Publications

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Conference Papers

CAV '19
( )
Overfitting in Synthesis: Theory and Practice

We define overfitting in the context of CEGIS-based SyGuS, and show that there exists a tradeoff between expressiveness and performance. We present two mitigation strategies: (1) a black-box approach that any existing tool can use, and (2) a white-box technique called hybrid enumeration.

CC '19
( )
A Static Slicing Method for Functional Programs and Its Incremental Version
Prasanna Kumar K.,  Amitabha Sanyal,  Amey KarkareSaswat Padhi

We propose a static analysis for slicing functional programs, which precisely captures structure-transmitted dependencies and provides a weak form of context sensitivity — weakened to guarantee decidability. We also show an incremental version this technique that is efficient in practice.

PLDI '16
( )
Data-Driven Precondition Inference with Learned Features
Saswat PadhiRahul SharmaTodd Millstein
⟬   Inv Track Winner of SyGuS-Comp 2017 – 18 ⟭  

We present a technique, called the precondition inference engine (PIE), which uses on-demand feature learning to automatically infer a precondition that would satisfy a given postcondition. We use PIE to also construct a novel automatic verification system called LoopInvGen.

Journal Papers

OOPSLA '18
( )
FlashProfile: A Framework for Synthesizing Data Profiles
Saswat PadhiPrateek Jain,  Daniel Perelman,  Oleksandr PolozovSumit GulwaniTodd Millstein

We present a technique, called FlashProfile, to generate hierarchical data profiles. Existing tools, including commercial ones, generate a single flat profile, and are often overly general or incomplete. Furthermore, we show that data profiles can improve accuracy and efficiency of PBE techniques.


Reports

Manuscripts


Patent Grants & Applications

US 2019
[ 20190034437A1 ]
US 2018
[ 20180121525A1 ]
Record Profiling for Dataset Sampling
Daniel G. Simmons,  Kevin D. J. Grealish,  Sumit Gulwani,  Ranvijay Kumar,  Kevin Michael EllisSaswat Padhi