Learning to Find Software Bugs

Informazioni relative al progetto

LearnBugs

ID dell’accordo di sovvenzione: 851895

DOI

10.3030/851895

Progetto chiuso

Data della firma CE 18 Settembre 2019

Data di avvio 1 Marzo 2020

Data di completamento 31 Agosto 2025

Finanziato da

• EXCELLENT SCIENCE - European Research Council (ERC)

Costo totale

€ 1 458 375,00

Contributo UE

€ 1 458 375,00

Coordinato da

UNIVERSITY OF STUTTGART
Germany

CORDIS fornisce collegamenti ai risultati finali pubblici e alle pubblicazioni dei progetti ORIZZONTE.

I link ai risultati e alle pubblicazioni dei progetti del 7° PQ, così come i link ad alcuni tipi di risultati specifici come dataset e software, sono recuperati dinamicamente da .OpenAIRE .

Risultati finali

Open Research Data Pilot (1)

Data Management Plan

Research data produced during the project

Pubblicazioni

Conference proceedings (36)

Nalin: Learning from Runtime Behavior to Find Name-Value Inconsistencies in Jupyter Notebooks

Autori: Jibesh Patra, Michael Pradel
Pubblicato in: ICSE '22: Proceedings of the 44th International Conference on Software Engineering, 2022
Editore: Association for Computing Machinery
DOI: 10.1145/3510003.3510144

Wobfuscator: Obfuscating JavaScript Malware via Opportunistic Translation to WebAssembly

Autori: Alan Romano, Daniel Lehmann, Michael Pradel, Weihang Wang
Pubblicato in: 2022 IEEE Symposium on Security and Privacy (SP), 2022
Editore: IEEE
DOI: 10.1109/sp46214.2022.9833626

Resource Usage and Optimization Opportunities in Workflows of GitHub Actions

Autori: Islem Bouzenia, Michael Pradel
Pubblicato in: Proceedings of the IEEE/ACM 46th International Conference on Software Engineering, 2024, Pagina/e 1-12
Editore: ACM
DOI: 10.1145/3597503.3623303

Finding data compatibility bugs with JSON subschema checking

Autori: Andrew Habib, Avraham Shinnar, Martin Hirzel, Michael Pradel
Pubblicato in: Proceedings of the 30th ACM SIGSOFT International Symposium on Software Testing and Analysis, 2021, Pagina/e 620-632, ISBN 9781450384599
Editore: ACM
DOI: 10.1145/3460319.3464796

Everything Old is New Again: Binary Security of WebAssembly

Autori: Daniel Lehmann, Johannes Kinder, Michael Pradel
Pubblicato in: 2020
Editore: USENIX Security Symposium 2020

SecBench.js: An Executable Security Benchmark Suite for Server-Side JavaScript

Autori: Masudul Hasan Masud Bhuiyan, Adithya Srinivas Parthasarathy, Nikos Vasilakis, Michael Pradel, Cristian-Alexandru Staicu
Pubblicato in: 2023 IEEE/ACM 45th International Conference on Software Engineering (ICSE), 2023
Editore: IEEE
DOI: 10.1109/icse48619.2023.00096

PyTy: Repairing Static Type Errors in Python

Autori: Yiu Wai Chow, Luca Di Grazia, Michael Pradel
Pubblicato in: Proceedings of the IEEE/ACM 46th International Conference on Software Engineering, 2024, Pagina/e 1-13
Editore: ACM
DOI: 10.1145/3597503.3639184

Fuzz4All: Universal Fuzzing with Large Language Models

Autori: Chunqiu Steven Xia, Matteo Paltenghi, Jia Le Tian, Michael Pradel, Lingming Zhang
Pubblicato in: Proceedings of the IEEE/ACM 46th International Conference on Software Engineering, 2024, Pagina/e 1-13
Editore: ACM
DOI: 10.1145/3597503.3639121

TypeWriter: neural type prediction with search-based validation

Autori: Michael Pradel, Georgios Gousios, Jason Liu, Satish Chandra
Pubblicato in: Proceedings of the 28th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering, 2020, Pagina/e 209-220, ISBN 9781450370431
Editore: ACM
DOI: 10.1145/3368089.3409715

Scaffle: bug localization on millions of files

Autori: Michael Pradel, Vijayaraghavan Murali, Rebecca Qian, Mateusz Machalica, Erik Meijer, Satish Chandra
Pubblicato in: Proceedings of the 29th ACM SIGSOFT International Symposium on Software Testing and Analysis, 2020, Pagina/e 225-236, ISBN 9781450380089
Editore: ACM
DOI: 10.1145/3395363.3397356

An Empirical Study of Real-World WebAssembly Binaries - Security, Languages, Use Cases

Autori: Aaron Hilbig, Daniel Lehmann, Michael Pradel
Pubblicato in: Proceedings of the Web Conference 2021, 2021, Pagina/e 2696-2708, ISBN 9781450383127
Editore: ACM
DOI: 10.1145/3442381.3450138

Preventing Dynamic Library Compromise on Node.js via RWX-Based Privilege Reduction

Autori: Nikos Vasilakis, Cristian-Alexandru Staicu, Grigoris Ntousakis, Konstantinos Kallas, Ben Karel, Andre DeHon, Michael Pradel
Pubblicato in: CCS '21: Proceedings of the 2021 ACM SIGSAC Conference on Computer and Communications Security, 2021
Editore: Association for Computing Machinery
DOI: 10.1145/3460120

Nessie: Automatically Testing JavaScript APIs with Asynchronous Callbacks

Autori: Ellen Arteca, Sebastian Harner, Michael Pradel, Frank Tip
Pubblicato in: ICSE '22: Proceedings of the 44th International Conference on Software Engineering, 2022
Editore: Association for Computing Machinery
DOI: 10.1145/3510003.3510106

ConfProf: White-Box Performance Profiling of Configuration Options

Autori: Xue Han, Tingting Yu, Michael Pradel
Pubblicato in: Proceedings of the ACM/SPEC International Conference on Performance Engineering, 2021, Pagina/e 1-8, ISBN 9781450381949
Editore: ACM
DOI: 10.1145/3427921.3450255

Continuous test suite failure prediction

Autori: Cong Pan, Michael Pradel
Pubblicato in: Proceedings of the 30th ACM SIGSOFT International Symposium on Software Testing and Analysis, 2021, Pagina/e 553-565, ISBN 9781450384599
Editore: ACM
DOI: 10.1145/3460319.3464840

Treefix: Enabling Execution with a Tree of Prefixes

Autori: Beatriz Souza, Michael Pradel
Pubblicato in: 2025 IEEE/ACM 47th International Conference on Software Engineering (ICSE), 2025, Pagina/e 2676-2688
Editore: IEEE
DOI: 10.1109/icse55347.2025.00215

No strings attached - an empirical study of string-related software bugs

Autori: Aryaz Eghbali, Michael Pradel
Pubblicato in: Proceedings of the 35th IEEE/ACM International Conference on Automated Software Engineering, 2020, Pagina/e 956-967, ISBN 9781450367684
Editore: ACM
DOI: 10.1145/3324884.3416576

The Evolution of Type Annotations in Python: An Empirical Study

Autori: Luca Di Grazia, Michael Pradel
Pubblicato in: ESEC/FSE 2022: Proceedings of the 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, 2022
Editore: Association for Computing Machinery
DOI: 10.5281/zenodo.7082252

Beware of the Unexpected: Bimodal Taint Analysis

Autori: Yiu Wai Chow, Max Schäfer, Michael Pradel
Pubblicato in: Proceedings of the 32nd ACM SIGSOFT International Symposium on Software Testing and Analysis, 2023, Pagina/e 211-222
Editore: ACM
DOI: 10.1145/3597926.3598050

RepairAgent: An Autonomous, LLM-Based Agent for Program Repair

Autori: Islem Bouzenia, Premkumar Devanbu, Michael Pradel
Pubblicato in: 2025 IEEE/ACM 47th International Conference on Software Engineering (ICSE), 2025, Pagina/e 2188-2200
Editore: IEEE
DOI: 10.1109/icse55347.2025.00157

Generating Realistic Vulnerabilities via Neural Code Editing: An Empirical Study

Autori: Yu Nong, Yuzhe Ou, Michael Pradel, Feng Chen, Haipeng Cai
Pubblicato in: ESEC/FSE 2022: Proceedings of the 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, 2022
Editore: Association for Computing Machinery
DOI: 10.5281/zenodo.7048525

MorphQ: Metamorphic Testing of the Qiskit Quantum Computing Platform

Autori: Matteo Paltenghi, Michael Pradel
Pubblicato in: 2023 IEEE/ACM 45th International Conference on Software Engineering (ICSE), 2024, Pagina/e 2413-2424
Editore: IEEE
DOI: 10.1109/icse48619.2023.00202

LExecutor: Learning-Guided Execution

Autori: Beatriz Souza, Michael Pradel
Pubblicato in: Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, 2024, Pagina/e 1522-1534
Editore: ACM
DOI: 10.1145/3611643.3616254

Semantic bug seeding: a learning-based approach for creating realistic bugs

Autori: Jibesh Patra, Michael Pradel
Pubblicato in: Proceedings of the 29th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering, 2021, Pagina/e 906-918, ISBN 9781450385626
Editore: ACM
DOI: 10.1145/3468264.3468623

IdBench: Evaluating Semantic Representations of Identifier Names in Source Code

Autori: Yaza Wainakh, Moiz Rauf, Michael Pradel
Pubblicato in: 2021 IEEE/ACM 43rd International Conference on Software Engineering (ICSE), 2021, Pagina/e 562-573, ISBN 978-1-6654-0296-5
Editore: IEEE
DOI: 10.1109/icse43902.2021.00059

Thinking Like a Developer? Comparing the Attention of Humans with Neural Models of Code

Autori: Matteo Paltenghi, Michael Pradel
Pubblicato in: 2021 36th IEEE/ACM International Conference on Automated Software Engineering (ASE), 2021
Editore: IEEE
DOI: 10.1109/ase51524.2021.9678712

That’s a Tough Call: Studying the Challenges of Call Graph Construction for WebAssembly

Autori: Daniel Lehmann, Michelle Thalakottur, Frank Tip, Michael Pradel
Pubblicato in: Proceedings of the 32nd ACM SIGSOFT International Symposium on Software Testing and Analysis, 2023
Editore: ACM
DOI: 10.1145/3597926.3598104

Calibration and Correctness of Language Models for Code

Autori: Claudio Spiess, David Gros, Kunal Suresh Pai, Michael Pradel, Md Rafiqul Islam Rabin, Amin Alipour, Susmit Jha, Prem Devanbu, Toufique Ahmed
Pubblicato in: 2025 IEEE/ACM 47th International Conference on Software Engineering (ICSE), 2025, Pagina/e 540-552
Editore: IEEE
DOI: 10.1109/icse55347.2025.00040

VULGEN: Realistic Vulnerability Generation Via Pattern Mining and Deep Learning

Autori: Yu Nong, Yuzhe Ou, Michael Pradel, Feng Chen, Haipeng Cai
Pubblicato in: 2023 IEEE/ACM 45th International Conference on Software Engineering (ICSE), 2023, Pagina/e 2527-2539
Editore: IEEE
DOI: 10.1109/icse48619.2023.00211

CrystalBLEU: Precisely and Efficiently Measuring the Similarity of Code

Autori: Aryaz Eghbali, Michael Pradel
Pubblicato in: ICSE '22: Proceedings of the ACM/IEEE 44th International Conference on Software Engineering: Companion Proceedings, 2022
Editore: Association for Computing Machinery
DOI: 10.1145/3510454.3528648

Learning to make compiler optimizations more effective

Autori: Rahim Mammadli; Marija Selakovic; Felix Wolf; Michael Pradel
Pubblicato in: MAPS@PLDI, Numero 1, 2021
Editore: ACM
DOI: 10.1145/3460945.3464952

Finding the Dwarf: Recovering Precise Types from WebAssembly Binaries

Autori: Daniel Lehmann, Michael Pradel
Pubblicato in: PLDI 2022: Proceedings of the 43rd ACM SIGPLAN International Conference on Programming Language Design and Implementation, 2022
Editore: Association for Computing Machinery
DOI: 10.1145/3519939.3523449

When to Say What: Learning to Find Condition-Message Inconsistencies

Autori: Islem Bouzenia, Michael Pradel
Pubblicato in: 2023 IEEE/ACM 45th International Conference on Software Engineering (ICSE), 2023, Pagina/e 868-880
Editore: IEEE
DOI: 10.1109/icse48619.2023.00081

DynaPyt: A Dynamic Analysis Framework for Python

Autori: Aryaz Eghbali, Michael Pradel
Pubblicato in: ESEC/FSE 2022: Proceedings of the 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, 2022
Editore: Association for Computing Machinery
DOI: 10.5281/zenodo.7037946

Can LLMs Replace Manual Annotation of Software Engineering Artifacts?

Autori: Toufique Ahmed, Premkumar Devanbu, Christoph Treude, Michael Pradel
Pubblicato in: 2025 IEEE/ACM 22nd International Conference on Mining Software Repositories (MSR), 2025, Pagina/e 526-538
Editore: IEEE
DOI: 10.1109/msr66628.2025.00086

Extracting taint specifications for JavaScript libraries

Autori: Cristian-Alexandru Staicu, Martin Toldam Torp, Max Schäfer, Anders Møller, Michael Pradel
Pubblicato in: Proceedings of the ACM/IEEE 42nd International Conference on Software Engineering, 2020, Pagina/e 198-209, ISBN 9781450371216
Editore: ACM
DOI: 10.1145/3377811.3380390

Peer reviewed articles (10)

DyPyBench: A Benchmark of Executable Python Software

Autori: Islem Bouzenia, Bajaj Piyush Krishan, Michael Pradel
Pubblicato in: Proceedings of the ACM on Software Engineering, Numero 1, 2024, Pagina/e 338-358, ISSN 2994-970X
Editore: FSE
DOI: 10.1145/3643742

ChangeGuard: Validating Code Changes via Pairwise Learning-Guided Execution

Autori: Lars Gröninger, Beatriz Souza, Michael Pradel
Pubblicato in: Proceedings of the ACM on Software Engineering, Numero 2, 2025, Pagina/e 936-956, ISSN 2994-970X
Editore: Association for Computing Machinery (ACM)
DOI: 10.1145/3715760

An Empirical Study of Suppressed Static Analysis Warnings

Autori: Huimin Hu, Yingying Wang, Julia Rubin, Michael Pradel
Pubblicato in: Proceedings of the ACM on Software Engineering, Numero 2, 2025, Pagina/e 290-311, ISSN 2994-970X
Editore: Association for Computing Machinery (ACM)
DOI: 10.1145/3715729

Analyzing Quantum Programs with LintQ: A Static Analysis Framework for Qiskit

Autori: Matteo Paltenghi, Michael Pradel
Pubblicato in: Proceedings of the ACM on Software Engineering, Numero 1, 2024, Pagina/e 2144-2166, ISSN 2994-970X
Editore: FSE
DOI: 10.1145/3660802

You Name It, I Run It: An LLM Agent to Execute Tests of Arbitrary Projects

Autori: Islem Bouzenia, Michael Pradel
Pubblicato in: Proceedings of the ACM on Software Engineering, Numero 2, 2025, Pagina/e 1054-1076, ISSN 2994-970X
Editore: Association for Computing Machinery (ACM)
DOI: 10.1145/3728922

Code Search: A Survey of Techniques for Finding Code

Autori: Luca Di Grazia, Michael Pradel
Pubblicato in: ACM Computing Surveys Volume 55, Numero 11, 2022, ISSN 0360-0300
Editore: Association for Computing Machinary, Inc.
DOI: 10.1145/3565971

DiffSearch: A Scalable and Precise Search Engine for Code Changes

Autori: Luca Di Grazia, Paul Bredl, Michael Pradel
Pubblicato in: IEEE Transactions on Software Engineering, Numero 49, 2024, Pagina/e 2366-2380, ISSN 0098-5589
Editore: Institute of Electrical and Electronics Engineers
DOI: 10.1109/tse.2022.3218859

Wasm-R3: Record-Reduce-Replay for Realistic and Standalone WebAssembly Benchmarks

Autori: Doehyun Baek, Jakob Getz, Yusung Sim, Daniel Lehmann, Ben L. Titzer, Sukyoung Ryu, Michael Pradel
Pubblicato in: Proceedings of the ACM on Programming Languages, Numero 8, 2025, Pagina/e 2156-2182, ISSN 2475-1421
Editore: Association for Computing Machinery (ACM)
DOI: 10.1145/3689787

DyLin: A Dynamic Linter for Python

Autori: Aryaz Eghbali, Felix Burk, Michael Pradel
Pubblicato in: Proceedings of the ACM on Software Engineering, Numero 2, 2025, Pagina/e 2828-2849, ISSN 2994-970X
Editore: Association for Computing Machinery (ACM)
DOI: 10.1145/3729395

Bugs in Quantum Computing Platforms: An Empirical Study

Autori: Matteo Paltenghi, Michael Pradel
Pubblicato in: Proceedings of the ACM on Programming Languages Volume 6, Numero OOPSLA1, 2022, ISSN 2475-1421
Editore: Association for Computing Machinery
DOI: 10.5281/zenodo.5834281

Other (1)

Neural Software Analysis

Autori: Satish Chandra, Michael Pradel
Pubblicato in: Communications of the ACM, 2020
Editore: ACM
DOI: 10.1145/3460348