Justyna Petke
A survey of genetic improvement search spaces. GECCO (Companion) 2019: 1715-1721 - [c39]David Robert White, Benjamin Fowler, Wolfgang Banzhaf, Earl T. Barr
Modelling Genetic Programming as a Simple Sampling Algorithm. GPTP 2019: 367-381 - [i16]David A. Kelly, Mark Marron, David Clark, Earl T. Barr:
SafeStrings: Representing Strings as Structured Data. CoRR abs/1904.11254 (2019) - [i15]Jie M. Zhang
Perturbed Model Validation: A New Framework to Validate Model Relevance. CoRR abs/1905.10201 (2019) - [i14]Earl T. Barr, David W. Binkley, Mark Harman, Mohamed Nassim Seghir:
Sub-Turing Islands in the Wild. CoRR abs/1905.12734 (2019) - 2018
- [j7]Miltiadis Allamanis
A Survey of Machine Learning for Big Code and Naturalness. ACM Comput. Surv. 51(4): 81:1-81:37 (2018) - [j6]Miltiadis Allamanis
Mining Semantic Loop Idioms. IEEE Trans. Software Eng. 44(7): 651-668 (2018) - [c38]Kareem Khazem, Earl T. Barr
Making data-driven porting decisions with Tuscan. ISSTA 2018: 276-286 - [c37]Santanu Kumar Dash
RefiNym: using names to refine types. ESEC/SIGSOFT FSE 2018: 107-117 - [c36]Michail Basios, Lingbo Li, Fan Wu
Darwinian data structure selection. ESEC/SIGSOFT FSE 2018: 118-128 - [c35]Vincent J. Hellendoorn, Christian Bird, Earl T. Barr
Deep learning type inference. ESEC/SIGSOFT FSE 2018: 152-162 - [i13]Annie Louis, Santanu Kumar Dash, Earl T. Barr, Charles Sutton:
Deep Learning to Detect Redundant Method Comments. CoRR abs/1806.04616 (2018) - [i12]Earl T. Barr, David Clark, Mark Harman, Alexandru Marginean:
Indexing Operators to Extend the Reach of Symbolic Execution. CoRR abs/1806.10235 (2018) - [i11]David Landsberg, Earl T. Barr:
Doric: Foundations for Statistical Fault Localisation. CoRR abs/1810.00798 (2018) - [i10]David Landsberg, Earl T. Barr:
Automated Fix Detection Given Flaky Tests. CoRR abs/1810.02659 (2018) - 2017
- [j5]Dong Qiu, Bixin Li
Understanding the syntactic rule usage in java. J. Syst. Softw. 123: 160-172 (2017) - [c34]Zheng Gao, Christian Bird, Earl T. Barr
To type or not to type: quantifying detectable bugs in JavaScript. ICSE 2017: 758-769 - [c33]Michail Basios, Lingbo Li, Fan Wu
Optimising Darwinian Data Structures on Google Guava. SSBSE 2017: 161-167 - [i9]Michail Basios, Lingbo Li, Fan Wu, Leslie Kanthan, Donald Lawrence, Earl T. Barr:
Darwinian Data Structure Selection. CoRR abs/1706.03232 (2017) - [i8]Miltiadis Allamanis, Earl T. Barr, Premkumar T. Devanbu, Charles Sutton:
A Survey of Machine Learning for Big Code and Naturalness. CoRR abs/1709.06182 (2017) - 2016
- [j4]Abram Hindle, Earl T. Barr
On the naturalness of software. Commun. ACM 59(5): 122-131 (2016) - [j3]Benoit Cornu, Earl T. Barr
Casper: Automatic tracking of null dereferences to inception with causality traces. J. Syst. Softw. 122: 52-62 (2016) - [c32]Earl T. Barr
Time-travel debugging for JavaScript/Node.js. SIGSOFT FSE 2016: 1003-1007 - [p1]Earl T. Barr, Premkumar T. Devanbu:
The naturalness of software ☆. Perspectives on Data Science for Software Engineering 2016: 51-55 - [i7]Sukriti Bhattacharya, Héctor D. Menéndez, Earl T. Barr, David Clark:
ITect: Scalable Information Theoretic Similarity for Malware Detection. CoRR abs/1609.02404 (2016) - [i6]Miltiadis Allamanis, Earl T. Barr, René Just, Charles Sutton:
Tailored Mutants Fit Bugs Better. CoRR abs/1611.02516 (2016) - [i5]Avishkar Bhoopchand, Tim Rocktäschel, Earl T. Barr, Sebastian Riedel:
Learning Python Code Suggestion with a Sparse Pointer Network. CoRR abs/1611.08307 (2016) - 2015
- [j2]Earl T. Barr
The Oracle Problem in Software Testing: A Survey. IEEE Trans. Software Eng. 41(5): 507-525 (2015) - [c31]Earl T. Barr
Automated software transplantation. ISSTA 2015: 257-269 - [c30]Miltiadis Allamanis
Suggesting accurate method and class names. ESEC/SIGSOFT FSE 2015: 38-49 - [c29]Edward K. Smith, Earl T. Barr
Is the cure worse than the disease? overfitting in automated program repair. ESEC/SIGSOFT FSE 2015: 532-543 - [c28]Alexandru Marginean, Earl T. Barr
Automated Transplantation of Call Graph and Layout Features into Kate. SSBSE 2015: 262-268 - [i4]Martin Velez, Dong Qiu, You Zhou, Earl T. Barr, Zhendong Su:
A Study of "Wheat" and "Chaff" in Source Code. CoRR abs/1502.01410 (2015) - [i3]Benoit Cornu, Earl T. Barr, Lionel Seinturier
Casper: Debugging Null Dereferences with Dynamic Causality Traces. CoRR abs/1502.02004 (2015) - [i2]Nadia Alshahwan, Earl T. Barr, David Clark, George Danezis:
Detecting Malware with Information Complexity. CoRR abs/1502.07661 (2015) - 2014
- [c27]Foyzur Rahman, Sameer Khatri, Earl T. Barr
Comparing static bug finders and statistical prediction. ICSE 2014: 424-434 - [c26]Emmanuel Letier, David Stefan, Earl T. Barr
Uncertainty, risk, and information value in software requirements and architecture. ICSE 2014: 883-894 - [c25]Earl T. Barr
Tardis: affordable time-travel debugging in managed runtimes. OOPSLA 2014: 67-82 - [c24]Zhongxian Gu, Drew Schleck, Earl T. Barr
Capturing and Exploiting IDE Interactions. Onward! 2014: 83-94 - [c23]Miltiadis Allamanis
Learning natural coding conventions. SIGSOFT FSE 2014: 281-293 - [c22]Earl T. Barr
The plastic surgery hypothesis. SIGSOFT FSE 2014: 306-317 - [i1]Miltiadis Allamanis, Earl T. Barr, Charles Sutton:
Learning Natural Coding Conventions. CoRR abs/1402.4182 (2014) - 2013
- [c21]Peter C. Rigby, Earl T. Barr
What effect does distributed version control have on OSS project organization? RELENG@ICSE 2013: 29-32 - [c20]Earl T. Barr
Collecting a heap of shapes. ISSTA 2013: 123-133 - [c19]Earl T. Barr
Automatic detection of floating-point exceptions. POPL 2013: 549-560 - 2012
- [c18]Earl T. Barr
Cohesive and Isolated Development with Branches. FASE 2012: 316-331 - [c17]Abram Hindle, Earl T. Barr
On the naturalness of software. ICSE 2012: 837-847 - [c16]Mehrdad Afshari, Earl T. Barr
Liberating the programmer with prorogued programming. Onward! 2012: 11-26 - [c15]Zhongxian Gu, Earl T. Barr
Reusing debugging knowledge via trace-based bug search. OOPSLA 2012: 927-942 - 2011
- [c14]Zhongxian Gu, Earl T. Barr
BQL: capturing and reusing debugging knowledge. ICSE 2011: 1001-1003 - [c13]Foyzur Rahman, Daryl Posnett, Abram Hindle, Earl T. Barr
BugCache for inspections: hit or miss? SIGSOFT FSE 2011: 322-331 - 2010
- [c12]Zhongxian Gu, Earl T. Barr
Has the bug really been fixed? ICSE (1) 2010: 55-64 - [c11]Enyi Tang, Earl T. Barr
Perturbing numerical calculations for statistical analysis of floating-point program (in)stability. ISSTA 2010: 131-142 - [c10]Earl T. Barr
On the shoulders of giants. FoSER 2010: 23-28
2000 – 2009
- 2009
- [c9]Dimitri do B. DeFigueiredo, Earl T. Barr
Trust Is in the Eye of the Beholder. CSE (3) 2009: 100-108 - [c8]Christian Bird, Peter C. Rigby, Earl T. Barr
The promises and perils of mining git. MSR 2009: 1-10 - [c7]Christian Bird, Earl T. Barr
Structure and Dynamics of Research Collaboration in Computer Science. SDM 2009: 826-837 - 2007
- [j1]Earl T. Barr
Fixing federal e-voting standards. Commun. ACM 50(3): 19-24 (2007) - [c6]Jedidiah R. Crandall
ConceptDoppler: a weather tracker for internet censorship. CCS 2007: 352-365 - 2005
- [c5]Dimitri do B. DeFigueiredo, Earl T. Barr
TrustDavis: A Non-Exploitable Online Reputation System. CEC 2005: 274-283 - 2004
- [c4]Michael Haungs, Raju Pandey, Earl T. Barr
Handling Catastrophic Failures in Scalable Internet Applications. SAINT 2004: 188-196 - 2002
- [c3]Michael Haungs, Raju Pandey, Earl T. Barr, J. Fritz Barnes:
A Fast Connection-Time Redirection Mechanism for Internet Application Scalability. HiPC 2002: 209-218 - 2001
- [c2]Earl T. Barr, Raju Pandey, Michael Haungs:
MAGE: A Distributed Programming Model. ICDCS 2001: 303-312 - 2000
- [c1]Scott Malabarba, Raju Pandey, Jeff Gragg, Earl T. Barr
Runtime Support for Type-Safe Dynamic Java Classes. ECOOP 2000: 337-361
Coauthor Index
Premkumar T. Devanbu
aka: Prem Devanbu
aka: Prem Devanbu
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last updated on 2024-11-22 20:39 CET by the dblp team
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