Supplementary Material - Mining Billions of AST Nodes to Study Actual and Potential Usage of Java Language Features
by Robert Dyer, Hridesh Rajan, Hoan Anh Nguyen, and Tien N. Nguyen
Table of Contents
- Section 2 - JLS Background
- Section 4.2 - Dataset Metrics
- Section 5.1 - RQ1 - Do projects use new language features before the features are released?
- Section 5.2 - RQ2 - How frequently is each language feature used?
- Section 5.3 - RQ3 - How did committers adopt and use language features?
- Section 5.3.1 - RQ3.1 - How many committers adopted and used new features over time?
- Section 5.3.2 - RQ3.2 - How much did committers use each feature?
- Section 5.3.3 - RQ3.3 - Did committers adopt features on an individual basis or as a team?
- Section 5.3.4 - RQ3.4 - Did committers use all new features?
- Section 5.4 - RQ4 - Were there missed opportunities to use language features?
- Section 5.5 - RQ5 - Was old code converted to use new language features?
Section 5.2 - RQ2 - How frequently is each language feature used?
This material mines uses for language features, shown in Figure 4.
This material mines uses for language features over time, which is used to generate the histograms shown in Figures 5-6.NOTE: The Boa Program and Raw Data are the same as Section 5.1.
This material mines when files and projects were created, which (along with the previous data) is used to generate the density plots shown in Figures 5-6.
Section 5.2.1 - Investigating Frequently Used Features
This material mines the most frequently used annotations, shown in Figure 7.
This material mines the most frequently used generic types, shown in Figure 8.
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