activity
20202026
most citedRatGPT: Turning online LLMs into Proxies for Malware Attacks

15 citations · 20 across the 7 of their papers we have counts for

collaborators
Showing cs.SEShow all

5 papers · 1 filter

cs.SE2026

Neural Change Prediction: Relating Software Changes to Their Effects and Vice Versa

Laura Plein, Souhila Zidane, Jordan Samhi +1

Much of software development revolves around understanding the relationship between software changes and their effects. If we could learn and predict those relationships, such pred…

cs.SE2023★ 2 cited

Enriching Automatic Test Case Generation by Extracting Relevant Test Inputs from Bug Reports

Wendkûuni C. Ouédraogo, Laura Plein, Kader Kaboré +4

The quality of software is closely tied to the effectiveness of the tests it undergoes. Manual test writing, though crucial for bug detection, is time-consuming, which has driven s…

cs.SE2023★ 1 cited

Automatic Generation of Test Cases based on Bug Reports: a Feasibility Study with Large Language Models

Laura Plein, Wendkûuni C. Ouédraogo, Jacques Klein +1

Software testing is a core discipline in software engineering where a large array of research results has been produced, notably in the area of automatic test generation. Because e…

cs.SE2023★ 2 cited

Can LLMs Demystify Bug Reports?

Laura Plein, Tegawendé F. Bissyandé

Bugs are notoriously challenging: they slow down software users and result in time-consuming investigations for developers. These challenges are exacerbated when bugs must be repor…

cs.SE2020

What You See is What it Means! Semantic Representation Learning of Code based on Visualization and Transfer Learning

Patrick Keller, Laura Plein, Tegawendé F. Bissyandé +2

Recent successes in training word embeddings for NLP tasks have encouraged a wave of research on representation learning for source code, which builds on similar NLP methods. The o…