default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDMichael Pradel
Person information
- affiliation: University of Stuttgart, Department of Computer Science, Germany
- affiliation: TU Darmstadt, Department of Computer Science, Germany
- affiliation: ETH Zurich, Switzerland
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2024
[j21]Doehyun Baek
, Jakob Getz, Yusung Sim, Daniel Lehmann, Ben L. Titzer, Sukyoung Ryu, Michael Pradel:
Wasm-R3: Record-Reduce-Replay for Realistic and Standalone WebAssembly Benchmarks. Proc. ACM Program. Lang. 8(OOPSLA2): 2156-2182 (2024)- [j20]Islem Bouzenia, Bajaj Piyush Krishan, Michael Pradel:
DyPyBench: A Benchmark of Executable Python Software. Proc. ACM Softw. Eng. 1(FSE): 338-358 (2024) - [j19]Matteo Paltenghi, Michael Pradel:
Analyzing Quantum Programs with LintQ: A Static Analysis Framework for Qiskit. Proc. ACM Softw. Eng. 1(FSE): 2144-2166 (2024) - [j18]Sebastián Uchitel, Marsha Chechik, Massimiliano Di Penta, Bram Adams, Nazareno Aguirre, Gabriele Bavota, Domenico Bianculli, Kelly Blincoe, Ana Cavalcanti, Yvonne Dittrich, Filomena Ferrucci, Rashina Hoda, LiGuo Huang, David Lo, Michael R. Lyu, Lei Ma, Jonathan I. Maletic, Leonardo Mariani, Collin McMillan, Tim Menzies, Martin Monperrus, Ana Moreno, Nachiappan Nagappan, Liliana Pasquale, Patrizio Pelliccione, Michael Pradel, Rahul Purandare, Sukyoung Ryu, Mehrdad Sabetzadeh, Alexander Serebrenik, Jun Sun, Chakkrit Kla Tantithamthavorn, Christoph Treude, Manuel Wimmer, Yingfei Xiong, Tao Yue, Andy Zaidman, Tao Zhang, Hao Zhong:
Scoping Software Engineering for AI: The TSE Perspective. IEEE Trans. Software Eng. 50(11): 2709-2711 (2024) - [c85]Islem Bouzenia, Michael Pradel:
Resource Usage and Optimization Opportunities in Workflows of GitHub Actions. ICSE 2024: 25:1-25:12 - [c84]Yiu Wai Chow, Luca Di Grazia, Michael Pradel:
PyTy: Repairing Static Type Errors in Python. ICSE 2024: 87:1-87:13 - [c83]Chunqiu Steven Xia, Matteo Paltenghi, Jia Le Tian, Michael Pradel, Lingming Zhang:
Fuzz4All: Universal Fuzzing with Large Language Models. ICSE 2024: 126:1-126:13 - [e1]Maria Christakis, Michael Pradel:
Proceedings of the 33rd ACM SIGSOFT International Symposium on Software Testing and Analysis, ISSTA 2024, Vienna, Austria, September 16-20, 2024. ACM 2024, ISBN 979-8-4007-0612-7 [contents] - [i41]Aryaz Eghbali, Michael Pradel:
De-Hallucinator: Iterative Grounding for LLM-Based Code Completion. CoRR abs/2401.01701 (2024) - [i40]Yiu Wai Chow, Luca Di Grazia, Michael Pradel:
PyTy: Repairing Static Type Errors in Python. CoRR abs/2401.06619 (2024) - [i39]Claudio Spiess, David Gros, Kunal Suresh Pai, Michael Pradel, Md. Rafiqul Islam Rabin, Amin Alipour, Susmit Jha, Prem Devanbu, Toufique Ahmed:
Calibration and Correctness of Language Models for Code. CoRR abs/2402.02047 (2024) - [i38]Islem Bouzenia, Bajaj Piyush Krishan, Michael Pradel:
DyPyBench: A Benchmark of Executable Python Software. CoRR abs/2403.00539 (2024) - [i37]Islem Bouzenia, Premkumar T. Devanbu, Michael Pradel:
RepairAgent: An Autonomous, LLM-Based Agent for Program Repair. CoRR abs/2403.17134 (2024) - [i36]Toufique Ahmed, Premkumar T. Devanbu, Christoph Treude, Michael Pradel:
Can LLMs Replace Manual Annotation of Software Engineering Artifacts? CoRR abs/2408.05534 (2024) - [i35]Doehyun Baek, Jakob Getz, Yusung Sim, Daniel Lehmann, Ben L. Titzer, Sukyoung Ryu, Michael Pradel:
Wasm-R3: Record-Reduce-Replay for Realistic and Standalone WebAssembly Benchmarks. CoRR abs/2409.00708 (2024) - [i34]Matteo Paltenghi, Michael Pradel:
A Survey on Testing and Analysis of Quantum Software. CoRR abs/2410.00650 (2024) - [i33]Lars Gröninger, Beatriz Souza, Michael Pradel:
ChangeGuard: Validating Code Changes via Pairwise Learning-Guided Execution. CoRR abs/2410.16092 (2024) - [i32]Islem Bouzenia, Michael Pradel:
You Name It, I Run It: An LLM Agent to Execute Tests of Arbitrary Projects. CoRR abs/2412.10133 (2024) - [i31]Satish Chandra, Michael Pradel, Kathryn T. Stolee:
Code Search (Dagstuhl Seminar 24172). Dagstuhl Reports 14(4): 108-123 (2024) - 2023
- [j17]Luca Di Grazia, Michael Pradel:
Code Search: A Survey of Techniques for Finding Code. ACM Comput. Surv. 55(11): 220:1-220:31 (2023) - [j16]Luca Di Grazia, Paul Bredl, Michael Pradel:
DiffSearch: A Scalable and Precise Search Engine for Code Changes. IEEE Trans. Software Eng. 49(4): 2366-2380 (2023) - [c82]Islem Bouzenia, Michael Pradel:
When to Say What: Learning to Find Condition-Message Inconsistencies. ICSE 2023: 868-880 - [c81]Masudul Hasan Masud Bhuiyan, Adithya Srinivas Parthasarathy, Nikos Vasilakis, Michael Pradel, Cristian-Alexandru Staicu:
SecBench.js: An Executable Security Benchmark Suite for Server-Side JavaScript. ICSE 2023: 1059-1070 - [c80]Matteo Paltenghi, Michael Pradel:
MorphQ: Metamorphic Testing of the Qiskit Quantum Computing Platform. ICSE 2023: 2413-2424 - [c79]Yu Nong, Yuzhe Ou, Michael Pradel, Feng Chen, Haipeng Cai:
VULGEN: Realistic Vulnerability Generation Via Pattern Mining and Deep Learning. ICSE 2023: 2527-2539 - [c78]Yiu Wai Chow, Max Schäfer, Michael Pradel:
Beware of the Unexpected: Bimodal Taint Analysis. ISSTA 2023: 211-222 - [c77]Daniel Lehmann, Michelle Thalakottur, Frank Tip, Michael Pradel:
That's a Tough Call: Studying the Challenges of Call Graph Construction for WebAssembly. ISSTA 2023: 892-903 - [c76]Beatriz Souza, Michael Pradel:
LExecutor: Learning-Guided Execution. ESEC/SIGSOFT FSE 2023: 1522-1534 - [i30]Yiu Wai Chow, Max Schäfer, Michael Pradel:
Beware of the Unexpected: Bimodal Taint Analysis. CoRR abs/2301.10545 (2023) - [i29]Beatriz Souza, Michael Pradel:
LExecutor: Learning-Guided Execution. CoRR abs/2302.02343 (2023) - [i28]Islem Bouzenia, Yangruibo Ding, Kexin Pei, Baishakhi Ray, Michael Pradel:
TraceFixer: Execution Trace-Driven Program Repair. CoRR abs/2304.12743 (2023) - [i27]Dominik Huber, Matteo Paltenghi, Michael Pradel:
Where to Look When Repairing Code? Comparing the Attention of Neural Models and Developers. CoRR abs/2305.07287 (2023) - [i26]Chunqiu Steven Xia, Matteo Paltenghi, Jia Le Tian, Michael Pradel, Lingming Zhang:
Universal Fuzzing via Large Language Models. CoRR abs/2308.04748 (2023) - [i25]Matteo Paltenghi, Michael Pradel:
LintQ: A Static Analysis Framework for Qiskit Quantum Programs. CoRR abs/2310.00718 (2023) - [i24]Michael Pradel, Baishakhi Ray, Charles Sutton, Eran Yahav:
Programming Language Processing (Dagstuhl Seminar 23062). Dagstuhl Reports 13(2): 20-32 (2023) - 2022
- [j15]Michael Pradel, Satish Chandra:
Neural software analysis. Commun. ACM 65(1): 86-96 (2022) - [j14]Matteo Paltenghi, Michael Pradel:
Bugs in Quantum computing platforms: an empirical study. Proc. ACM Program. Lang. 6(OOPSLA1): 1-27 (2022) - [c75]Aryaz Eghbali, Michael Pradel:
CrystalBLEU: Precisely and Efficiently Measuring the Similarity of Code. ICSE-Companion 2022: 341-342 - [c74]Jibesh Patra, Michael Pradel:
Nalin: learning from Runtime Behavior to Find Name-Value Inconsistencies in Jupyter Notebooks. ICSE 2022: 1469-1481 - [c73]Ellen Arteca, Sebastian Harner, Michael Pradel, Frank Tip:
Nessie: Automatically Testing JavaScript APIs with Asynchronous Callbacks. ICSE 2022: 1494-1505 - [c72]Aryaz Eghbali, Michael Pradel:
CrystalBLEU: Precisely and Efficiently Measuring the Similarity of Code. ASE 2022: 28:1-28:12 - [c71]Daniel Lehmann, Michael Pradel:
Finding the dwarf: recovering precise types from WebAssembly binaries. PLDI 2022: 410-425 - [c70]Luca Di Grazia, Michael Pradel:
The evolution of type annotations in python: an empirical study. ESEC/SIGSOFT FSE 2022: 209-220 - [c69]Aryaz Eghbali, Michael Pradel:
DynaPyt: a dynamic analysis framework for Python. ESEC/SIGSOFT FSE 2022: 760-771 - [c68]Yu Nong, Yuzhe Ou, Michael Pradel, Feng Chen, Haipeng Cai:
Generating realistic vulnerabilities via neural code editing: an empirical study. ESEC/SIGSOFT FSE 2022: 1097-1109 - [c67]Alan Romano, Daniel Lehmann, Michael Pradel, Weihang Wang:
Wobfuscator: Obfuscating JavaScript Malware via Opportunistic Translation to WebAssembly. SP 2022: 1574-1589 - [i23]Moiz Rauf, Sebastian Padó, Michael Pradel:
Meta Learning for Code Summarization. CoRR abs/2201.08310 (2022) - [i22]Luca Di Grazia, Michael Pradel:
Code Search: A Survey of Techniques for Finding Code. CoRR abs/2204.02765 (2022) - [i21]Luca Di Grazia, Paul Bredl, Michael Pradel:
DiffSearch: A Scalable and Precise Search Engine for Code Changes. CoRR abs/2204.02787 (2022) - [i20]Matteo Paltenghi, Michael Pradel:
MorphQ: Metamorphic Testing of Quantum Computing Platforms. CoRR abs/2206.01111 (2022) - [i19]Patrick Bareiß, Beatriz Souza, Marcelo d'Amorim, Michael Pradel:
Code Generation Tools (Almost) for Free? A Study of Few-Shot, Pre-Trained Language Models on Code. CoRR abs/2206.01335 (2022) - 2021
- [j13]Junjie Chen, Jibesh Patra, Michael Pradel, Yingfei Xiong, Hongyu Zhang, Dan Hao, Lu Zhang:
A Survey of Compiler Testing. ACM Comput. Surv. 53(1): 4:1-4:36 (2021) - [j12]Jhonny Mertz, Ingrid Nunes, Luca Della Toffola, Marija Selakovic, Michael Pradel:
Satisfying Increasing Performance Requirements With Caching at the Application Level. IEEE Softw. 38(3): 87-95 (2021) - [j11]Claire Le Goues, Michael Pradel, Abhik Roychoudhury, Satish Chandra:
Automatic Program Repair. IEEE Softw. 38(4): 22-27 (2021) - [c66]Nikos Vasilakis, Cristian-Alexandru Staicu, Grigoris Ntousakis, Konstantinos Kallas, Ben Karel, André DeHon, Michael Pradel:
Preventing Dynamic Library Compromise on Node.js via RWX-Based Privilege Reduction. CCS 2021: 1821-1838 - [c65]Yaza Wainakh, Moiz Rauf, Michael Pradel:
IdBench: Evaluating Semantic Representations of Identifier Names in Source Code. ICSE 2021: 562-573 - [c64]Cong Pan, Michael Pradel:
Continuous test suite failure prediction. ISSTA 2021: 553-565 - [c63]Andrew Habib, Avraham Shinnar, Martin Hirzel, Michael Pradel:
Finding data compatibility bugs with JSON subschema checking. ISSTA 2021: 620-632 - [c62]Matteo Paltenghi, Michael Pradel:
Thinking Like a Developer? Comparing the Attention of Humans with Neural Models of Code. ASE 2021: 867-879 - [c61]Rahim Mammadli, Marija Selakovic, Felix Wolf, Michael Pradel:
Learning to make compiler optimizations more effective. MAPS@PLDI 2021: 9-20 - [c60]Jibesh Patra, Michael Pradel:
Semantic bug seeding: a learning-based approach for creating realistic bugs. ESEC/SIGSOFT FSE 2021: 906-918 - [c59]Xue Han, Tingting Yu, Michael Pradel:
ConfProf: White-Box Performance Profiling of Configuration Options. ICPE 2021: 1-8 - [c58]Aaron Hilbig, Daniel Lehmann, Michael Pradel:
An Empirical Study of Real-World WebAssembly Binaries: Security, Languages, Use Cases. WWW 2021: 2696-2708 - [i18]Rahim Mammadli, Marija Selakovic, Felix Wolf, Michael Pradel:
Learning to Make Compiler Optimizations More Effective. CoRR abs/2102.13514 (2021) - [i17]Matteo Paltenghi, Michael Pradel:
Bugs in Quantum Computing Platforms: An Empirical Study. CoRR abs/2110.14560 (2021) - [i16]Daniel Lehmann, Martin Toldam Torp, Michael Pradel:
Fuzzm: Finding Memory Bugs through Binary-Only Instrumentation and Fuzzing of WebAssembly. CoRR abs/2110.15433 (2021) - [i15]Jibesh Patra, Michael Pradel:
Nalin: Learning from Runtime Behavior to Find Name-Value Inconsistencies in Jupyter Notebooks. CoRR abs/2112.06186 (2021) - 2020
- [c57]Cristian-Alexandru Staicu, Martin Toldam Torp, Max Schäfer, Anders Møller, Michael Pradel:
Extracting taint specifications for JavaScript libraries. ICSE 2020: 198-209 - [c56]Michael Pradel, Vijayaraghavan Murali, Rebecca Qian, Mateusz Machalica, Erik Meijer, Satish Chandra:
Scaffle: bug localization on millions of files. ISSTA 2020: 225-236 - [c55]Aryaz Eghbali, Michael Pradel:
No Strings Attached: An Empirical Study of String-related Software Bugs. ASE 2020: 956-967 - [c54]Michael Pradel, Georgios Gousios, Jason Liu, Satish Chandra:
TypeWriter: neural type prediction with search-based validation. ESEC/SIGSOFT FSE 2020: 209-220 - [c53]Daniel Lehmann, Johannes Kinder, Michael Pradel:
Everything Old is New Again: Binary Security of WebAssembly. USENIX Security Symposium 2020: 217-234 - [i14]Jhonny Mertz, Ingrid Nunes, Luca Della Toffola, Marija Selakovic, Michael Pradel:
Satisfying Increasing Performance Requirements with Caching at the Application Level. CoRR abs/2010.12939 (2020) - [i13]Nikos Vasilakis, Cristian-Alexandru Staicu, Greg Ntousakis, Konstantinos Kallas, Ben Karel, André DeHon, Michael Pradel:
Mir: Automated Quantifiable Privilege Reduction Against Dynamic Library Compromise in JavaScript. CoRR abs/2011.00253 (2020) - [i12]Michael Pradel, Satish Chandra:
Neural Software Analysis. CoRR abs/2011.07986 (2020)
2010 – 2019
- 2019
- [j10]Claire Le Goues, Michael Pradel, Abhik Roychoudhury:
Automated program repair. Commun. ACM 62(12): 56-65 (2019) - [j9]Johannes Bader, Andrew Scott, Michael Pradel, Satish Chandra:
Getafix: learning to fix bugs automatically. Proc. ACM Program. Lang. 3(OOPSLA): 159:1-159:27 (2019) - [c52]Daniel Lehmann, Michael Pradel:
Wasabi: A Framework for Dynamically Analyzing WebAssembly. ASPLOS 2019: 1045-1058 - [c51]Cristian-Alexandru Staicu, Daniel Schoepe, Musard Balliu, Michael Pradel, Andrei Sabelfeld:
An Empirical Study of Information Flows in Real-World JavaScript. PLAS@CCS 2019: 45-59 - [c50]Rabee Sohail Malik, Jibesh Patra, Michael Pradel:
NL2Type: inferring JavaScript function types from natural language information. ICSE 2019: 304-315 - [c49]Sandro Tolksdorf, Daniel Lehmann, Michael Pradel:
Interactive metamorphic testing of debuggers. ISSTA 2019: 273-283 - [c48]Cristian-Alexandru Staicu, Michael Pradel:
Leaky Images: Targeted Privacy Attacks in the Web. USENIX Security Symposium 2019: 923-939 - [c47]Markus Zimmermann, Cristian-Alexandru Staicu, Cam Tenny, Michael Pradel:
Small World with High Risks: A Study of Security Threats in the npm Ecosystem. USENIX Security Symposium 2019: 995-1010 - [c46]Philippe Skolka, Cristian-Alexandru Staicu, Michael Pradel:
Anything to Hide? Studying Minified and Obfuscated Code in the Web. WWW 2019: 1735-1746 - [i11]Saeed Ehteshamifar, Antonio Barresi, Thomas R. Gross, Michael Pradel:
Easy to Fool? Testing the Anti-evasion Capabilities of PDF Malware Scanners. CoRR abs/1901.05674 (2019) - [i10]Markus Zimmermann, Cristian-Alexandru Staicu, Cam Tenny, Michael Pradel:
Small World with High Risks: A Study of Security Threats in the npm Ecosystem. CoRR abs/1902.09217 (2019) - [i9]Andrew Habib, Michael Pradel:
Neural Bug Finding: A Study of Opportunities and Challenges. CoRR abs/1906.00307 (2019) - [i8]Cristian-Alexandru Staicu, Daniel Schoepe, Musard Balliu, Michael Pradel, Andrei Sabelfeld:
An Empirical Study of Information Flows in Real-World JavaScript. CoRR abs/1906.11507 (2019) - [i7]Yaza Wainakh, Moiz Rauf, Michael Pradel:
Evaluating Semantic Representations of Source Code. CoRR abs/1910.05177 (2019) - [i6]Andrew Habib, Avraham Shinnar, Martin Hirzel, Michael Pradel:
Type Safety with JSON Subschema. CoRR abs/1911.12651 (2019) - [i5]Michael Pradel, Georgios Gousios, Jason Liu, Satish Chandra:
TypeWriter: Neural Type Prediction with Search-based Validation. CoRR abs/1912.03768 (2019) - 2018
- [j8]Tingting Yu, Michael Pradel:
Pinpointing and repairing performance bottlenecks in concurrent programs. Empir. Softw. Eng. 23(5): 3034-3071 (2018) - [j7]Michael Pradel, Koushik Sen:
DeepBugs: a learning approach to name-based bug detection. Proc. ACM Program. Lang. 2(OOPSLA): 147:1-147:25 (2018) - [j6]Marija Selakovic, Michael Pradel, Rezwana Karim, Frank Tip:
Test generation for higher-order functions in dynamic languages. Proc. ACM Program. Lang. 2(OOPSLA): 161:1-161:27 (2018) - [c45]Luca Della Toffola, Michael Pradel, Thomas R. Gross:
Synthesizing programs that expose performance bottlenecks. CGO 2018: 314-326 - [c44]Jibesh Patra, Pooja N. Dixit, Michael Pradel:
ConflictJS: finding and understanding conflicts between JavaScript libraries. ICSE 2018: 741-751 - [c43]Dileep Ramachandrarao Krishna Murthy, Michael Pradel:
Change-Aware Dynamic Program Analysis for JavaScript. ICSME 2018: 127-137 - [c42]Andrew Habib, Michael Pradel:
Is this class thread-safe? inferring documentation using graph-based learning. ASE 2018: 41-52 - [c41]Andrew Habib, Michael Pradel:
How many of all bugs do we find? a study of static bug detectors. ASE 2018: 317-328 - [c40]Cristian-Alexandru Staicu, Michael Pradel, Benjamin Livshits:
SYNODE: Understanding and Automatically Preventing Injection Attacks on NODE.JS. NDSS 2018 - [c39]Daniel Lehmann, Michael Pradel:
Feedback-directed differential testing of interactive debuggers. ESEC/SIGSOFT FSE 2018: 610-620 - [c38]Cristian-Alexandru Staicu, Michael Pradel:
Freezing the Web: A Study of ReDoS Vulnerabilities in JavaScript-based Web Servers. USENIX Security Symposium 2018: 361-376 - [i4]Michael Pradel, Koushik Sen:
DeepBugs: A Learning Approach to Name-based Bug Detection. CoRR abs/1805.11683 (2018) - [i3]Daniel Lehmann, Michael Pradel:
Wasabi: A Framework for Dynamically Analyzing WebAssembly. CoRR abs/1808.10652 (2018) - [i2]Rohan Bavishi, Michael Pradel, Koushik Sen:
Context2Name: A Deep Learning-Based Approach to Infer Natural Variable Names from Usage Contexts. CoRR abs/1809.05193 (2018) - 2017
- [j5]Esben Andreasen, Liang Gong, Anders Møller, Michael Pradel, Marija Selakovic, Koushik Sen, Cristian-Alexandru Staicu:
A Survey of Dynamic Analysis and Test Generation for JavaScript. ACM Comput. Surv. 50(5): 66:1-66:36 (2017) - [j4]Philipp Haller, Michael Pradel, Tijs van der Storm:
Front Matter - ECOOP 2017 Artifacts, Table of Contents, Preface, Artifact Evaluation Committee. Dagstuhl Artifacts Ser. 3(2): 00:-1-00:-12 (2017) - [j3]Andrew Rice, Edward Aftandilian, Ciera Jaspan, Emily Johnston, Michael Pradel, Yulissa Arroyo-Paredes:
Detecting argument selection defects. Proc. ACM Program. Lang. 1(OOPSLA): 104:1-104:22 (2017) - [c37]Ankit Choudhary, Shan Lu, Michael Pradel:
Efficient detection of thread safety violations via coverage-guided generation of concurrent tests. ICSE 2017: 266-277 - [c36]Siegfried Rasthofer, Steven Arzt, Stefan Triller, Michael Pradel:
Making malory behave maliciously: targeted fuzzing of android execution environments. ICSE 2017: 300-311 - [c35]Marija Selakovic, Thomas Glaser, Michael Pradel:
An actionable performance profiler for optimizing the order of evaluations. ISSTA 2017: 170-180 - [c34]Luca Della Toffola, Cristian-Alexandru Staicu, Michael Pradel:
Saying 'hi!' is not enough: mining inputs for effective test generation. ASE 2017: 44-49 - [c33]Satia Herfert, Jibesh Patra, Michael Pradel:
Automatically reducing tree-structured test inputs. ASE 2017: 861-871 - [c32]Marina Billes, Anders Møller, Michael Pradel:
Systematic black-box analysis of collaborative web applications. PLDI 2017: 171-184 - [c31]Marija Selakovic, Michael Pradel:
Performance Issues and Optimizations in JavaScript: An Empirical Study. Software Engineering 2017: 63 - [c30]Markus Ermuth, Michael Pradel:
Monkey See, Monkey Do: Effective Generation of GUI Tests with Inferred Macro Events. Software Engineering 2017: 87 - [i1]Sunghun Kim, Claire Le Goues, Michael Pradel, Abhik Roychoudhury:
Automated Program Repair (Dagstuhl Seminar 17022). Dagstuhl Reports 7(1): 19-31 (2017) - 2016
- [c29]