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
Modern source-level debuggers support dynamic breakpoints that are guarded by conditions based on program state. Such breakpoints address situations where a static breakpoint is not sufficiently precise to characterise a point of interest in program execution. However, we believe that current IDE support for dynamic breakpoints are cumbersome to use. Firstly, guard conditions formulated in (non-aspect-oriented) source-languages cannot directly express control-flow conditions, forcing developers to seek alternative formulations. Secondly, guard-conditions can be complex expressions and manually typing them is cumbersome.We present the Control-flow Breakpoint Debugger (CBD). CBD uses a dynamic pointcut language to characterise control-flow breakpoints---dynamic breakpoints which are conditional on the control-flow through which they were reached. CBD provides a "point-and-click" GUI to specify and incrementally refine control-flow breakpoints, thereby avoiding the burden of manually editing the potentially complex expressions that define them.We performed 20 case studies debugging and fixing documented bugs in 3 existing applications. Our results show that dynamic breakpoints in general are useful in practice, and that CBD's GUI allows specifying them adequately in the majority of cases.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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