Dynamic Program Slices Change How Developers Diagnose Gradual Run-Time Type Errors
Why this work is in the frame
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Bibliographic record
Abstract
A gradual type system allows developers to declare certain types to be enforced by the compiler (i.e., statically typed), while leaving other types to be enforced via runtime checks (i.e., dynamically typed).When runtime checks fail, debugging gradually typed programs becomes cumbersome, because these failures may arise far from the original point where an inconsistent type assumption is made.To ease this burden on developers, some gradually typed languages produce a blame report for a given type inconsistency.However, these reports are sometimes misleading, because they might point to program points that do not need to be changed to stop the error.To overcome the limitations of blame reports, we propose using dynamic program slicing as an alternative approach to help programmers debug run-time type errors.We describe a proof-of-concept for TypeSlicer, a tool that would present dynamic program slices to developers when a runtime check fails.We performed a Wizard-of-Oz user study to investigate how developers respond to dynamic program slices through a set of simulated interactions with TypeScript programs.This formative study shows that developers can understand and apply dynamic slice information to provide change recommendations when debugging runtime type errors.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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