REENGINEERING TECHNIQUE ADAPTATION OF LEGACY SOFTWARE SYSTEMS
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
В статье рассматривается адаптация методики реинжиниринга унаследованных систем. Приводится обзор подходов к реинжинирингу. Несмотря на то, что термин «реинжиниринг» в первую очередь относится к изменению бизнес процессов, он удачно подходит и к модернизации программного обеспечения. Обосновывается необходимость адаптации методики. В статье описывается применение адаптированной методики на примере реинжиниринга программного комплекса для прогнозных исследований ТЭК. Приведен исторический обзор версий ПК «ИНТЭК» и описаны поэтапно все шаги проведения его реинжиниринга на основе агентно-сервисного подхода The article presents an adaptation of the legacy systems reengineering technique. An overview of approaches to reengineering is given. Although the term “reengineering” primarily refers to changing business processes, it is well suited to software development. The necessity of adapting the method has been substantiated. The article describes the application of the described methodology on the example of software complex reengineering for predictive research of the fuel and energy complex. A historical overview of the current problem is given and all stages of INTEC PC reengineering are described step by step
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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