LCD: Local Combining on Demand. - Dana Drachsler-Cohen; Erez Petrank (OPODIS, 2014)

Practical concurrent binary search trees via logical ordering. - Dana Drachsler; Martin T. Vechev; Eran Yahav (PPoPP, 2014)

ExcUseMe: Asking Users to Help in Item Cold-Start Recommendations. - Michal Aharon; Oren Anava; Noa Avigdor-Elgrabli; Dana Drachsler-Cohen; Shahar Golan; Oren Somekh (RecSys, 2015)

Optimal Learning of Specifications from Examples. - Dana Drachsler-Cohen; Martin T. Vechev; Eran Yahav (CoRR, 2016)

Synthesis with Abstract Examples. - Dana Drachsler-Cohen; Sharon Shoham; Eran Yahav (CAV (1), 2017)

Learning Disjunctions of Predicates. - Nader H. Bshouty; Dana Drachsler-Cohen; Martin T. Vechev; Eran Yahav (COLT, 2017)

Exact Programming by Example. - Dana Drachsler-Cohen (2017)

DP-Finder: Finding Differential Privacy Violations by Sampling and Optimization. - Benjamin Bichsel; Timon Gehr; Dana Drachsler-Cohen; Petar Tsankov; Martin T. Vechev (CCS, 2018)

Securify: Practical Security Analysis of Smart Contracts. - Petar Tsankov; Andrei Marian Dan; Dana Drachsler-Cohen; Arthur Gervais; Florian Bünzli; Martin T. Vechev (CCS, 2018)

Net2Text: Query-Guided Summarization of Network Forwarding Behaviors. - Rüdiger Birkner; Dana Drachsler-Cohen; Laurent Vanbever; Martin T. Vechev (NSDI, 2018)

Practical concurrent traversals in search trees. - Dana Drachsler-Cohen; Martin T. Vechev; Eran Yahav (PPoPP, 2018)

AI2: Safety and Robustness Certification of Neural Networks with Abstract Interpretation. - Timon Gehr; Matthew Mirman; Dana Drachsler-Cohen; Petar Tsankov; Swarat Chaudhuri; Martin T. Vechev (IEEE Symposium on Security and Privacy, 2018)

DL2: Training and Querying Neural Networks with Logic. - Marc Fischer 002; Mislav Balunovic; Dana Drachsler-Cohen; Timon Gehr; Ce Zhang 001; Martin T. Vechev (ICML, 2019)

Config2Spec: Mining Network Specifications from Network Configurations. - Rüdiger Birkner; Dana Drachsler-Cohen; Laurent Vanbever; Martin T. Vechev (NSDI, 2020)

VerX: Safety Verification of Smart Contracts. - Anton Permenev; Dimitar Dimitrov 004; Petar Tsankov; Dana Drachsler-Cohen; Martin T. Vechev (SP, 2020)

Boosting Robustness Verification of Semantic Feature Neighborhoods. - Anan Kabaha; Dana Drachsler-Cohen (SAS, 2022)

Maximal Robust Neural Network Specifications via Oracle-Guided Numerical Optimization. - Anan Kabaha; Dana Drachsler-Cohen (VMCAI, 2023)

One Pixel Adversarial Attacks via Sketched Programs. - Tom Yuviler; Dana Drachsler-Cohen (Proc. ACM Program. Lang., 2023)

Deep Learning Robustness Verification for Few-Pixel Attacks. - Yuval Shapira; Eran Avneri; Dana Drachsler-Cohen (Proc. ACM Program. Lang., 2023)

Boosting Few-Pixel Robustness Verification via Covering Verification Designs. - Yuval Shapira; Naor Wiesel; Shahar Shabelman; Dana Drachsler-Cohen (CAV (2), 2024)

Robustness Verification of Multi-label Neural Network Classifiers. - Julian Mour; Dana Drachsler-Cohen (SAS, 2024)

Verification of Neural Networks' Local Differential Classification Privacy. - Roie Reshef; Anan Kabaha; Olga Seleznova; Dana Drachsler-Cohen (VMCAI (2), 2024)

Verification of Neural Networks' Global Robustness. - Anan Kabaha; Dana Drachsler-Cohen (Proc. ACM Program. Lang., 2024)

Guarding the Privacy of Label-Only Access to Neural Network Classifiers via iDP Verification. - Anan Kabaha; Dana Drachsler-Cohen (Proc. ACM Program. Lang., 2025)