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ORCIDMichael Pradel
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- affiliation: University of Stuttgart, Department of Computer Science, Germany
- affiliation: TU Darmstadt, Department of Computer Science, Germany
- affiliation: ETH Zurich, Switzerland
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2020 – today
- 2024
[j19]Islem Bouzenia
, Bajaj Piyush Krishan, Michael Pradel:
DyPyBench: A Benchmark of Executable Python Software. Proc. ACM Softw. Eng. 1(FSE): 338-358 (2024)- [j18]Matteo Paltenghi, Michael Pradel:
Analyzing Quantum Programs with LintQ: A Static Analysis Framework for Qiskit. Proc. ACM Softw. Eng. 1(FSE): 2144-2166 (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] - [i39]Aryaz Eghbali, Michael Pradel:
De-Hallucinator: Iterative Grounding for LLM-Based Code Completion. CoRR abs/2401.01701 (2024) - [i38]Yiu Wai Chow, Luca Di Grazia, Michael Pradel:
PyTy: Repairing Static Type Errors in Python. CoRR abs/2401.06619 (2024) - [i37]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) - [i36]Islem Bouzenia, Bajaj Piyush Krishan, Michael Pradel:
DyPyBench: A Benchmark of Executable Python Software. CoRR abs/2403.00539 (2024) - [i35]Islem Bouzenia, Premkumar T. Devanbu, Michael Pradel:
RepairAgent: An Autonomous, LLM-Based Agent for Program Repair. CoRR abs/2403.17134 (2024) - [i34]Toufique Ahmed, Premkumar T. Devanbu, Christoph Treude, Michael Pradel:
Can LLMs Replace Manual Annotation of Software Engineering Artifacts? CoRR abs/2408.05534 (2024) - [i33]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) - [i32]Matteo Paltenghi, Michael Pradel:
A Survey on Testing and Analysis of Quantum Software. CoRR abs/2410.00650 (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]Marija Selakovic, Michael Pradel:
Performance issues and optimizations in JavaScript: an empirical study. ICSE 2016: 61-72 - [c28]Hui Liu, Qiurong Liu, Cristian-Alexandru Staicu, Michael Pradel, Yue Luo:
Nomen est omen: exploring and exploiting similarities between argument and parameter names. ICSE 2016: 1063-1073 - [c27]Markus Ermuth, Michael Pradel:
Monkey see, monkey do: effective generation of GUI tests with inferred macro events. ISSTA 2016: 82-93 - [c26]Tingting Yu, Michael Pradel:
SyncProf: detecting, localizing, and optimizing synchronization bottlenecks. ISSTA 2016: 389-400 - 2015
- [c25]Michael Pradel, Koushik Sen:
The Good, the Bad, and the Ugly: An Empirical Study of Implicit Type Conversions in JavaScript. ECOOP 2015: 519-541 - [c24]Michael Pradel, Parker Schuh, Koushik Sen:
TypeDevil: Dynamic Type Inconsistency Analysis for JavaScript. ICSE (1) 2015: 314-324 - [c23]Marija Selakovic, Michael Pradel:
Poster: Automatically Fixing Real-World JavaScript Performance Bugs. ICSE (2) 2015: 811-812 - [c22]Liang Gong, Michael Pradel, Manu Sridharan, Koushik Sen:
DLint: dynamically checking bad coding practices in JavaScript. ISSTA 2015: 94-105 - [c21]Luca Della Toffola, Michael Pradel, Thomas R. Gross:
Performance problems you can fix: a dynamic analysis of memoization opportunities. OOPSLA 2015: 607-622 - [c20]Michael Pradel, Markus Huggler, Thomas R. Gross:
Performance Regression Testing of Concurrent Classes. Software Engineering & Management 2015: 107 - [c19]Michael Pradel, Parker Schuh, George C. Necula, Koushik Sen:
EventBreak: Analyzing the Responsiveness of User Interfaces through Performance-Guided Test Generation. Software Engineering & Management 2015: 131 - [c18]Liang Gong, Michael Pradel, Koushik Sen:
JITProf: pinpointing JIT-unfriendly JavaScript code. ESEC/SIGSOFT FSE 2015: 357-368 - 2014
- [c17]Michael Pradel, Markus Huggler, Thomas R. Gross:
Performance regression testing of concurrent classes. ISSTA 2014: 13-25 - [c16]Michael Pradel, Parker Schuh, George C. Necula, Koushik Sen:
EventBreak: analyzing the responsiveness of user interfaces through performance-guided test generation. OOPSLA 2014: 33-47 - 2013
- [j2]Michael Pradel, Thomas R. Gross:
Name-Based Analysis of Equally Typed Method Arguments. IEEE Trans. Software Eng. 39(8): 1127-1143 (2013) - [c15]Michael Pradel, Thomas R. Gross:
Automatic testing of sequential and concurrent substitutability. ICSE 2013: 282-291 - [c14]Samira Tasharofi, Michael Pradel, Yu Lin, Ralph E. Johnson:
Bita: Coverage-guided, automatic testing of actor programs. ASE 2013: 114-124 - 2012
- [b1]Michael Pradel:
Program analyses for automatic and precise error detection. ETH Zurich, Zürich, Switzerland, 2012 - [c13]Michael Pradel, Thomas R. Gross:
Leveraging test generation and specification mining for automated bug detection without false positives. ICSE 2012: 288-298 - [c12]Adrian Nistor, Qingzhou Luo, Michael Pradel, Thomas R. Gross, Darko Marinov:
Ballerina: Automatic generation and clustering of efficient random unit tests for multithreaded code. ICSE 2012: 727-737 - [c11]Michael Pradel, Ciera Jaspan, Jonathan Aldrich, Thomas R. Gross:
Statically checking API protocol conformance with mined multi-object specifications. ICSE 2012: 925-935 - [c10]Michael Pradel, Severin Heiniger, Thomas R. Gross:
Static detection of brittle parameter typing. ISSTA 2012: 265-275 - [c9]Michael Pradel, Thomas R. Gross:
Fully automatic and precise detection of thread safety violations. PLDI 2012: 521-530 - 2011
- [c8]Michael Pradel, Thomas R. Gross:
Detecting anomalies in the order of equally-typed method arguments. ISSTA 2011: 232-242 - 2010
- [j1]Michael Pradel, Jakob Henriksson, Uwe Aßmann:
A Good Role Model for Ontologies: Collaborations. Int. J. Enterp. Inf. Syst. 6(1): 1-11 (2010) - [c7]Michael Pradel, Philipp Bichsel, Thomas R. Gross:
A framework for the evaluation of specification miners based on finite state machines. ICSM 2010: 1-10
2000 – 2009
- 2009
- [c6]Michael Pradel, Thomas R. Gross:
Automatic Generation of Object Usage Specifications from Large Method Traces. ASE 2009: 371-382 - [c5]Michael Pradel:
Dynamically inferring, refining, and checking API usage protocols. OOPSLA Companion 2009: 773-774 - 2008
- [c4]Michael Pradel, Martin Odersky:
Scala Roles - A Lightweight Approach Towards Reusable Collaborations. ICSOFT (PL/DPS/KE) 2008: 13-20 - [c3]Michael Pradel, Martin Odersky:
Scala Roles: Reusable Object Collaborations in a Library. ICSOFT (Selected Papers) 2008: 23-36 - [c2]Michael Pradel:
Ontology Composition using a Role Modeling Approach. Informatiktage 2008: 99-102 - [c1]Jakob Henriksson, Michael Pradel, Steffen Zschaler, Jeff Z. Pan:
Ontology Design and Reuse with Conceptual Roles. RR 2008: 104-118
Coauthor Index
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