Foutse Khomh

Towards Understanding Interactive Debugging

2016

Debugging is a laborious activity in which developers spend lot of time navigating through code, looking for starting points, and stepping through statements. Yet, although debuggers exist for 40 years now, there have been few …

Opiner: An opinion search and summarization engine for APIs

2017

Opinions are key determinants to many of the activities related to software development. The perceptions of developers about an API, and the choices they make about whether and how they should use it, may, to …

Towards Crowd-Sourced API Documentation

2019

The learnability of an API suffers when the official documentation of the API is incomplete. Developers discuss usage scenarios of APIs in the online developer forums. As such, by automatically mining such crowd-sourced documentation of …

Anti-patterns for multi-language systems

2019

Multi-language systems are common nowadays because most of the systems are developed using components written in different programming languages. These systems could arise from three different reasons: (1) to leverage the strengths and take benefits …

Analysis of Modern Release Engineering Topics : – A Large-Scale Study using StackOverflow –

2020

Release engineers are continuously required to de-liver high-quality software products to the end-user. As a result, modern software companies are proposing new changes in their delivery process that adapt to new technologies such as continuous …

Investigating Design Anti-pattern and Design Pattern Mutations and Their Change- and Fault-proneness

2021 · arXiv (Cornell University)

During software evolution, inexperienced developers may introduce design anti-patterns when they modify their software systems to fix bugs or to add new functionalities based on changes in requirements. Developers may also use design patterns to …

Studying the Characteristics of AIOps Projects on GitHub

2022 · arXiv (Cornell University)

Artificial Intelligence for IT Operations (AIOps) leverages AI approaches to handle the massive amount of data generated during the operations of software systems. Prior works have proposed various AIOps solutions to support different tasks in …

Maintenance Cost of Software Ecosystem Updates

2023 · Procedia Computer Science

Over the past decades, software domains have witnessed a trend towards faster software release cycles, an increase of software components, and their connectivity. Examples include products in Industry 4.0 domains such as health care, retail, …

An Empirical Study of Self-Admitted Technical Debt in Machine Learning Software

2023 · arXiv (Cornell University)

The emergence of open-source ML libraries such as TensorFlow and Google Auto ML has enabled developers to harness state-of-the-art ML algorithms with minimal overhead. However, during this accelerated ML development process, said developers may often …

An Empirical Study on Bugs Inside PyTorch: A Replication Study

2023

Software systems are increasingly relying on deep learning components, due to their remarkable capability of identifying complex data patterns and powering intelligent behaviour. A core enabler of this change in software development is the availability …

DeepCodeProbe: Towards Understanding What Models Trained on Code Learn

2024 · arXiv (Cornell University)

Machine learning models trained on code and related artifacts offer valuable support for software maintenance but suffer from interpretability issues due to their complex internal variables. These concerns are particularly significant in safety-critical applications where …

Automated UML Visualization of Software Ecosystems: Tracking Versions, Dependencies, and Security Updates

2025 · Procedia Computer Science

The growing complexity of software ecosystems—spanning multiple operating systems and their interconnected software components—poses significant challenges for documenting, visualizing, and maintaining these large systems over time. This complexity stems from the increasing number of components, …