Investigating java type analyses for the receiver-classes testing criterion
Why this work is in the frame
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Bibliographic record
Abstract
This paper investigates the precision of three linear-complexity type analyses for Java software: Class Hierarchy Analysis (CHA), Rapid Type Analysis (RTA) and Variable Type Analysis (VTA). Precision is measured relative to class targets. Class targets results are useful in the context of the receiver-classes criterion, which is an object-oriented testing strategy that aims to exercise every possible class binding of the receiver object reference at each dynamic call site. In this context, using a more precise analysis decreases the number of infeasible bindings to cover, thus it reduces the time spent on conceiving test data sets. This paper also introduces two novel variations to VTA, called the iteration and intersection variants. We present experimental results about the precision of CHA, RTA and VTA on a set of 17 Java programs, corresponding to a total of 600 kLOC of source code. Results show that, on average, RTA suggests 13% less bindings than CHA, standard VTA suggests 23% less bindings than CHAt and VTA with the two variations together suggests 32% less bindings than CHA.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it