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20242026
most citedAutomatically Detecting Numerical Instability in Machine Learning Applications via Soft Assertions

2 citations · 3 across the 12 of their papers we have counts for

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5 papers · 1 filter

cs.SE2025

Targeted Testing of Compiler Optimizations via Grammar-Level Composition Styles

Zitong Zhou, Ben Limpanukorn, Hong Jin Kang +5

Ensuring the correctness of compiler optimizations is critical, but existing fuzzers struggle to test optimizations effectively. First, most fuzzers use optimization pipelines (heu…

cs.SE2025

WhyFlow: Interrogative Debugger for Sensemaking Taint Analysis

Burak Yetiştiren, Hong Jin Kang, Miryung Kim

Taint analysis is a security analysis technique used to track the flow of potentially dangerous data through an application and its dependent libraries. Investigating why certain u…

cs.SE2025

Structural Code Search using Natural Language Queries

Ben Limpanukorn, Yanjun Wang, Zach Patterson +5

Searching code is a common task that developers perform to understand APIs, learn common code patterns, and navigate code. Currently, developers most commonly search using keywords…

cs.SE2025

PALM: Path-aware LLM-based Test Generation with Comprehension

Yaoxuan Wu, Xiaojie Zhou, Ahmad Humayun +2

Symbolic execution is a widely used technique for test generation, offering systematic exploration of program paths through constraint solving. However, it is fundamentally constra…

cs.SE2025★ 2 cited

Automatically Detecting Numerical Instability in Machine Learning Applications via Soft Assertions

Shaila Sharmin, Anwar Hossain Zahid, Subhankar Bhattacharjee +3

Machine learning (ML) applications have become an integral part of our lives. ML applications extensively use floating-point computation and involve very large/small numbers; thus,…