11 papers
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…
TENSURE: Fuzzing Sparse Tensor Compilers (Registered Report)
Kabilan Mahathevan, Yining Zhang, Muhammad Ali Gulzar +1
Sparse Tensor Compilers (STCs) have emerged as critical infrastructure for optimizing high-dimensional data analytics and machine learning workloads. The STCs must synthesize compl…
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…
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…