A formal component-based software engineering approach for developing trustworthy systems
Bibliographic record
Abstract
Software systems are increasingly becoming ubiquitous, affecting the way we experience the world. Embedded software systems, especially those used in smart devices, have become an essential constituent of the technological infrastructure of modem societies. Such systems, in order to be trusted in society, must be proved to be trustworthy. Trustworthiness is a composite non-functional property that implies safety, timeliness, security, availability, and reliability. This thesis is a contribution to a rigorous development of systems in which trustworthiness property can be specified and formally verified. Developing trustworthy software systems that are complex and used by a large heterogenous population of users is a challenging task. The component-based software engineering (CBSE) paradigm can provide an effective solution to address these challenges. However, none of the current component-based approaches can be used as is, because all of them lack the essential requirements for constructing trustworthy systems. The three contributions made in this thesis are intended to add to the expressive power needed to raise CBSE practices to a rigorous level for constructing formally verifiable trustworthy systems. The first contribution of the thesis is a formal definition of the trustworthy component model. The trustworthiness quality attributes are introduced as first class structural elements. The behavior of a component is automatically generated as an extended timed automata. A model checking technique is used to verify the properties of trustworthiness. A composition theory that preserves the properties of trustworthiness in a composition is presented. Conventional software engineering development processes are not suitable either for developing component-based systems or for developing trustworthy systems. In order to develop a component-based trustworthy system, the development process must be reuse-oriented, component-oriented, and must integrate formal languages and rigorous methods in all phases of system life-cycle. The second contribution of the thesis is a software engineering process model that consists of several parallel tracks of activities including component development, component assessment, component reuse, and component-based system development. The central concern in all activities of this process is ensuring trustworthiness. The third and final contribution of the thesis is a development framework with a comprehensive set of tools supporting the spectrum of formal development activity from modeling to deployment. The proposed approach has been applied to several case studies in the domains of component-based development and safety-critical systems. The experience from the case studies confirms that the approach is suitable for developing large and complex trustworthy systems.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.005 |
| 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".