An XML-Based Framework for Language Neutral Program Representation and Generic Analysis
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
XML applications are becoming increasingly popular to define structured or semi-structured constrained data in XML for special application areas. In pursuit there is a growing momentum of activities related to XML representation of source code in the area of program comprehension and software re-engineering. The source code and the artifacts extracted from a program are necessarily structured information that needs to be stored and exchanged among different tools. This makes XML to be a natural choice to be used as the external representation formats for program representations. Most of the XML representations proposed so far abstract the source code at the AST level. These AST representations are tightly coupled with the language grammar of the source code and hence require development of different tools for different programming languages to perform the same type of analysis. Moreover AST abstracts the program at a very fine level of granularity and hence not suitable to be used directly for higher-level sophisticated program analysis. As such, we propose XML applications for language neutral representation of programs at different levels of abstractions and by combining them we present a program representation framework in order to facilitate the development of generic program analysis tools.
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 | 0.000 | 0.000 |
| 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 | 0.000 | 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