Taming control flow: a structured approach to eliminating goto statements
Bibliographic record
Abstract
In designing optimizing and parallelizing compilers, it is often simpler and more efficient to deal with programs that have structured control flow. Although most programmers naturally program in a structured fashion, there remain many important programs and benchmarks that include some number of goto statements, thus rendering the entire program unstructured. Such unstructured programs cannot be handled with compilers built with analyses and transformations for structured programs. In this paper we present a straight-forward algorithm to structure C programs by eliminating all goto statements. The method works directly on a high-level abstract syntax tree (AST) representation of the program and could easily be integrated into any compiler that uses an AST-based intermediate representation. The actual algorithm proceeds by eliminating each goto by first applying a sequence of goto-movement transformations followed by the appropriate goto-elimination transformation. We have implemented the method in the McCAT (McGill Compiler Architecture Testbed) optimizing/parallelizing C compiler and we present experimental results that demonstrate that the method is both efficient and effective.>
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".