Bibliographic record
Abstract
Middleware platforms, such as Web services, J2EE, CORBA, and DCOM, have become increasingly popular during the last decade. They have been very successful in solving distributed computing problems for a large family of application domains. The architecture of middleware systems have gone through many significant cycles of evolution, both in terms of the completeness of functionality and the range of adoptions for different types of platforms. However, at the same time, it is getting increasingly difficult to achieve and to maintain a high level of adaptability and configurability because the structure of the middleware architecture is becoming overly complicated and rigid. We attribute that problem to the limitations of traditional software decomposition methods. Aspect-oriented programming, on the contrary, has introduced new design perspectives that permit the superimpositions of different abstraction models on top of one another. This is a very powerful technique for separating and simplifying design concerns. In our effort of applying principles of aspect orientation to the middleware architecture, we first pragmatically analyze the use of aspects in the middleware architecture. We then show that aspects are the correct remedy for the above outlined middleware problems by quantifying crosscutting concerns in the legacy implementations of several prominent middleware systems. Our aspect analysis results strongly indicate that modularity of middleware architecture is greatly hindered by the wide existence of tangled logic. To go one step further, we factor out a number of crosscutting concerns identified in the mining process, reimplement them as aspects, and superimpose them back into the refactored architecture. This allows us to use a set of software engineering metrics to quantify the refactorization in terms of changes in the structural complexity, modularity, and performance of the resulting system. This aspect-oriented refactoring proves that aspect orientation is capable of composing orthogonal design requirements. The final "woven" system is able to correctly provide both the fundamental functionality and the "aspectized" functionality with negligible overhead and an overall leaner architecture. Furthermore, the "aspectized" feature can be configured in and out during compile-time, which greatly enhances the configurability of the architecture.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 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 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".