Bibliographic record
Abstract
Common to most software development processes is that system functionalities are defined early in the life cycle in terms of informal requirements and visual models. As requirement descriptions evolve, they quickly become error-prone and difficult to understand leading to prolonged detrimental effects on reliability, cost, and safety of a software system that are very costly to fix in later phases of the software development process. Thus, the development of techniques and tools to support requirement specification development, understanding, validation, verification, maintenance and reuse becomes an important issue. This thesis proposes a novel methodology named Early Stages V&V (Early Stages Validation & Verification), which combines the semi-formal scenario-based Use Case Maps language with formal techniques to help comprehend, validate and verify requirements. UCM models allow the description of functional requirements and high-level designs at early stages of the development process. Use Case Maps is being standardized as part of the User Requirements Notation (URN), the most recent addition to ITU-Ts family of languages. In the first part of the thesis, we propose a concise and rigorous formal semantics for Use Case Maps based on Abstract State Machines (ASM) formalism. The resulting semantics are embedded in an ASM-UCM simulation engine and are expressed in AsmL, an advanced ASM-based executable specification language, which is used to validate UCM models through simulation. Timing issues are often overlooked during the initial system design and treated as separate behavioral issues and therefore described in separate models. In the second part of the thesis, we extend the Use Case Maps language to cover timing constraints. A potential timed version of UCM (called Timed UCM ) is formalized using Clocked Transition Systems (CTS) and Timed Automata (TA). The proposed semantics can be applied to comprehend, analyze, validate and verify (using model checking) timed UCM models. In addition, we have proposed a novel UCM-based property pattern system that combines qualitative, real-time and architectural properties into single graphical representation. The resulting pattern system is mapped to popular temporal logics CTL, TCTL and ArTCTL (Architectural real-time temporal logic), which is an extension to TCTL introduced in this research that provides temporal logics with architectural scopes. In order to achieve an efficient validation and verification of UCM models and to assess the impact of a specification change (e.g. as a result of a bug fixing or a feature upgrade), we extend the application of the well-known technique of program slicing to Use Case Maps language. An ongoing example of a simple telephone system is used to illustrate these concepts. The thesis validates the Early Stage V&V methodology by implementing it and applying it to two case studies: IP Multicast Protocol and an Online Store application.
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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 | 0.009 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".