João Felipe Pimentel

Orcid: 0000-0001-6680-7470

According to our database1, João Felipe Pimentel authored at least 25 papers between 2015 and 2024.

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Bibliography

2024
Biomedical Open Source Software: Crucial Packages and Hidden Heroes.
CoRR, 2024

How to Support ML End-User Programmers through a Conversational Agent.
Proceedings of the 46th IEEE/ACM International Conference on Software Engineering, 2024

2023
Tag that issue: applying API-domain labels in issue tracking systems.
Empir. Softw. Eng., October, 2023

Tell Me Who Are You Talking to and I Will Tell You What Issues Need Your Skills.
Proceedings of the 20th IEEE/ACM International Conference on Mining Software Repositories, 2023

Designing for Cognitive Diversity: Improving the GitHub Experience for Newcomers.
Proceedings of the 45th IEEE/ACM International Conference on Software Engineering: Software Engineering in Society, 2023

Anticipating User Needs: Insights from Design Fiction on Conversational Agents for Computational Thinking.
Proceedings of the Chatbot Research and Design - 7th International Workshop, 2023

2022
P+RProv: Prospective+Retrospective Provenance Graphs of Python Scripts.
J. Inf. Data Manag., 2022

How to Choose a Task? Mismatches in Perspectives of Newcomers and Existing Contributors.
Proceedings of the ESEM '22: ACM / IEEE International Symposium on Empirical Software Engineering and Measurement, Helsinki, Finland, September 19, 2022

2021
Recommending Participants for Collaborative Merge Sessions.
IEEE Trans. Software Eng., 2021

Attributes that may raise the occurrence of merge conflicts.
J. Softw. Eng. Res. Dev., 2021

Understanding and improving the quality and reproducibility of Jupyter notebooks.
Empir. Softw. Eng., 2021

2020
On the performance of hybrid search strategies for systematic literature reviews in software engineering.
Inf. Softw. Technol., 2020

What causes merge conflicts?
Proceedings of the 34th Brazilian Symposium on Software Engineering, 2020

2019
Dataset of A Large-scale Study about Quality and Reproducibility of Jupyter Notebooks / Understanding and Improving the Quality and Reproducibility of Jupyter Notebooks.
Dataset, March, 2019

Dataset of A Large-scale Study about Quality and Reproducibility of Jupyter Notebooks.
Dataset, March, 2019

A Survey on Collecting, Managing, and Analyzing Provenance from Scripts.
ACM Comput. Surv., 2019

Provenance-enhanced Algorithmic Debugging.
Proceedings of the XXXIII Brazilian Symposium on Software Engineering, 2019

A large-scale study about quality and reproducibility of jupyter notebooks.
Proceedings of the 16th International Conference on Mining Software Repositories, 2019

2018
Versioned-PROV: A PROV Extension to Support Mutable Data Entities.
Proceedings of the Provenance and Annotation of Data and Processes, 2018

2017
noWorkflow: a Tool for Collecting, Analyzing, and Managing Provenance from Python Scripts.
Proc. VLDB Endow., 2017

2016
Fine-Grained Provenance Collection over Scripts Through Program Slicing.
Proceedings of the Provenance and Annotation of Data and Processes, 2016

Tracking and Analyzing the Evolution of Provenance from Scripts.
Proceedings of the Provenance and Annotation of Data and Processes, 2016

Yin & Yang: Demonstrating Complementary Provenance from noWorkflow & YesWorkflow.
Proceedings of the Provenance and Annotation of Data and Processes, 2016

2015
Software rejuvenation via a multi-agent approach.
J. Syst. Softw., 2015

Collecting and Analyzing Provenance on Interactive Notebooks: When IPython Meets noWorkflow.
Proceedings of the 7th USENIX Workshop on the Theory and Practice of Provenance, 2015


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