A user-centered approach to modeling BPEL business processes using SUCD use cases
Bibliographic record
Abstract
BPEL is being widely used to specify business processes through the orchestration, composition and coordination of web services. It is now common practice to begin the process of modeling the work ows within a set of BPEL business processes using UML Activity Diagrams since they can be automatically mapped down onto BPEL code. However activity diagrams were not intended to explicitly model user goals and interactions with external systems o ering web services. However, since the chief purpose of BPEL business processes is to rst and foremost provide services to their users, using activity diagram modeling alone will not allow an E-commerce analyst to explicitly capture and model the users ' goals. In this paper we propose an approach to solve this issue; initially model BPEL business processes using Use Cases to capture users ' perspective, and to systematically develop activity diagrams from Use Case models. A Travel Agency system case study is presented illustrates the feasibility of the proposed approach. 1
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How this classification was reachedexpand
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 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".