38 citations · 267 across the 48 of their papers we have counts for
8 papers · 1 filter
Searching for Replacement Classes
Malavika Samak, Jose Pablo Cambronero, Martin C. Rinard
Software developers must often replace existing components in their systems to adapt to evolving environments or tooling. While traditional code search systems are effective at ret…
Verifying Low-dimensional Input Neural Networks via Input Quantization
Kai Jia, Martin Rinard
Deep neural networks are an attractive tool for compressing the control policy lookup tables in systems such as the Airborne Collision Avoidance System (ACAS). It is vital to ensur…
Incompatibility Clustering as a Defense Against Backdoor Poisoning Attacks
Charles Jin, Melinda Sun, Martin Rinard
We propose a novel clustering mechanism based on an incompatibility property between subsets of data that emerges during model training. This mechanism partitions the dataset into…
Inductive Program Synthesis over Noisy Datasets using Abstraction Refinement Based Optimization
Shivam Handa, Martin Rinard
We present a new synthesis algorithm to solve program synthesis over noisy datasets, i.e., data that may contain incorrect/corrupted input-output examples. Our algorithm uses an ab…
Program Synthesis Over Noisy Data with Guarantees
Shivam Handa, Martin Rinard
We explore and formalize the task of synthesizing programs over noisy data, i.e., data that may contain corrupted input-output examples. By formalizing the concept of a Noise Sourc…
Inferring Drop-in Binary Parsers from Program Executions
Thurston H. Y. Dang, Jose P. Cambronero, Martin C. Rinard
We present BIEBER (Byte-IdEntical Binary parsER), the first system to model and regenerate a full working parser from instrumented program executions. To achieve this, BIEBER explo…