Corina S. Pasareanu

ORCID

Publication Activity (10 Years)

Years Active: 1998-2024
Publications (10 Years): 128

Top Venues

CoRR

ACM SIGSOFT Softw. Eng. Notes

ISSTA

ICSE (Companion Volume)

Publications

Ravi Mangal, Nina Narodytska, Divya Gopinath, Boyue Caroline Hu, Anirban Roy, Susmit Jha, Corina S. Pasareanu
Concept-based Analysis of Neural Networks via Vision-Language Models. CoRR (2024)
Radu Calinescu, Calum Imrie, Ravi Mangal, Genaína Nunes Rodrigues, Corina S. Pasareanu, Misael Alpizar Santana, Gricel Vázquez
Controller Synthesis for Autonomous Systems With Deep-Learning Perception Components. IEEE Trans. Software Eng. 50 (6) (2024)
Eduard Pinconschi, Divya Gopinath, Rui Abreu, Corina S. Pasareanu
Evaluating Deep Neural Networks in Deployment (A Comparative and Replicability Study). CoRR (2024)
Amirfarhad Nilizadeh, Gary T. Leavens, Corina S. Pasareanu, Yannic Noller
JMLKelinci+: Detecting Semantic Bugs and Covering Branches with Valid Inputs Using Coverage-guided Fuzzing and Runtime Assertion Checking. Formal Aspects Comput. 36 (1) (2024)
Nils Palumbo, Ravi Mangal, Zifan Wang, Saranya Vijayakumar, Corina S. Pasareanu, Somesh Jha
Mechanistically Interpreting a Transformer-based 2-SAT Solver: An Axiomatic Approach. CoRR (2024)
Ismet Burak Kadron, Yannic Noller, Rohan Padhye, Tevfik Bultan, Corina S. Pasareanu, Koushik Sen
Fuzzing, Symbolic Execution, and Expert Guidance for Better Testing. IEEE Softw. 41 (1) (2024)
Dat Nguyen, Hieu M. Vu, Cong-Thanh Le, Bach Le, David Lo, Corina S. Pasareanu
Inferring Properties of Graph Neural Networks. CoRR (2024)
Corina S. Pasareanu, Ravi Mangal, Divya Gopinath, Sinem Getir Yaman, Calum Imrie, Radu Calinescu, Huafeng Yu
Closed-Loop Analysis of Vision-Based Autonomous Systems: A Case Study. CAV (1) (2023)
Corina S. Pasareanu, Ravi Mangal, Divya Gopinath, Huafeng Yu
Assumption Generation for Learning-Enabled Autonomous Systems. RV (2023)
Marieke Huisman, Corina S. Pasareanu, Naijun Zhan
Introduction to the Special Section on FM 2021. Formal Aspects Comput. 35 (2) (2023)
Muhammad Usman, Youcheng Sun, Divya Gopinath, Rishi Dange, Luca Manolache, Corina S. Pasareanu
An overview of structural coverage metrics for testing neural networks. Int. J. Softw. Tools Technol. Transf. 25 (3) (2023)
Chi Zhang, Zifan Wang, Ravi Mangal, Matt Fredrikson, Limin Jia, Corina S. Pasareanu
Transfer Attacks and Defenses for Large Language Models on Coding Tasks. CoRR (2023)
Sofia Reis, Corina S. Pasareanu, Rui Abreu, Hakan Erdogmus
SECOMlint: A linter for Security Commit Messages. CoRR (2023)
Divya Gopinath, Luca Lungeanu, Ravi Mangal, Corina S. Pasareanu, Siqi Xie, Huanfeng Yu
Feature-Guided Analysis of Neural Networks. FASE (2023)
Corina S. Pasareanu, Ravi Mangal, Divya Gopinath, Huafeng Yu
Assumption Generation for the Verification of Learning-Enabled Autonomous Systems. CoRR (2023)
Ravi Mangal, Klas Leino, Zifan Wang, Kai Hu, Weicheng Yu, Corina S. Pasareanu, Anupam Datta, Matt Fredrikson
Robustness Still Worthwhile? CoRR (2023)
Haoze Wu, Teruhiro Tagomori, Alexander Robey, Fengjun Yang, Nikolai Matni, George J. Pappas, Hamed Hassani, Corina S. Pasareanu, Clark W. Barrett
Toward Certified Robustness Against Real-World Distribution Shifts. SaTML (2023)
Elena Sherman, Yannic Noller, Cyrille Artho, Franck van Breugel, Anto Nanah Ji, John Kellerman, Parssa Khazra, Filip Kliber, Gaurang Kudale, Pavel Parízek, Corina S. Pasareanu, Ron Pressler, Matt Walker, Hongru Wang, Qiuchen Yan
The Java Pathfinder Workshop 2022. ACM SIGSOFT Softw. Eng. Notes 48 (1) (2023)
Corina S. Pasareanu, Ravi Mangal, Divya Gopinath, Sinem Getir Yaman, Calum Imrie, Radu Calinescu, Huafeng Yu
Closed-loop Analysis of Vision-based Autonomous Systems: A Case Study. CoRR (2023)
Muhammad Usman, Youcheng Sun, Divya Gopinath, Corina S. Pasareanu
Rule-Based Testing of Neural Networks. SE4SafeML@SIGSOFT FSE (2023)
Eduard Pinconschi, Sofia Reis, Chi Zhang, Rui Abreu, Hakan Erdogmus, Corina S. Pasareanu, Limin Jia
Tenet: A Flexible Framework for Machine-Learning-based Vulnerability Detection. CAIN (2023)
Sofia Reis, Rui Abreu, Corina S. Pasareanu
Are security commit messages informative? Not enough! EASE (2023)
Ravi Mangal, Zifan Wang, Chi Zhang, Klas Leino, Corina S. Pasareanu, Matt Fredrikson
On the Perils of Cascading Robust Classifiers. ICLR (2023)
Hong Jin Kang, Pattarakrit Rattanukul, Stefanus Agus Haryono, Truong Giang Nguyen, Chaiyong Ragkhitwetsagul, Corina S. Pasareanu, David Lo
SkipFuzz: Active Learning-based Input Selection for Fuzzing Deep Learning Libraries. CoRR (2022)
Radu Calinescu, Calum Imrie, Ravi Mangal, Corina S. Pasareanu, Misael Alpizar Santana, Gricel Vázquez
Discrete-Event Controller Synthesis for Autonomous Systems with Deep-Learning Perception Components. CoRR (2022)
Ravi Mangal, Corina S. Pasareanu
A Cascade of Checkers for Run-time Certification of Local Robustness. NSV/FoMLAS@CAV (2022)
Marieke Huisman, Corina S. Pasareanu, Naijun Zhan
Preface for the formal methods in system design special issue on 'Formal Methods 2021'. Formal Methods Syst. Des. 61 (1) (2022)
Muhammad Usman, Divya Gopinath, Youcheng Sun, Corina S. Pasareanu
Rule-Based Runtime Mitigation Against Poison Attacks on Neural Networks. RV (2022)
Hadar Frenkel, Orna Grumberg, Corina S. Pasareanu, Sarai Sheinvald
Assume, Guarantee or Repair - A Regular Framework for Non Regular Properties (full version). CoRR (2022)
Sofia Reis, Rui Abreu, Hakan Erdogmus, Corina S. Pasareanu
SECOM: Towards a convention for security commit messages. MSR (2022)
Klas Leino, Aymeric Fromherz, Ravi Mangal, Matt Fredrikson, Bryan Parno, Corina S. Pasareanu
Self-correcting Neural Networks for Safe Classification. NSV/FoMLAS@CAV (2022)
Muhammad Usman, Youcheng Sun, Divya Gopinath, Rishi Dange, Luca Manolache, Corina S. Pasareanu
An Overview of Structural Coverage Metrics for Testing Neural Networks. CoRR (2022)
Haoze Wu, Teruhiro Tagomori, Alexander Robey, Fengjun Yang, Nikolai Matni, George J. Pappas, Hamed Hassani, Corina S. Pasareanu, Clark W. Barrett
Toward Certified Robustness Against Real-World Distribution Shifts. CoRR (2022)
Hadar Frenkel, Orna Grumberg, Corina S. Pasareanu, Sarai Sheinvald
Assume, guarantee or repair: a regular framework for non regular properties. Int. J. Softw. Tools Technol. Transf. 24 (5) (2022)
Youcheng Sun, Muhammad Usman, Divya Gopinath, Corina S. Pasareanu
VPN: Verification of Poisoning in Neural Networks. NSV/FoMLAS@CAV (2022)
Klas Leino, Chi Zhang, Ravi Mangal, Matt Fredrikson, Bryan Parno, Corina S. Pasareanu
Degradation Attacks on Certifiably Robust Neural Networks. Trans. Mach. Learn. Res. 2022 (2022)
Ravi Mangal, Zifan Wang, Chi Zhang, Klas Leino, Corina S. Pasareanu, Matt Fredrikson
On the Perils of Cascading Robust Classifiers. CoRR (2022)
Youcheng Sun, Muhammad Usman, Divya Gopinath, Corina S. Pasareanu
VPN: Verification of Poisoning in Neural Networks. CoRR (2022)
Hong Jin Kang, Truong Giang Nguyen, Bach Le, Corina S. Pasareanu, David Lo
Test mimicry to assess the exploitability of library vulnerabilities. ISSTA (2022)
Muhammad Usman, Youcheng Sun, Divya Gopinath, Corina S. Pasareanu
AntidoteRT: Run-time Detection and Correction of Poison Attacks on Neural Networks. CoRR (2022)
Corina S. Pasareanu, Andreas Zeller
IEEE International Conference on Software Testing, Verification and Validation (ICST 2020). Softw. Test. Verification Reliab. 32 (5) (2022)
Klas Leino, Aymeric Fromherz, Ravi Mangal, Matt Fredrikson, Bryan Parno, Corina S. Pasareanu
Self-Repairing Neural Networks: Provable Safety for Deep Networks via Dynamic Repair. CoRR (2021)
Muhammad Usman, Divya Gopinath, Youcheng Sun, Yannic Noller, Corina S. Pasareanu
NNrepair: Constraint-Based Repair of Neural Network Classifiers. CAV (1) (2021)
Muhammad Usman, Yannic Noller, Corina S. Pasareanu, Youcheng Sun, Divya Gopinath
NEUROSPF: A tool for the Symbolic Analysis of Neural Networks. CoRR (2021)
David Coimbra, Sofia Reis, Rui Abreu, Corina S. Pasareanu, Hakan Erdogmus
On using distributed representations of source code for the detection of C security vulnerabilities. CoRR (2021)
Muhammad Usman, Divya Gopinath, Youcheng Sun, Yannic Noller, Corina S. Pasareanu
NNrepair: Constraint-based Repair of Neural Network Classifiers. CoRR (2021)
Amirfarhad Nilizadeh, Gary T. Leavens, Corina S. Pasareanu
Using a Guided Fuzzer and Preconditions to Achieve Branch Coverage with Valid Inputs. TAP@STAF (2021)
Ismet Burak Kadron, Divya Gopinath, Corina S. Pasareanu, Huafeng Yu
Case Study: Analysis of Autonomous Center Line Tracking Neural Networks. VSTTE (2021)
Amirfarhad Nilizadeh, Gary T. Leavens, Xuan-Bach Dinh Le, Corina S. Pasareanu, David R. Cok
Exploring True Test Overfitting in Dynamic Automated Program Repair using Formal Methods. ICST (2021)
Muhammad Usman, Yannic Noller, Corina S. Pasareanu, Youcheng Sun, Divya Gopinath
NEUROSPF: A Tool for the Symbolic Analysis of Neural Networks. ICSE (Companion Volume) (2021)
Aymeric Fromherz, Klas Leino, Matt Fredrikson, Bryan Parno, Corina S. Pasareanu
Fast Geometric Projections for Local Robustness Certification. ICLR (2021)
Yoshiki Takashima, Ruben Martins, Limin Jia, Corina S. Pasareanu
SyRust: automatic testing of Rust libraries with semantic-aware program synthesis. PLDI (2021)
Muhammad Usman, Divya Gopinath, Corina S. Pasareanu
QuantifyML: How Good is my Machine Learning Model? FMAS (2021)
Zichao Zhang, Arthur Azevedo de Amorim, Limin Jia, Corina S. Pasareanu
Learning Assumptions for Verifying Cryptographic Protocols Compositionally. FACS (2021)
Colin Paterson, Haoze Wu, John Grese, Radu Calinescu, Corina S. Pasareanu, Clark W. Barrett
DeepCert: Verification of Contextually Relevant Robustness for Neural Network Image Classifiers. CoRR (2021)
Colin Paterson, Haoze Wu, John Grese, Radu Calinescu, Corina S. Pasareanu, Clark W. Barrett
DeepCert: Verification of Contextually Relevant Robustness for Neural Network Image Classifiers. SAFECOMP (2021)
Edward Kim, Divya Gopinath, Corina S. Pasareanu, Sanjit A. Seshia
A Programmatic and Semantic Approach to Explaining and Debugging Neural Network Based Object Detectors. CVPR (2020)
Hadar Frenkel, Orna Grumberg, Corina S. Pasareanu, Sarai Sheinvald
Assume, Guarantee or Repair. TACAS (1) (2020)
Cyrille Artho, Quoc-Sang Phan, Peter Aldous, Alyas Almaawi, Lucas Bang, Lasse Berglund, Tevfik Bultan, Zhenbang Chen, Hayes Converse, Wei Dong, William Eiers, Milos Gligoric, Simon Goldsmith, Lars Grunske, Joshua Hooker, Ismet Burak Kadron, Timo Kehrer, Sarfraz Khurshid, Xuan-Bach Dinh Le, David Lo, Eric Mercer, Sasa Misailovic, Egor Namakonov, Hoang Lam Nguyen, Yannic Noller, Benjamin Ogles, Rohan Padhye, Pavel Parízek, Corina S. Pasareanu, Sheridan Jacob Powell, Seemanta Saha, Koushik Sen, Elena Sherman, Kyle Storey, Minxing Tang, Willem Visser, Ji Wang, Hengbiao Yu
The Java Pathfinder Workshop 2019. ACM SIGSOFT Softw. Eng. Notes 45 (2) (2020)
Corina S. Pasareanu
SafeDNN: understanding and verifying neural networks (keynote). A-TEST@ESEC/SIGSOFT FSE (2020)
Shirin Nilizadeh, Yannic Noller, Corina S. Pasareanu
DifFuzz: Differential Fuzzing for Side-Channel Analysis. SE (2020)
Yannic Noller, Corina S. Pasareanu, Marcel Böhme, Youcheng Sun, Hoang Lam Nguyen, Lars Grunske
HyDiff: hybrid differential software analysis. ICSE (2020)
Haoze Wu, Alex Ozdemir, Aleksandar Zeljic, Kyle Julian, Ahmed Irfan, Divya Gopinath, Sadjad Fouladi, Guy Katz, Corina S. Pasareanu, Clark W. Barrett
Parallelization Techniques for Verifying Neural Networks. FMCAD (2020)
Corina S. Pasareanu, Hayes Converse, Antonio Filieri, Divya Gopinath
On the probabilistic analysis of neural networks. SEAMS@ICSE (2020)
Zichao Zhang, Arthur Azevedo de Amorim, Limin Jia, Corina S. Pasareanu
Automating Compositional Analysis of Authentication Protocols. FMCAD (2020)
Hayes Converse, Antonio Filieri, Divya Gopinath, Corina S. Pasareanu
Probabilistic Symbolic Analysis of Neural Networks. ISSRE (2020)
Haoze Wu, Alex Ozdemir, Aleksandar Zeljic, Ahmed Irfan, Kyle Julian, Divya Gopinath, Sadjad Fouladi, Guy Katz, Corina S. Pasareanu, Clark W. Barrett
Parallelization Techniques for Verifying Neural Networks. CoRR (2020)
Aymeric Fromherz, Klas Leino, Matt Fredrikson, Bryan Parno, Corina S. Pasareanu
Fast Geometric Projections for Local Robustness Certification. CoRR (2020)
Kasper Søe Luckow, Rody Kersten, Corina S. Pasareanu
Complexity vulnerability analysis using symbolic execution. Softw. Test. Verification Reliab. 30 (7-8) (2020)
Divya Gopinath, Mengshi Zhang, Kaiyuan Wang, Ismet Burak Kadron, Corina S. Pasareanu, Sarfraz Khurshid
Symbolic Execution for Importance Analysis and Adversarial Generation in Neural Networks. ISSRE (2019)
Guowei Yang, Rui Qiu, Sarfraz Khurshid, Corina S. Pasareanu, Junye Wen
A synergistic approach to improving symbolic execution using test ranges. Innov. Syst. Softw. Eng. 15 (3-4) (2019)
Divya Gopinath, Hayes Converse, Corina S. Pasareanu, Ankur Taly
Property Inference for Deep Neural Networks. ASE (2019)
Yannic Noller, Rody Kersten, Corina S. Pasareanu
Badger: Complexity Analysis with Fuzzing and Symbolic Execution. SE/SWM (2019)
Corina S. Pasareanu, Rody Kersten, Kasper Søe Luckow, Quoc-Sang Phan
Chapter Six - Symbolic Execution and Recent Applications to Worst-Case Execution, Load Testing, and Security Analysis. Adv. Comput. 113 (2019)
Shirin Nilizadeh, Yannic Noller, Corina S. Pasareanu
DifFuzz: differential fuzzing for side-channel analysis. ICSE (2019)
Edward Kim, Divya Gopinath, Corina S. Pasareanu, Sanjit A. Seshia
A Programmatic and Semantic Approach to Explaining and DebuggingNeural Network Based Object Detectors. CoRR (2019)
Xuan-Bach Dinh Le, Corina S. Pasareanu, Rohan Padhye, David Lo, Willem Visser, Koushik Sen
Saffron: Adaptive Grammar-based Fuzzing for Worst-Case Analysis. ACM SIGSOFT Softw. Eng. Notes 44 (4) (2019)
Yannic Noller, Corina S. Pasareanu, Aymeric Fromherz, Xuan-Bach Dinh Le, Willem Visser
Symbolic Pathfinder for SV-COMP - (Competition Contribution). TACAS (3) (2019)
Divya Gopinath, Corina S. Pasareanu, Kaiyuan Wang, Mengshi Zhang, Sarfraz Khurshid
Symbolic execution for attribution and attack synthesis in neural networks. ICSE (Companion Volume) (2019)
Xuan-Bach Dinh Le, Lingfeng Bao, David Lo, Xin Xia, Shanping Li, Corina S. Pasareanu
On reliability of patch correctness assessment. ICSE (2019)
Divya Gopinath, Ankur Taly, Hayes Converse, Corina S. Pasareanu
Finding Invariants in Deep Neural Networks. CoRR (2019)
Heron Yang, Robert Morris, Corina S. Pasareanu
Analysing the effect of uncertainty in airport surface operations. ISSTA/ECOOP Workshops (2018)
Corina S. Pasareanu, Divya Gopinath, Huafeng Yu
Compositional Verification for Autonomous Systems with Deep Learning Components. CoRR (2018)
Karam Abd Elkader, Orna Grumberg, Corina S. Pasareanu, Sharon Shoham
Automated circular assume-guarantee reasoning. Formal Aspects Comput. 30 (5) (2018)
Yannic Noller, Rody Kersten, Corina S. Pasareanu
Badger: Complexity Analysis with Fuzzing and Symbolic Execution. CoRR (2018)
Sarfraz Khurshid, Corina S. Pasareanu, Willem Visser
Test input generation with Java PathFinder: then and now (invited talk abstract). ISSTA (2018)
Tegan Brennan, Seemanta Saha, Tevfik Bultan, Corina S. Pasareanu
Symbolic path cost analysis for side-channel detection. ISSTA (2018)
Yannic Noller, Rody Kersten, Corina S. Pasareanu
Badger: complexity analysis with fuzzing and symbolic execution. ISSTA (2018)
Pasquale Malacaria, M. H. R. Khouzani, Corina S. Pasareanu, Quoc-Sang Phan, Kasper Søe Luckow
Symbolic Side-Channel Analysis for Probabilistic Programs. CSF (2018)
Divya Gopinath, Kaiyuan Wang, Mengshi Zhang, Corina S. Pasareanu, Sarfraz Khurshid
Symbolic Execution for Deep Neural Networks. CoRR (2018)
Pasquale Malacaria, M. H. R. Khouzani, Corina S. Pasareanu, Quoc-Sang Phan, Kasper Søe Luckow
Symbolic Side-Channel Analysis for Probabilistic Programs. IACR Cryptol. ePrint Arch. 2018 (2018)
Kasper Søe Luckow, Corina S. Pasareanu, Willem Visser
Monte Carlo Tree Search for Finding Costly Paths in Programs. SEFM (2018)
Rui Qiu, Sarfraz Khurshid, Corina S. Pasareanu, Junye Wen, Guowei Yang
Using Test Ranges to Improve Symbolic Execution. NFM (2018)
Andrew Hill, Corina S. Pasareanu, Kathryn T. Stolee
Automated program repair with canonical constraints. ICSE (Companion Volume) (2018)
Divya Gopinath, Guy Katz, Corina S. Pasareanu, Clark W. Barrett
DeepSafe: A Data-Driven Approach for Assessing Robustness of Neural Networks. ATVA (2018)
Shirin Nilizadeh, Yannic Noller, Corina S. Pasareanu
DifFuzz: Differential Fuzzing for Side-Channel Analysis. CoRR (2018)
Willem Visser, Corina S. Pasareanu
Probabilistic programming for Java using symbolic execution and model counting. SAICSIT (2017)
Quoc-Sang Phan, Lucas Bang, Corina S. Pasareanu, Pasquale Malacaria, Tevfik Bultan
Synthesis of Adaptive Side-Channel Attacks. IACR Cryptol. ePrint Arch. 2017 (2017)
Divya Gopinath, Guy Katz, Corina S. Pasareanu, Clark W. Barrett
DeepSafe: A Data-driven Approach for Checking Adversarial Robustness in Neural Networks. CoRR (2017)
Huafeng Yu, Stanley Bak, Xin Li, Corina S. Pasareanu, Ramesh S, Qi Zhu
Guest Editorial. IET Cyper-Phys. Syst.: Theory & Appl. 2 (2) (2017)

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Publication Activity (10 Years)

Top Topics

Top Venues

Corina S. Pasareanu