An Empirical Study of Method Chaining in Java: Sampled Chains and Inspection Results

Method chains collected from Java code for a study published at MSR 2020. The archive includes lists of chains, manual inspection results, and sampled data for specific research questions. Tomoki Nakamaru from The University of Tokyo authored this research dataset.

Use Cases

• Analyzing the prevalence and patterns of method chaining in Java code based on the collected chain lists.
• Training or evaluating models for code smell detection based on manual inspection results for specific research questions.
• Studying API usage and fluency over time using the sampled chains from 2010 and 2018.
• Conducting replication studies on method chaining using the provided raw data and inspection results.

Strengths

• Includes manual inspection results for specific research questions, providing labeled data.
• Contains sampled chains from two distinct years (2010 and 2018), allowing for temporal analysis.
• Associated with a peer-reviewed publication (MSR 2020), suggesting academic rigor.

Limitations

• The dataset description notes 'THERE ARE PROBLEMS WITH THIS DATASET', indicating potential quality issues.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count and overall data scale are unknown, which may limit suitability assessment.

Provenance

Source

The University of Tokyo

Collection Method

Collected from Java code for an empirical study; includes manual inspections.

Time Range

Data samples from 2010 and 2018 are mentioned.