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Record W1509712248

Deriving real-time monitors from system requirements documentation

2000· dissertation· en· W1509712248 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldComputer Science
TopicSoftware Reliability and Analysis Research
Canadian institutionsMcMaster University
Fundersnot available
KeywordsCorrectnessSystem requirements specificationDocumentationComputer scienceSoftware requirements specificationProcess (computing)System requirementsAutomatonEquivalence (formal languages)Software engineeringReliability engineeringProgramming languageEngineeringSoftwareOperating systemTheoretical computer scienceSoftware developmentSoftware design
DOInot available

Abstract

fetched live from OpenAlex

During system testing, determining if the observed behaviour of a real–time system is consistent with its requirements specification can be difficult. I propose that a system to check the behaviour against the specification, a monitor, be automatically derived from the requirements documentation. The monitor would model the system requirements as a modified finite state automaton in which the states represent equivalence classes of system histories and transitions are labelled with predicates such that it accepts only executions representing acceptable system behaviour. Investigation into the design of such a monitor, and the process for automatically generating it from reviewable requirements documentation is on–going. 1. Problem Statement The process of testing a real–time system typically involves running the system in a test environment, observing its behaviour and comparing it to that required by its specification. In general, making this comparison can be quite difficult since the requirements may be complex, possibly including time constraints and interdependencies. A monitor is a system that automatically determines if the observed behaviour is consistent with a given specification. When designing safety– or mission–critical systems, good engineering practice dictates that a clear, precise and unambiguous specification of the required behaviour of the system be produced and reviewed for correctness by experts in the domain of application of the system. Research has demonstrated that such reviews are effective if the system behavioural requirements documentation is written such that: it expresses the required behaviour in terms of the quantities from the environment that are monitored and/or controlled by the system, it uses terminology and notation that is familiar to, or easily understood by, the domain experts, and it is presented in a manner that permits independent review of small parts of the document.[5] As discussed in [4], [9], [12] and [13], a (relational) system requirements document describes a relation, REQ, on vector functions of time representing the environmental quantities that are monitored and controlled by the system. I intend to explore techniques for using reviewable forms of such documentation (i.e. satisfying the above three criteria) to generate a software monitor that will determine if the observed behaviour of some software is consistent with that expressed in the documentation. Such a monitor would be useful, during system testing, for determining if the system is operating correctly, or, in certain safety–critical applications, it may be useful as a redundant monitoring system during operation. Through this research I hope to answer the following questions: 1. How can a monitor be used to verify conformance with relational requirements documentation? 2. What are the useful classes of behavioural properties that can and cannot be: a) specified in relational documentation? b) verified using a monitor as described above? 3. Under what conditions can an effective monitor be produced automatically from a relational requirements document? What restrictions on the form or content of the documentation must be imposed? 4. What is the cost (computational and space complexity) of using such a monitor? Are there some optimizations that can be done to reduce this complexity or restrictions on the documentation that will ensure that the complexity is tractable?

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.902
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.014
GPT teacher head0.306
Teacher spread0.292 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it