Whole program analysis of Java programs for virtual calls and exception handling
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Java Programs suffer performance degradation due to the presence of virtual calls and the lack of an efficient exception handling mechanism. In this dissertation, we show how virtual calls can be statically resolved to one or two target methods. The resolved calls can then be potentially inlined and hence improve the performance of the program. Analyzing the whole program (including the Java runtime library) instead of only user code has a positive effect on the performance of the program. We present two exception handling mechanisms, Direct Path Analysis and Display Catch Exception Handling, that improve the performance of programs as compared to the existing popular techniques, Stack Unwinding and Stack Cutting. The first analysis shows that the number of the stack frames needed to be unwound is lower in our analysis than Stack Unwinding. In the second analysis, we propose the Display Catch Exception Handling mechanism which is better than Stack Cutting in terms of operations required to catch exceptions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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