2024

SWT-Bench: Testing and Validating Real-World Bug-Fixes with Code Agents
Niels Mündler, Mark Niklas Müller, Jingxuan He, Martin Vechev
NeurIPS 2024
Ward: Provable RAG Dataset Inference via LLM Watermarks
Nikola Jovanović, Robin Staab, Maximilian Baader, Martin Vechev
arXiv 2024
COMPL-AI Framework: A Technical Interpretation and LLM Benchmarking Suite for the EU Artificial Intelligence Act
Philipp Guldimann, Alexander Spiridonov, Robin Staab, Nikola Jovanović, Mark Vero, Velko Vechev, Anna Gueorguieva, Mislav Balunović, Nikola Konstantinov, Pavol Bielik, Petar Tsankov, Martin Vechev
arXiv 2024
Discovering Clues of Spoofed LM Watermarks
Thibaud Gloaguen, Nikola Jovanović, Robin Staab, Martin Vechev
arXiv 2024
A Unified Approach to Routing and Cascading for LLMs
Jasper Dekoninck, Maximilian Baader, Martin Vechev
ArXiv 2024
Practical Attacks against Black-box Code Completion Engines
Slobodan Jenko, Jingxuan He, Niels Mündler, Mark Vero, Martin Vechev
arXiv 2024
Polyrating: A Cost-Effective and Bias-Aware Rating System for LLM Evaluation
Jasper Dekoninck, Maximilian Baader, Martin Vechev
ArXiv 2024
CuTS: Customizable Tabular Synthetic Data Generation
Mark Vero, Mislav Balunović, Martin Vechev
ICML 2024
Watermark Stealing in Large Language Models
Nikola Jovanović, Robin Staab, Martin Vechev
ICML 2024 R2-FM@ICLR24 Oral
Instruction Tuning for Secure Code Generation
Jingxuan He*, Mark Vero*, Gabriela Krasnopolska, Martin Vechev
ICML 2024 * Equal contribution
Prompt Sketching for Large Language Models
Luca Beurer-Kellner, Mark Niklas Müller, Marc Fischer, Martin Vechev
ICML 2024
Guiding LLMs The Right Way: Fast, Non-Invasive Constrained Generation
Luca Beurer-Kellner, Marc Fischer, Martin Vechev
ICML 2024
A Synthetic Dataset for Personal Attribute Inference
Hanna Yukhymenko, Robin Staab, Mark Vero, Martin Vechev
NeurIPS Datasets and Benchmarks 2024
Modular Synthesis of Efficient Quantum Uncomputation
Hristo Venev, Timon Gehr, Dimitar Dimitrov, Martin Vechev
ACM OOPSLA 2024
DAGER: Exact Gradient Inversion for Large Language Models
Ivo Petrov, Dimitar I. Dimitrov, Maximilian Baader, Mark Niklas Müller, Martin Vechev
ArXiv 2024
ConStat: Performance-Based Contamination Detection in Large Language Models
Jasper Dekoninck, Mark Niklas Müller, Martin Vechev
NeurIPS 2024
From Principle to Practice: Vertical Data Minimization for Machine Learning
Robin Staab, Nikola Jovanović, Mislav Balunović, Martin Vechev
IEEE S&P 2024
Beyond Memorization: Violating Privacy Via Inference with Large Language Models
Robin Staab, Mark Vero, Mislav Balunović, Martin Vechev
ICLR 2024 Spotlight, 2024 PPPM-Award
Back to the Drawing Board for Fair Representation Learning
Angéline Pouget, Nikola Jovanović, Mark Vero, Robin Staab, Martin Vechev
arXiv 2024
Understanding Certified Training with Interval Bound Propagation
Yuhao Mao, Mark Niklas Müller, Marc Fischer, Martin Vechev
ICLR 2024
Black-Box Detection of Language Model Watermarks
Thibaud Gloaguen, Nikola Jovanović, Robin Staab, Martin Vechev
arXiv 2024
Hiding in Plain Sight: Disguising Data Stealing Attacks in Federated Learning
Kostadin Garov, Dimitar I. Dimitrov, Nikola Jovanović, Martin Vechev
ICLR 2024
Exploiting LLM Quantization
Kazuki Egashira, Mark Vero, Robin Staab, Jingxuan He, Martin Vechev
NeurIPS 2024 NextGenAISafety@ICML24 Oral
Controlled Text Generation via Language Model Arithmetic
Jasper Dekoninck, Marc Fischer, Luca Beurer-Kellner, Martin Vechev
ICLR 2024 Spotlight
Expressivity of ReLU-Networks under Convex Relaxations
Maximilian Baader*, Mark Niklas Müller*, Yuhao Mao, Martin Vechev
ICLR 2024 * Equal contribution
Private Attribute Inference from Images with Vision-Language Models
Batuhan Tömekçe, Mark Vero, Robin Staab, Martin Vechev
NeurIPS 2024
Synthetiq: Fast and Versatile Quantum Circuit Synthesis
Anouk Paradis*, Jasper Dekoninck*, Benjamin Bichsel, Martin Vechev
OOPSLA 2024 * Equal contribution
SPEAR: Exact Gradient Inversion of Batches in Federated Learning
Dimitar I. Dimitrov, Maximilian Baader, Mark Niklas Müller, Martin Vechev
ArXiv 2024
Overcoming the Paradox of Certified Training with Gaussian Smoothing
Stefan Balauca, Mark Niklas Müller, Yuhao Mao, Maximilian Baader, Marc Fischer, Martin Vechev
arXiv 2024
Large Language Models are Advanced Anonymizers
Robin Staab, Mark Vero, Mislav Balunović, Martin Vechev
arXiv 2024
Reqomp: Space-constrained Uncomputation for Quantum Circuits
Anouk Paradis, Benjamin Bichsel, Martin Vechev
Quantum Journal 2024
Evading Data Contamination Detection for Language Models is (too) Easy
Jasper Dekoninck, Mark Niklas Müller, Maximilian Baader, Marc Fischer, Martin Vechev
arXiv 2024

2023

Automated Classification of Model Errors on ImageNet
Momchil Peychev*, Mark Niklas Müller*, Marc Fischer, Martin Vechev
NeurIPS 2023 * Equal contribution
Connecting Certified and Adversarial Training
Yuhao Mao, Mark Niklas Müller, Marc Fischer, Martin Vechev
NeuIPS 2023
Group and Attack: Auditing Differential Privacy
Johan Lokna, Anouk Paradis, Dimitar I. Dimitrov, Martin Vechev
ACM CCS 2023
Large Language Models for Code: Security Hardening and Adversarial Testing
Jingxuan He, Martin Vechev
ACM CCS 2023 Distinguished Paper Award
Abstraqt: Analysis of Quantum Circuits via Abstract Stabilizer Simulation
Benjamin Bichsel, Anouk Paradis, Maximilian Baader, Martin Vechev
Quantum Journal 2023
TabLeak: Tabular Data Leakage in Federated Learning
Mark Vero, Mislav Balunović, Dimitar I. Dimitrov, Martin Vechev
ICML 2023
FARE: Provably Fair Representation Learning with Practical Certificates
Nikola Jovanović, Mislav Balunović, Dimitar I. Dimitrov, Martin Vechev
ICML 2023
LMQL Chat: Scripted Chatbot Development
Luca Beurer-Kellner*, Marc Fischer*, Martin Vechev
Neural Conversational AI Workshop, TEACH -- ICML 2023 * Equal contribution
Large Language Models are Zero-Shot Multi-Tool Users
Luca Beurer-Kellner*, Marc Fischer*, Martin Vechev
Knowlege and Logical Reasoning Workshop -- ICML 2023 * Equal contribution
Abstract Interpretation of Fixpoint Iterators with Applications to Neural Networks
Mark Niklas Müller, Marc Fischer, Robin Staab, Martin Vechev
PLDI 2023
Prompting Is Programming: A Query Language for Large Language Models
Luca Beurer-Kellner, Marc Fischer, Martin Vechev
PLDI 2023
Efficient Certified Training and Robustness Verification of Neural ODEs
Mustafa Zeqiri, Mark Niklas Müller, Marc Fischer, Martin Vechev
ICLR 2023
Certified Training: Small Boxes are All You Need
Mark Niklas Müller*, Franziska Eckert*, Marc Fischer, Martin Vechev
ICLR 2023 * Equal contribution Spotlight
Human-Guided Fair Classification for Natural Language Processing
Florian E. Dorner, Momchil Peychev, Nikola Konstantinov, Naman Goel, Elliott Ash, Martin Vechev
ICLR 2023 Spotlight

2022

(De-)Randomized Smoothing for Decision Stump Ensembles
Miklós Z. Horváth*, Mark Niklas Müller*, Marc Fischer, Martin Vechev
NeurIPS 2022 * Equal contribution
Learning to Configure Computer Networks with Neural Algorithmic Reasoning
Luca Beurer-Kellner, Martin Vechev, Laurent Vanbever, Petar Veličković
NeurIPS 2022
LAMP: Extracting Text from Gradients with Language Model Priors
Mislav Balunović*, Dimitar I. Dimitrov*, Nikola Jovanović, Martin Vechev
NeurIPS 2022 * Equal contribution
Zapper: Smart Contracts with Data and Identity Privacy
Samuel Steffen, Benjamin Bichsel, Martin Vechev
ACM CCS 2022 Distinguished Paper Award
Private and Reliable Neural Network Inference
Nikola Jovanović, Marc Fischer, Samuel Steffen, Martin Vechev
ACM CCS 2022
Latent Space Smoothing for Individually Fair Representations
Momchil Peychev, Anian Ruoss, Mislav Balunović, Maximilian Baader, Martin Vechev
ECCV 2022
On the Paradox of Certified Training
Nikola Jovanović*, Mislav Balunović*, Maximilian Baader, Martin Vechev
TMLR 2022 * Equal contribution
Data Leakage in Federated Averaging
Dimitar I. Dimitrov, Mislav Balunović, Nikola Konstantinov, Martin Vechev
TMLR 2022
Shared Certificates for Neural Network Verification
Marc Fischer*, Christian Sprecher*, Dimitar I. Dimitrov, Gagandeep Singh, Martin Vechev
CAV 2022 * Equal contribution
On Distribution Shift in Learning-based Bug Detectors
Jingxuan He, Luca Beurer-Kellner, Martin Vechev
ICML 2022
ZeeStar: Private Smart Contracts by Homomorphic Encryption and Zero-knowledge Proofs
Samuel Steffen, Benjamin Bichsel, Roger Baumgartner, Martin Vechev
IEEE S&P 2022
Fast and Optimal Sequence-to-Graph Alignment Guided by Seeds
Pesho Ivanov, Benjamin Bichsel, Martin Vechev
RECOMB 2022
Robust and Accurate - Compositional Architectures for Randomized Smoothing
Miklós Z. Horváth, Mark Niklas Müller, Marc Fischer, Martin Vechev
SRML@ICLR 2022
Boosting Randomized Smoothing with Variance Reduced Classifiers
Miklós Z. Horváth, Mark Niklas Müller, Marc Fischer, Martin Vechev
ICLR 2022 Spotlight
Complete Verification via Multi-Neuron Relaxation Guided Branch-and-Bound
Claudio Ferrari, Mark Niklas Müller, Nikola Jovanović, Martin Vechev
ICLR 2022
Provably Robust Adversarial Examples
Dimitar I. Dimitrov, Gagandeep Singh, Timon Gehr, Martin Vechev
ICLR 2022
Fair Normalizing Flows
Mislav Balunović, Anian Ruoss, Martin Vechev
ICLR 2022
Bayesian Framework for Gradient Leakage
Mislav Balunović, Dimitar I. Dimitrov, Robin Staab, Martin Vechev
ICLR 2022
PRIMA: General and Precise Neural Network Certification via Scalable Convex Hull Approximations
Mark Niklas Müller*, Gleb Makarchuk*, Gagandeep Singh, Markus Püschel, Martin Vechev
POPL 2022 * Equal contribution
The Fundamental Limits of Neural Networks for Interval Certified Robustness
Matthew Mirman, Maximilian Baader, Martin Vechev
TMLR 2022

2021

Automated Discovery of Adaptive Attacks on Adversarial Defenses
Chengyuan Yao, Pavol Bielik, Petar Tsankov, Martin Vechev
NeurIPS 2021
Learning to Explore Paths for Symbolic Execution
Jingxuan He, Gishor Sivanrupan, Petar Tsankov, Martin Vechev
ACM CCS 2021
Machine Learning for Health -- Algorithm Auditing & Quality Control
Luis Oala, Andrew G. Murchison, Pradeep Balachandran, Shruti Choudhary, Jana Fehr, Alixandro Werneck Leite, Peter G. Goldschmidt, Christian Johner, Elora D. M. Schorverth, Rose Nakasi, Martin Meyer, Federico Cabitza, Pat Baird, Carolin Prabhu, Eva Weicken, Xiaoxuan Liu, Markus Wenzel, Steffen Vogler, Darlington Akogo, Shada Alsalamah, Emre Kazim, Adriano Koshiyama, Sven Piechottka, Sheena Macpherson, Ian Shadforth, Regina Geierhofer, Christian Matek, Joachim Krois, Bruno Sanguinetti, Matthew Arentz, Pavol Bielik, Saul Calderon-Ramirez, Auss Abbood, Nicolas Langer, Stefan Haufe, Ferath Kherif, Sameer Pujari, Wojciech Samek, Thomas Wiegand
Journal of Medical Systems 2021
Robustness Certification for Point Cloud Models
Tobias Lorenz, Anian Ruoss, Mislav Balunović, Gagandeep Singh, Martin Vechev
ICCV 2021
Scalable Polyhedral Verification of Recurrent Neural Networks
Wonryong Ryou, Jiayu Chen, Mislav Balunović, Gagandeep Singh, Andrei Dan, Martin Vechev
CAV 2021
PODS: Policy Optimization via Differentiable Simulation
Miguel Angel Zamora Mora, Momchil Peychev, Sehoon Ha, Martin Vechev, Stelian Coros
ICML 2021
Scalable Certified Segmentation via Randomized Smoothing
Marc Fischer, Maximilian Baader, Martin Vechev
ICML 2021
Automated Discovery of Adaptive Attacks on Adversarial Defenses
Chengyuan Yao, Pavol Bielik, Petar Tsankov, Martin Vechev
AutoML@ICML 2021 Oral
TFix: Learning to Fix Coding Errors with a Text-to-Text Transformer
Berkay Berabi, Jingxuan He, Veselin Raychev, Martin Vechev
ICML 2021
Unqomp: Synthesizing Uncomputation in Quantum Circuits
Anouk Paradis, Benjamin Bichsel, Samuel Steffen, Martin Vechev
PLDI 2021
Learning to Find Naming Issues with Big Code and Small Supervision
Jingxuan He, Cheng-Chun Lee, Veselin Raychev, Martin Vechev
PLDI 2021
Fast and Precise Certification of Transformers
Gregory Bonaert, Dimitar I. Dimitrov, Maximilian Baader, Martin Vechev
PLDI 2021
Certify or Predict: Boosting Certified Robustness with Compositional Architectures
Mark Niklas Müller, Mislav Balunović, Martin Vechev
ICLR 2021
DP-Sniper: Black-Box Discovery of Differential Privacy Violations using Classifiers
Benjamin Bichsel, Samuel Steffen, Ilija Bogunovic, Martin Vechev
IEEE S&P 2021
Scaling Polyhedral Neural Network Verification on GPUs
Christoph Müller*, François Serre*, Gagandeep Singh, Markus Püschel, Martin Vechev
MLSys 2021 * Equal contribution
Robustness Certification with Generative Models
Matthew Mirman, Alexander Hägele, Timon Gehr, Pavol Bielik, Martin Vechev
PLDI 2021
Metha: Network Verifiers Need To Be Correct Too!
Rüdiger Birkner*, Tobias Brodmann*, Petar Tsankov, Laurent Vanbever, Martin Vechev
USENIX NSDI 2021 * Equal contribution
Efficient Certification of Spatial Robustness
Anian Ruoss, Maximilian Baader, Mislav Balunović, Martin Vechev
AAAI 2021

2020

Learning Certified Individually Fair Representations
Anian Ruoss, Mislav Balunović, Marc Fischer, Martin Vechev
NeurIPS 2020
Certified Defense to Image Transformations via Randomized Smoothing
Marc Fischer, Maximilian Baader, Martin Vechev
NeurIPS 2020
zkay v0.2: Practical Data Privacy for Smart Contracts
Nick Baumann, Samuel Steffen, Benjamin Bichsel, Petar Tsankov, Martin Vechev
arXiv 2020
Probabilistic Verification of Network Configurations
Samuel Steffen, Timon Gehr, Petar Tsankov, Laurent Vanbever, Martin Vechev
ACM SIGCOMM 2020 Best Student Paper Award
Adversarial Attacks on Probabilistic Autoregressive Forecasting Models
Raphaël Dang-Nhu, Gagandeep Singh, Pavol Bielik, Martin Vechev
ICML 2020
Learning Fast and Precise Numerical Analysis
Jingxuan He, Gagandeep Singh, Markus Püschel, Martin Vechev
PLDI 2020
λPSI: Exact Inference for Higher-order Probabilistic Programs
Timon Gehr, Samuel Steffen, Martin Vechev
PLDI 2020
Silq: A High-Level Quantum Language with Safe Uncomputation and Intuitive Semantics
Benjamin Bichsel, Maximilian Baader, Timon Gehr, Martin Vechev
PLDI 2020
Guiding Program Synthesis by Learning to Generate Examples
Larissa Laich, Pavol Bielik, Martin Vechev
ICLR 2020
Adversarial Training and Provable Defenses: Bridging the Gap
Mislav Balunović, Martin Vechev
ICLR 2020 Oral
Universal Approximation with Certified Networks
Maximilian Baader, Matthew Mirman, Martin Vechev
ICLR 2020
Config2Spec: Mining Network Specifications from Network Configurations
Rüdiger Birkner, Dana Drachsler-Cohen, Laurent Vanbever, Martin Vechev
NSDI 2020 2021 IETF/IRTF Applied Networking Research Prize
Adversarial Robustness for Code
Pavol Bielik, Martin Vechev
ACM ICML 2020
VerX: Safety Verification of Smart Contracts
Anton Permenev, Dimitar Dimitrov, Petar Tsankov, Dana Drachsler-Cohen, Martin Vechev
IEEE S&P 2020
AStarix: Fast and Optimal Sequence-to-Graph Alignment
Pesho Ivanov, Benjamin Bichsel, Harun Mustafa, André Kahles, Gunnar Rätsch, Martin Vechev
RECOMB 2020
Robustness Certification of Generative Models
Mathew Mirman, Timon Gehr, Martin Vechev
arXiv 2020

2019

Beyond the Single Neuron Convex Barrier for Neural Network Certification
Gagandeep Singh, Rupanshu Ganvir, Markus Püschel, Martin Vechev
NeurIPS 2019
Learning to Infer User Interface Attributes from Images
Philippe Schlattner, Pavol Bielik, Martin Vechev
ArXiv 2019
Certifying Geometric Robustness of Neural Networks
Mislav Balunović, Maximilian Baader, Gagandeep Singh, Timon Gehr, Martin Vechev
NeurIPS 2019
zkay: Specifying and Enforcing Data Privacy in Smart Contracts
Samuel Steffen, Benjamin Bichsel, Mario Gersbach, Noa Melchior, Petar Tsankov, Martin Vechev
ACM CCS 2019
Learning to Fuzz from Symbolic Execution with Application to Smart Contracts
Jingxuan He, Mislav Balunović, Nodar Ambroladze, Petar Tsankov, Martin Vechev
ACM CCS 2019
Online Robustness Training for Deep Reinforcement Learning
Marc Fischer, Matthew Mirman, Steven Stalder, Martin Vechev
arXiv 2019
DL2: Training and Querying Neural Networks with Logic
Marc Fischer, Mislav Balunović, Dana Drachsler-Cohen, Timon Gehr, Ce Zhang, Martin Vechev
ICML 2019
Unsupervised Learning of API Aliasing Specifications
Jan Eberhardt, Samuel Steffen, Veselin Raychev, Martin Vechev
PLDI 2019
Scalable Taint Specification Inference with Big Code
Victor Chibotaru, Benjamin Bichsel, Veselin Raychev, Martin Vechev
PLDI 2019
Boosting Robustness Certification of Neural Networks
Gagandeep Singh, Timon Gehr, Markus Püschel, Martin Vechev
ICLR 2019
A Provable Defense for Deep Residual Networks
Matthew Mirman, Gagandeep Singh, Martin Vechev
ArXiv 2019
An Abstract Domain for Certifying Neural Networks
Gagandeep Singh, Timon Gehr, Markus Püschel, Martin Vechev
ACM POPL 2019

2018

Fast and Effective Robustness Certification
Gagandeep Singh, Timon Gehr, Matthew Mirman, Markus Püschel, Martin Vechev
NIPS 2018
Learning to Solve SMT Formulas
Mislav Balunović, Pavol Bielik, Martin Vechev
NeurIPS 2018 Oral
Robust Relational Layouts Synthesis from Examples for Android
Pavol Bielik, Marc Fischer, Martin Vechev
ACM OOPSLA 2018
Securify: Practical Security Analysis of Smart Contracts
Petar Tsankov, Andrei Dan, Dana Drachsler-Cohen, Arthur Gervais, Florian Bünzli, Martin Vechev
ACM CCS 2018
DEBIN: Predicting Debug Information in Stripped Binaries
Jingxuan He, Pesho Ivanov, Petar Tsankov, Veselin Raychev, Martin Vechev
ACM CCS 2018
DP-Finder: Finding Differential Privacy Violations by Sampling and Optimization
Benjamin Bichsel, Timon Gehr, Dana Drachsler-Cohen, Petar Tsankov, Martin Vechev
ACM CCS 2018
NetHide: Secure and Practical Network Topology Obfuscation
Roland Meier, Petar Tsankov, Vincent Lenders, Laurent Vanbever, Martin Vechev
USENIX SECURITY 2018
Fast Numerical Program Analysis with Reinforcement Learning
Gagandeep Singh, Markus Püschel, Martin Vechev
CAV 2018
Training Neural Machines with Trace-Based Supervision
Matthew Mirman, Dimitar Dimitrov, Pavle Djordjevich, Timon Gehr, Martin Vechev
ICML 2018
Inferring Crypto API Rules from Code Changes
Rumen Paletov, Petar Tsankov, Veselin Raychev, Martin Vechev
PLDI 2018
Bayonet: Probabilistic Inference for Networks
Timon Gehr, Sasa Misailovic, Petar Tsankov, Laurent Vanbever, Pascal Wiesmann, Martin Vechev
PLDI 2018
Incremental Inference for Probabilistic Programs
Marco Cusumano-Towner, Benjamin Bichsel, Timon Gehr, Martin Vechev, Vikash K. Mansinghka
PLDI 2018
Static Serializability Analysis for Causal Consistency
Lucas Brutschy, Dimitar Dimitrov, Peter Müller, Martin Vechev
PLDI 2018
AI2: Safety and Robustness Certification of Neural Networks with Abstract Interpretation
Timon Gehr, Matthew Mirman, Dana Drachsler-Cohen, Petar Tsankov, Swarat Chaudhuri, Martin Vechev
IEEE S&P 2018
NetComplete: Practical Network-Wide Configuration Synthesis with Autocompletion
Ahmed El-Hassany, Petar Tsankov, Laurent Vanbever, Martin Vechev
NSDI 2018
Net2Text: Query-Guided Summarization of Network Forwarding Behaviors
Rüdiger Birkner, Dana Drachsler-Cohen, Laurent Vanbever, Martin Vechev
NSDI 2018
Fine-grained Semantics for Probabilistic Programs
Benjamin Bichsel, Timon Gehr, Martin Vechev
ESOP 2018
Practical Concurrent Traversals in Search Trees
Dana Drachsler-Cohen, Martin Vechev, and Eran Yahav
ACM PPoPP 2018
A Practical Construction for Decomposing Numerical Abstract Domains
Gagandeep Singh, Markus Püschel, Martin Vechev
ACM POPL 2018
Automatic Verification of RMA Programs via Abstraction Extrapolation
Cedric Baumann, Andrei Marian Dan, Yuri Meshman, Torsten Hoefler, Martin Vechev
VMCAI 2018

2017

Fast Polyhedra Abstract Domain
Gagandeep Singh, Markus Püschel, Martin Vechev
ACM POPL 2017
Synthesis of Probabilistic Privacy Enforcement
Martin Kucera, Petar Tsankov, Timon Gehr, Marco Guarnieri, Martin Vechev
ACM CCS 2017
Network-wide Configuration Synthesis
Ahmed El-Hassany, Petar Tsankov, Laurent Vanbever, Martin Vechev
CAV 2017
Finding Fix Locations for CFL-Reachability Analyses via Minimum Cuts
Andrei Dan, Manu Sridharan, Satish Chandra, Jean-Baptiste Jeannin, Martin Vechev
CAV 2017
Learning Disjunctions of Predicates
Nader H. Bshouty, Dana Drachsler-Cohen, Martin Vechev, Eran Yahav
COLT 2017
Serializability for Eventual Consistency: Criterion, Analysis, and Applications
Lucas Brutschy, Dimitar Dimitrov, Peter Müller, Martin Vechev
ACM POPL 2017
Learning a Static Analyzer from Data
Pavol Bielik, Veselin Raychev, Martin Vechev
CAV 2017
Program Synthesis for Character Level Language Modeling
Pavol Bielik, Veselin Raychev, Martin Vechev
ICLR 2017

2016

Functionality-Aware Security Enforcement
Petar Tsankov, Marco Pistoia, Omer Tripp, Martin Vechev, Pietro Ferrara
ACM ACSAC 2016
Probabilistic Model for Code with Decision Trees
Veselin Raychev, Pavol Bielik, Martin Vechev
ACM OOPSLA 2016
Learning Programs from Noisy Data
Veselin Raychev, Pavol Bielik, Martin Vechev, Andreas Krause
ACM POPL 2016
PSI: Exact Symbolic Inference for Probabilistic Programs
Timon Gehr, Sasa Misailovic, Martin Vechev
CAV 2016
SDNRacer: Concurrency Analysis for Software-Defined Networks
Ahmed El-Hassany, Jeremie Miserez, Pavol Bielik, Laurent Vanbever, Martin Vechev
ACM PLDI 2016
Modeling and Analysis of Remote Memory Access Programming
Andrei Dan, Patrick Lam, Torsten Hoefler, Martin Vechev
ACM OOPSLA 2016
PHOG: Probabilistic Model for Code
Pavol Bielik, Veselin Raychev, Martin Vechev
ACM ICML 2016
Statistical Deobfuscation of Android Applications
Benjamin Bichsel, Veselin Raychev, Peter Tsankov, Martin Vechev
ACM CCS 2016

2015

Making Numerical Program Analysis Fast
Gagandeep Singh, Markus Püschel, Martin Vechev
ACM PLDI 2015
Predicting Program Properties from "Big Code"
Veselin Raychev, Martin Vechev, Andreas Krause
ACM POPL 2015
An Interactive System for Data Structure Development
Jibin Ou, Otmar Hilliges, Martin Vechev
ACM CHI 2015
SDNRacer: Detecting Concurrency Violations in Software-Defined Networks
Jeremie Miserez, Pavol Bielik, Ahmed El-Hassany, Laurent Vanbever, Martin Vechev
SOSR 2015
Stateless Model Checking of Event-Driven Applications
Casper Svenning Jensen, Anders Møller, Veselin Raychev, Dimitar Dimitrov, Martin Vechev
ACM OOPSLA 2015
Learning Commutativity Specifications
Timon Gehr, Dimitar Dimitrov, Martin Vechev
CAV 2015
Race Detection in Two Dimensions
Dimitar Dimitrov, Martin Vechev, Vivek Sarkar
ACM SPAA 2015
Effective Abstractions for Verification under Relaxed Memory Models
Andrei Dan, Yuri Meshman, Martin Vechev, Eran Yahav
VMCAI 2015
Scalable Race Detection for Android Applications
Pavol Bielik, Veselin Raychev, Martin Vechev
ACM OOPSLA 2015
Programming with Big Code: Lessons, Techniques and Applications
Pavol Bielik, Veselin Raychev, Martin Vechev
SNAPL 2015

2014

Verifying Atomicity via Data Independence
Ohad Shacham, Eran Yahav, Guy Gueta, Alex Aiken, Nathan Bronson, Mooly Sagiv and Martin Vechev
ISSTA 2014
Code Completion with Statistical Language Models
Veselin Raychev, Martin Vechev, Eran Yahav
ACM PLDI 2014
Synthesis of Memory Fences via Refinement Propagation
Yuri Meshman, Andrei Dan, Martin Vechev, Eran Yahav
SAS 2014
Phrase-Based Statistical Translation of Programming Languages
Svetoslav Karaivanov, Veselin Raychev, Martin Vechev
Onward 2014
Practical Concurrent Binary Search Trees via Logical Ordering
Dana Drachsler, Martin Vechev and Eran Yahav
ACM PPoPP 2014
Commutativity Race Detection
Dimitar Dimitrov, Veselin Raychev, Martin Vechev, Eric Koskinen
ACM PLDI 2014

2013

Refactoring with Synthesis
Veselin Raychev, Max Schaefer, Manu Sridharan, Martin Vechev
ACM OOPSLA 2013
Effective Race Detection for Event-Driven Programs
Veselin Raychev, Martin Vechev, Manu Sridharan
ACM OOPSLA 2013
Automatic Synthesis of Deterministic Concurrency
Veselin Raychev, Martin Vechev, Eran Yahav
Static Analysis Symposium (SAS) 2013
Predicate Abstraction for Relaxed Memory Models
Andrei Dan, Yuri Meshman, Martin Vechev, Eran Yahav
Static Analysis Symposium (SAS) 2013

2012

Scalable and Precise Dynamic Datarace Detection for Structured Parallelism
Raghavan Raman, Jisheng Zhao, Vivek Sarkar, Martin Vechev, Eran Yahav
ACM PLDI 2012
Race Detection for Web Applications
Boris Petrov, Martin Vechev, Manu Sridharan, Julian Dolby
ACM PLDI 2012
Dynamic Synthesis for Relaxed Memory Models
Feng Liu, Nayden Nedev, Nedyalko Prisadnikov, Martin Vechev, Eran Yahav
ACM PLDI 2012

2011

Testing Atomicity of Composed Concurrent Operations
Ohad Shacham, Nathan Bronson, Alex Aiken, Mooly Sagiv, Martin Vechev and Eran Yahav
ACM OOPSLA 2011
Sprint: Speculative Prefetching of Remote Data
Arun Raman, Greta Yorsh, Martin Vechev and Eran Yahav
ACM OOPSLA 2011
Partial-Coherence Abstractions for Relaxed Memory Models
Michael Kuperstein, Martin Vechev and Eran Yahav
ACM PLDI 2011
Laws of Order: Expensive Synchronization in Concurrent Algorithms Cannot be Eliminated
Hagit Attiya, Rachid Guerraoui, Danny Hendler, Petr Kuznetsov, Maged M. Michael and Martin Vechev
ACM POPL, ACM TOPLAS 2011
QVM: An Efficient Runtime for Detecting Defects in Deployed Systems
Mathew Arnold, Martin Vechev, Eran Yahav
ACM TOSEM (ACM Transactions on Software Engineering and Methodology) 2011
Asynchronous Assertions
Eddie Aftandilian, Samuel Guyer, Martin Vechev and Eran Yahav
ACM OOPSLA 2011

2010

Parallel Checking of Expressive Heap Assertions
Martin Vechev, Eran Yahav and Greta Yorsh
ACM ISMM 2010
Automatic Verification of Determinism for Structured Parallel Programs
Martin Vechev, Eran Yahav, Raghavan Raman and Vivek Sarkar
Static Analysis Symposium (SAS) 2010
Abstraction-Guided Synthesis Of Synchronization
Martin Vechev, Eran Yahav and Greta Yorsh
ACM POPL 2010
Efficient Data Race Detection for Async-Finish Parallelism
Raghavan Raman, Jisheng Zhao, Vivek Sarkar, Martin Vechev and Eran Yahav
Runtime Verification (RV) 2010 Best Paper Award
Verifying Linearizability with Hindsight
Peter O'Hearn, Noam Rinetzky, Martin Vechev, Eran Yahav and Greta Yorsh
ACM PODC 2010
Automatic Inference of Memory Fences
Michael Kuperstein, Martin Vechev and Eran Yahav
Formal Methods in Computer Aided Design (FMCAD) 2010

2009

Inferring Synchronization under Limited Observability
Martin Vechev, Eran Yahav, Greta Yorsh
TACAS 2009
Experience with Model Checking Linearizability
Martin Vechev, Eran Yahav, Greta Yorsh
SPIN 2009
Chameleon: Adaptive Selection of Collections
Ohad Shacham, Martin Vechev, Eran Yahav
ACM PLDI 2009
Idempotent Work Stealing
Maged Michael, Martin Vechev, Vijay Saraswat
ACM PPoPP 2009
Position Paper: Verifying Optimistic Algorithms Should be Easy
Noam Rinetzky, Martin Vechev, Eran Yahav and Greta Yorsh
EC2: Exploiting Concurrency Efficiently and Correctly -- CAV Workshop 2009

2008

Position Paper: Computer-Assisted Construction of Efficient Concurrent Algorithms
Martin Vechev, Eran Yahav, Maged Michael, Hagit Attiya, Greta Yorsh
EC2: Exploiting Concurrency Efficiently and Correctly -- CAV Workshop 2008
QVM: An Efficient Runtime for Detecting Defects in Deployed Systems
Mathew Arnold, Martin Vechev, Eran Yahav
ACM OOPSLA 2008

2007

CGCExplorer: A Semi-Automated Search Procedure for Provably Correct Concurrent Collectors
Martin Vechev, Eran Yahav, David F. Bacon and Noam Rinetzky
ACM PLDI 2007

2006

Correctness-Preserving Derivation of Concurrent Garbage Collection Algorithms
Martin Vechev, Eran Yahav, David F. Bacon
ACM PLDI 2006

2005

CDerivation And Evaluation Of Concurrent Collectors
Martin Vechev, David F. Bacon, Perry Cheng, David Grove
ECOOP 2005
Syncopation: Generational Real-time Garbage Collection in the Metronome
David F. Bacon, Perry Cheng, David Grove, Martin Vechev
ACM LCTES 2005
High-level Real-time Programming in Java
David F. Bacon, Perry Cheng, David Grove, Michael Hind, V.T. Rajan, Eran Yahav, M. Hauswirth, C. Kirsch, Daniel Spoonhower, and Martin T. Vechev
ACM EMSOFT 2005

2004

Write Barrier Elision for Concurrent Garbage Collectors
Martin Vechev and David F. Bacon
ACM ISMM 2004
Tuning Java on a DSP
Martin Vechev and Peter Petrov
GSPX 2004

2003

Java on DSP : Challenges and Choices
Martin Vechev and Peter Petrov
GSPX 2003