SEMar 17, 2021

DUETS: A Dataset of Reproducible Pairs ofJava Library-Clients

arXiv:2103.09672v1Has Code
Originality Synthesis-oriented
AI Analysis

This dataset addresses the need for reproducible software artifacts in software engineering research, though it is incremental as it builds on existing data collection methods.

The authors introduced DUETS, a dataset of 395 libraries and 2,874 clients from open-source Java projects, designed to support static and dynamic analysis for studying API usage and test suites.

Software engineering researchers look for software artifacts to study their characteristics or to evaluate new techniques. In this paper, we introduce DUETS, a new dataset of software libraries and their clients. This dataset can be exploited to gain many different insights, such as API usage, usage inputs, or novel observations about the test suites of clients and libraries. DUETS is meant to support both static and dynamic analysis. This means that the libraries and the clients compile correctly, they are executable and their test suites pass. The dataset is composed of open-source projects that have more than five stars on GitHub. The final dataset contains 395 libraries and 2,874 clients. Additionally, we provide the raw data that we use to create this dataset, such as 34,560 pom.xml files or the complete file list from 34,560 projects. This dataset can be used to study how libraries are used by their clients or as a list of software projects that successfully build. The client's test suite can be used as an additional verification step for code transformation techniques that modify the libraries.

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