An Approach for Extracting Workflows from E-Commerce Applications
Why this work is in the frame
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Bibliographic record
Abstract
For many enterprises, reacting to fast changes to their business process is key to maintaining their competitive edge in the market. However, developers often must manually locate and modify business logics in source code, in order to meet new requirements. This situation has caused system maintenance costs to escalate while budgets and corporate spending shrink. In this paper, we propose an automatic approach that recovers business processes from source code and refines them using control structure information in as-specified workflows (a workflow is a computerized representation of a business process). By using the as-specified workflows to guide our recovery, we can limit the search scope for business logics in the source code and we can locate explicit associations between artifacts in the as-specified and as-implemented workflows. Our case studies illustrate the effectiveness of this structural based business process recovery approach.
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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 | 0.001 |
| 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