From the 1 of 5 linked papers with an AI index.
2 citations · 2 across the 5 of their papers we have counts for
5 papers
SemaDiff: Identifying Semantic-Changing Commits with Generated Code and Tests
Maha Ayub, Michael Konstantinou, Ahmed Khanfir +2
The paper introduces SemaDiff, a method that uses large language models to generate additional calling code and tests in order to compare the behavior of pre- and post‑commit versi…
Intent-Based Mutation Testing: From Naturally Written Programming Intents to Mutants
Asma Hamidi, Ahmed Khanfir, Mike Papadakis
This paper presents intent-based mutation testing, a testing approach that generates mutations by changing the programming intents that are implemented in the programs under test.…
Round-Trip Mutation Testing: Translating Code to Natural Language Intent and back
Asma Hamidi, Cedric Richter, Ahmed Khanfir +1
This paper presents Round-Trip Mutation Testing (RTM), a novel approach that generates mutants from LLM mistranslations between a program code and its intent. Leveraging the genera…
Towards a more efficient bias detection in financial language models
Firas Hadj Kacem, Ahmed Khanfir, Mike Papadakis
Bias in financial language models constitutes a major obstacle to their adoption in real-world applications. Detecting such bias is challenging, as it requires identifying inputs w…
Impact of LLMs news Sentiment Analysis on Stock Price Movement Prediction
Walid Siala, Ahmed Khanfir, Mike Papadakis
This paper addresses stock price movement prediction by leveraging LLM-based news sentiment analysis. Earlier works have largely focused on proposing and assessing sentiment analys…