With the abundance of software libraries available, finding the right one to use can be a time-consuming task. In this research direction, we mine various software repositories to extract information that can be used to compare libraries across various aspects (e.g., their documentation, popularity etc.).
Given the popularity of data-driven applications, data scientists have become more involved in contributing to various software components. We also explore what selection factors data scientists consider when choosing a software library for their work.
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Related Resources
Related Publications
2023
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Evaluating Software Documentation Quality
Henry Tang, and Sarah Nadi
In Proceedings of the 20th ACM International Conference on Mining Software Repositories (MSR), Nov 2023
2022
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Selecting Third-party Libraries: The Data Scientist’s Perspective
Sarah Nadi, and Nourhan Sakr
Empirical Software Engineering Journal (EMSE), Nov 2022
2020
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LibComp: An IntelliJ Plugin for Comparing Java Libraries
Rehab El-Hajj, and Sarah Nadi
In Proceedings of the ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE ’20), Nov 2020
2018
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Which library should I use? A metric-based comparison of software libraries
Fernando Lopez Mora, and Sarah Nadi
In Proceedings of the 40th International Conference on Software Engineering New Ideas and Emerging Results Track (ICSE NIER ’18), Nov 2018
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An Empirical Study of Metric-based Comparisons of Software Libraries
Fernando Lopez Mora, and Sarah Nadi
In Proc. of the 14th International Conference on Predictive Models and Data Analytics in Software Engineering (PROMISE ’18), Nov 2018
Funding