1 citations · 2 across the 4 of their papers we have counts for
4 papers
Symetra: Visual Analytics for the Parameter Tuning Process of Symbolic Execution Engines
Donghee Hong, Minjong Kim, Sooyoung Cha +1
Symbolic execution engines such as KLEE automatically generate test cases to maximize branch coverage, but their numerous parameters make it difficult to understand the parameters'…
Scaling Atomistic Protein Binder Design with Generative Pretraining and Test-Time Compute
Kieran Didi, Zuobai Zhang, Guoqing Zhou +11
Protein interaction modeling is central to protein design, which has been transformed by machine learning with applications in drug discovery and beyond. In this landscape, structu…
ECO: Enhanced Code Optimization via Performance-Aware Prompting for Code-LLMs
Su-Hyeon Kim, Joonghyuk Hahn, Sooyoung Cha +1
Code runtime optimization-the task of rewriting a given code to a faster one-remains challenging, as it requires reasoning about performance trade-offs involving algorithmic and st…
Enhancing Dynamic Symbolic Execution by Automatically Learning Search Heuristics
Sooyoung Cha, Seongjoon Hong, Jingyoung Kim +2
We present a technique to automatically generate search heuristics for dynamic symbolic execution. A key challenge in dynamic symbolic execution is how to effectively explore the p…