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20212023
most citedEfficient Mutation Testing via Pre-Trained Language Models

5 citations · 11 across the 8 of their papers we have counts for

collaborators

8 papers

cs.SE20231 cited

ACoRe: Automated Goal-Conflict Resolution

Luiz Carvalho, Renzo Degiovanni, Matìas Brizzio +4

System goals are the statements that, in the context of software requirements specification, capture how the software should behave. Many times, the understanding of stakeholders o…

cs.SE20234 cited

Vulnerability Mimicking Mutants

Aayush Garg, Renzo Degiovanni, Mike Papadakis +1

With the increasing release of powerful language models trained on large code corpus (e.g. CodeBERT was trained on 6.4 million programs), a new family of mutation testing tools has…

cs.SE2023

Specification Inference for Evolving Systems

Renzo Degiovanni, Facundo Molina, Agustin Nolasco +2

In this paper, we propose an assertion-based approach to capture software evolution, through the notion of commit-relevant specification. A commit-relevant specification summarises…

cs.SE2023

Assertion Inferring Mutants

Aayush Garg, Renzo Degiovanni, Facundo Molina +4

Specification inference techniques aim at (automatically) inferring a set of assertions that capture the exhibited software behaviour by generating and filtering assertions through…

cs.SE20235 cited

Efficient Mutation Testing via Pre-Trained Language Models

Ahmed Khanfir, Renzo Degiovanni, Mike Papadakis +1

Mutation testing is an established fault-based testing technique. It operates by seeding faults into the programs under test and asking developers to write tests that reveal these…

cs.SE2022

Learning from what we know: How to perform vulnerability prediction using noisy historical data

Aayush Garg, Renzo Degiovanni, Matthieu Jimenez +3

Vulnerability prediction refers to the problem of identifying system components that are most likely to be vulnerable. Typically, this problem is tackled by training binary classif…