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 5.4 - RQ4 - Were there missed opportunities to use language features?
This material mines potential uses for language features, shown in Figure 15.
The output contains five keys (each key represents a row in Figure 15):
|OldPotential||Potential uses in old files.|
|NewPotential||Potential uses in new files.|
|AllPotential||Potential uses in all files.|
|FilesPotential||Number of files with potential uses.|
|ProjectsPotential||Number of projects with potential uses.|
and each key contains an index for the feature being mined:
|Key Index||Column in Figure 6|
This material mines potential bugs from not using try with resources.
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