6 citations · 7 across the 7 of their papers we have counts for
6 papers · 1 filter
On the Relation between Code Quality and Machine Learning Performance: A Large-scale Empirical Study
Marius Mignard, Steven Costiou, Anne Etien
Context: Computational notebooks are the standard environment for machine learning (ML) development. Within the ML community, model performance is often the primary considered metr…
Analysing Python Machine Learning Notebooks with Moose
Marius Mignard, Steven Costiou, Nicolas Anquetil +1
Machine Learning (ML) code, particularly within notebooks, often exhibits lower quality compared to traditional software. Bad practices arise at three distinct levels: general Pyth…
Automatic Recommendations for Evolving Relational Databases Schema
Anne Etien, Nicolas Anquetil
Relational databases play a central role in many information systems. Their schema contains structural (e.g. tables and columns) and behavioral (e.g. stored procedures or views) en…
Modular Moose: A new generation software reverse engineering environment
Nicolas Anquetil, Anne Etien, Mahugnon H. Houekpetodji +6
Advanced reverse engineering tools are required to cope with the complexity of software systems and the specific requirements of numerous different tasks (re-architecturing, migrat…
RTj: a Java framework for detecting and refactoring rotten green test cases
Matias Martinez, Anne Etien, Stéphane Ducasse +1
Rotten green tests are passing tests which have, at least, one assertion not executed. They give developers a false confidence. In this paper, we present, RTj, a framework that ana…
JSClassFinder: A Tool to Detect Class-like Structures in JavaScript
Leonardo Humberto Silva, Daniel Hovadick, Marco Tulio Valente +3
With the increasing usage of JavaScript in web applications, there is a great demand to write JavaScript code that is reliable and maintainable. To achieve these goals, classes can…