Travelled to:1 × India
1 × United Kingdom
5 × USA
Collaborated with:M.T.Vechev P.Bielik E.Yahav M.Sridharan D.Dimitrov A.Krause M.Musuvathi T.Mytkowicz S.Karaivanov E.Koskinen M.Schäfer Andreas Krause 0001 Rumen Paletov P.Tsankov Victor Chibotaru B.Bichsel Jan Eberhardt Samuel Steffen C.S.Jensen A.Møller
Talks about:code (5) program (4) detect (3) model (3) learn (3) race (3) synthesi (2) statist (2) scalabl (2) languag (2)
Person: Veselin Raychev
DBLP: Raychev:Veselin
Contributed to:
2015
2015
2015
2014
20142013
2013
20172016201620182019Wrote 16 papers:
- OOPSLA-2015-BielikRV #android #concurrent #detection #scalability
- Scalable race detection for Android applications (PB, VR, MTV), pp. 332–348.
- OOPSLA-2015-JensenMRDV #model checking
- Stateless model checking of event-driven applications (CSJ, AM, VR, DD, MTV), pp. 57–73.
- POPL-2015-RaychevVK #predict
- Predicting Program Properties from “Big Code” (VR, MTV, AK), pp. 111–124.
- SOSP-2015-RaychevMM #execution #symbolic computation #using
- Parallelizing user-defined aggregations using symbolic execution (VR, MM, TM), pp. 153–167.
- Onward-2014-KaraivanovRV #programming language #statistics
- Phrase-Based Statistical Translation of Programming Languages (SK, VR, MTV), pp. 173–184.
- PLDI-2014-DimitrovRVK #commutative #concurrent #detection
- Commutativity race detection (DD, VR, MTV, EK), p. 33.
- PLDI-2014-RaychevVY #code completion #modelling #statistics
- Code completion with statistical language models (VR, MTV, EY), p. 44.
- OOPSLA-2013-RaychevSSV #refactoring #synthesis
- Refactoring with synthesis (VR, MS, MS, MTV), pp. 339–354.
- OOPSLA-2013-RaychevVS #concurrent #detection #effectiveness #source code
- Effective race detection for event-driven programs (VR, MTV, MS), pp. 151–166.
- SAS-2013-RaychevVY #automation #concurrent #synthesis
- Automatic Synthesis of Deterministic Concurrency (VR, MTV, EY), pp. 283–303.
- CAV-2017-BielikRV #learning
- Learning a Static Analyzer from Data (PB, VR, MTV), pp. 233–253.
- OOPSLA-2016-RaychevBV #probability
- Probabilistic model for code with decision trees (VR, PB, MTV), pp. 731–747.
- POPL-2016-RaychevBVK #learning #semistructured data #source code
- Learning programs from noisy data (VR, PB, MTV, AK0), pp. 761–774.
- PLDI-2018-PaletovTRV #api
- Inferring crypto API rules from code changes (RP, PT, VR, MTV), pp. 450–464.
- PLDI-2019-ChibotaruBRV #scalability #specification
- Scalable taint specification inference with big code (VC, BB, VR, MTV), pp. 760–774.
- PLDI-2019-EberhardtSRV #alias #api #learning #specification
- Unsupervised learning of API aliasing specifications (JE, SS, VR, MTV), pp. 745–759.