4 papers · 1 filter
New Formulation of DNN Statistical Mutation Killing for Ensuring Monotonicity: A Technical Report
Jinhan Kim, Nargiz Humbatova, Gunel Jahangirova +2
Mutation testing has emerged as a powerful technique for evaluating the effectiveness of test suites for Deep Neural Networks. Among existing approaches, the statistical mutant kil…
METAMON: Finding Inconsistencies between Program Documentation and Behavior using Metamorphic LLM Queries
Hyeonseok Lee, Gabin An, Shin Yoo
Code documentation can, if written precisely, help developers better understand the code they accompany. However, unlike code, code documentation cannot be automatically verified v…
Beyond pip install: Evaluating LLM Agents for the Automated Installation of Python Projects
Louis Milliken, Sungmin Kang, Shin Yoo
Many works have recently proposed the use of Large Language Model (LLM) based agents for performing `repository level' tasks, loosely defined as a set of tasks whose scopes are gre…
Identifying Inaccurate Descriptions in LLM-generated Code Comments via Test Execution
Sungmin Kang, Louis Milliken, Shin Yoo
Software comments are critical for human understanding of software, and as such many comment generation techniques have been proposed. However, we find that a systematic evaluation…