Service-Oriented Architecture: A Mapping Study
Bibliographic record
Abstract
Service-oriented architecture has enjoyed great popularity in industry, academia, and science since its appearance about ten years ago. Many publications have tried to describe it and analyze different aspects of its implementation, adoption, and implication. They have reflected the complexity of the concept of SOA and fuelled the debate about its real contribution. However, there is limited work that studies how the field of research on SOA is evolving. As such, we proposed a mapping study to account for the nature of the research, developed subjects, application domains, standards, and technologies. Based on more than a hundred journal articles selected from the IEEE Xplore and ACM Digital Library databases over the period 2000-2013, our study revealed three themes, including system development and SOA application. A plethora of application domains, standards, and technologies are also identified, and confirm the ever-growing interest in SOA. We concluded by noting that organizational aspects, such as SOA governance, did not emerge, and we propose an extension of this study.
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.006 | 0.010 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.008 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".