Static And Dynamic Reverse Engineering Techniques for Java Software Systems
Why this work is in the frame
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Bibliographic record
Abstract
The main contributions of this dissertation are as follows: \n \nmethods for using the dependencies between static and dynamic models for goal driven reverse engineering tasks, including \n merging dynamic information to a static Rigiview; \n using static information to guide the generation of dynamici nformation; \n slicing a Rigi view using SCED scenarios; and \n raising the level of abstraction of SCED scenarios using a high-level Rigigraph; \n \nalgorithms for optimizing synthesized state diagrams using UMLnotation; \n \napplication of the synthesis algorithm presented by Koskimies and Mäkinen [54] to SCED; \n \nstring matching algorithms for raising the level of abstraction of SCED scenario iagrams; \n \nthe prototype reverse ngineering environment Shimba, which integrates two existing tools: \n Rigi for reverse engineering the static structure of Javasoftware; and \n SCED and its state diagram synthesis facility for reverse engineering the dynamic behavior of Java software; \n \nmethods and tools for gathering information, including \n extraction of static information from Java byte code;and \n extraction of run-time information by running the target system under a customized jdk debugger; \n \na case study to evaluate the facilities of Shimba.
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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 | 0.000 | 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 | 0.001 | 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