1 citations · 5 across the 13 of their papers we have counts for
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Operationalizing Property-Based Testing for Data-Intensive Scalable Computing Systems
Yaoxuan Wu, Ingrid Lee, Ahmad Humayun +2
While fuzzing effectively catches crashes, its shallow oracles often miss semantic drifts and optimization-related errors in data-intensive scalable computing (DISC) frameworks. Pr…
Assessing Large Language Models for Stabilizing Numerical Expressions in Scientific Software
Tien Nguyen, Kirshanthan Sundararajah, Muhammad Ali Gulzar
Scientific software relies on high-precision computation, yet finite floating-point representations introduce precision errors that propagate in safety-critical domains. Despite gr…
Evaluating LLM-Based Test Generation Under Software Evolution
Sabaat Haroon, Mohammad Taha Khan, Muhammad Ali Gulzar
Large Language Models (LLMs) are increasingly used for automated unit test generation. However, it remains unclear whether these tests reflect genuine reasoning about program behav…
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…
Assessing the Impact of Code Changes on the Fault Localizability of Large Language Models
Sabaat Haroon, Ahmad Faraz Khan, Ahmad Humayun +5
Generative Large Language Models (LLMs) are increasingly used in non-generative software maintenance tasks, such as fault localization (FL). Success in FL depends on a models abili…
Are the Majority of Public Computational Notebooks Pathologically Non-Executable?
Tien Nguyen, Waris Gill, Muhammad Ali Gulzar
Computational notebooks are the de facto platforms for exploratory data science, offering an interactive programming environment where users can create, modify, and execute code ce…