Bibliographic record
Abstract
A use case is a description of a sequence of actions constituting a complete task or transaction in an application. Use cases were first proposed by Jacobson (1987) and have since been incorporated as one of the key modeling constructs in UML (Booch, Jacobson, & Rumbaugh, 1999) and the Unified Software Development Process (Jacobson, Booch, & Rumbaugh, 1999). This paper traces the development of use cases, and identifies a number of problems with both their application and theoretical underpinnings. From an application perspective, the use case concept is marked by a high degree of variety in the level of abstraction versus implementation detail advocated by various authors. In addition, use cases are promoted as a primary mechanism for identifying objects in an application, even though they focus on processes rather than objects. Moreover, there is an apparent inconsistency between the so-called naturalness of object models and the commonly held view that use cases should be the primary means of communicating and verifying requirements with users. From a theoretical standpoint, the introduction of implementation issues in use cases can be seen as prematurely anchoring the analysis to particular implementation decisions. In addition, the fragmentation of objects across use cases creates conceptual difficulties in developing a comprehensive class model from a set of use cases. Moreover, the role of categorization in human thinking suggests that class models may serve directly as a good mechanism for communicating and verifying application requirements with users. We conclude by outlining a framework for further empirical research to resolve issues raised in our analysis.
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 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 | 0.000 |
| Open science | 0.001 | 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 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".