Download
slide1 n.
Skip this Video
Loading SlideShow in 5 Seconds..
Inah Omoronyia and Tor Stålhane Guided Natural Language and Requirement Boilerplates PowerPoint Presentation
Download Presentation
Inah Omoronyia and Tor Stålhane Guided Natural Language and Requirement Boilerplates

Inah Omoronyia and Tor Stålhane Guided Natural Language and Requirement Boilerplates

137 Vues Download Presentation
Télécharger la présentation

Inah Omoronyia and Tor Stålhane Guided Natural Language and Requirement Boilerplates

- - - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript

  1. Institutt for datateknikk og informasjonsvitenskap Inah Omoronyia and Tor Stålhane Guided Natural Language and Requirement Boilerplates TDT 4242 TDT 4242

  2. Requirements • There are three levels of requirements: • Informal – e.g. Natural language (NL): free text, no rules apply • Semiformal • Guided Natural Language (GNL): free text but allowable terms are defined by a vocabulare • Boilerplates (BP): structured text and an ontology – vocabulary plus relationships between terms • Formal: e.g. state diagrams or predicate logic TDT 4242

  3. Requirements elicitation

  4. Humans and machines – 1 Given the amount and complexity of RE, we need to automate as much as possible. Humans and machines have different strong and weak points. We want to elicit and analyze requirements in a way that allows both parties to build on their strong sides.

  5. Humans and machines - 2 Machines are good at observing quantitative data and being deductive, fast and precise. In addition, they are good at doing consistent repetition of several actions. bad at handling variations in written material and pattern recognition. Humans are good at handling variations in written material, being inductive. In addition, they are good at doing error correction.

  6. Why BPs and GNL – 1 GNL and BPs will reduce variation and thus giving the machines the opportunity to do what they are best at: to be fast, precise and consistent. By combining humans and machines and let both do what they are best at, we get a better result than we would get if we left the job of handling requirements to just one of them.

  7. Why BPs and GNL - 2 The final goal is to allow the machine to assist the developers in analysing requirements for: Consistency Completeness Safety implications

  8. GNL and BPs Template based textual Semantics = + + Syntax Meta Model • RMM • Refinement • Specialization Keywords: Reflects requirement, system and domain concepts Guided RSL Boilerplates • Analysis • Correctness • Completeness • Consistency • Safety analysis Requirements expressed on templates Uses predefined templates based on concepts, relations and axioms to guide requirements elicitation Example: The <system function> shall provide <system capability> to achieve <goal> Requirements expressed using a vocabulary guide Uses predefined concepts, relations and axioms to guide requirements elicitation Example: The ACC system shall be able to determine the speed of the ego-vehicle. • Ontology: General and SP specific • Requirements classification • System attributes • Domain concepts

  9. What is GNL - 1 Free text requirement elicitation with the assistance of prescribed words from a dictionary. This will give us requirements which use all terms in a uniform way, this reducing misunderstandings No formal constraints Requires minimal expertise.

  10. What is GNL - 2 Aim: Bridge the gap between unconstrained expression and qualitychecking when representing requirements as free text. Quality measures:Correctness, consistency, completeness and un-ambiguity (reduced variability) Provide the basis for semantic processing and checking of requirements. Dictionary – Simple taxonomy or more formal ontology

  11. Approach for GNL – 1 Ontology = Thesaurus + Inference Rules • Thesaurus – Domain concepts: entities, terms and events • Inference Rules – Relations, attributes and axioms • Causality, similarity, reflexivity, transitiveness, symmetric, disjoint (contradiction) …

  12. Approach for GNL – 2 Required Activity Knowledge capture: Information embedded in domain events from domain experts and ontologist Implementation: Formal representation of captured knowledge. Language: OWL, Support environment: Protégé. Verification: Checking that represented ontology is correct using Classifiers/reasoners Domain experts (semantic accuracy) Mapping of requirement segments to ontology concepts

  13. Motivation for use of templates - 1 Text has the advantage of unconstrained expression. There is, however, a need for common • Understanding of concepts used to express the requirements and relations between them. • Format of presentation Lack of common understanding makes requirement specifications expressed as free text prone to ambiguous representations and inconsistencies. TDT 4242

  14. Motivation for use of templates - 1 Template based textual requirements specification (boilerplates) will introduce some limitations when representing requirements but will also reduce the opportunity to introduce ambiguities and inconsistencies. Boilerplates • Provides an initial basis for requirements checking • Are easy to understand for stakeholders compared to more formal representations TDT 4242

  15. What is a boilerplate – 1 Boilerplates is a set of structures that can be used to write requirements. They use high-level concept classification and attributes TDT 4242

  16. What is a boilerplate – 2 The RE process is as follows: Select a boilerplate or a sequence of boilerplates. The selection is based on the attributes that need to be included and how they are organized – fixed terms. If needed, identify and include mode boilerplates Instantiate all attributes A boilerplate consists of fixed terms and attributes. It may, or may not, contain one or more modes. TDT 4242

  17. Fixed Terms

  18. Attributes

  19. Boilerplate examples - 1 • BP32 • The <user> shall be able to <capability> • Attributes: • <user> = driver • <capability> = start the ACC system • Requirement • The driver shall be able to start the ACC system TDT 4242

  20. Boilerplate examples - 2 • BP2 The <system> shall be able to <action> <entity> • Attributes: • <system> = ACC system • <action> = determine • <entity> = the speed of the ego-vehicle • Requirement • The ACC system shall be able to determine the speed of the ego-vehicle TDT 4242

  21. Boilerplate examples - 3 • BP43 While <operational condition> • BP32 The <user> shall be able to <capability> • BP43 is a mode • Attributes • <operational condition> = activated • <user> = driver • <capability> = override engine power control of the ACC system • Requirement • While activated the driver shall be able to override engine power control of the ACC-system TDT 4242

  22. Functional requirements example Functional requirements from the SafeLoc system • The robot control system shall stop the robot within 10 milliseconds if a gate is opened to the zone where the robot is operating • The robot shall only be allowed to start when all gates are closed and the reset button is pushed • The robot shall stop if it tries to move into a zone already occupied by an operator TDT 4242

  23. Non functional requirement example – 1 Non-functional requirements and soft goals fits into the same BPs as functional requirements BP61 The <system> shall be able to <action> to <entity> Suitability: The <system > shall be able to <provide an appropriate set of functions> to <the user> TDT 4242

  24. Non functional requirement example – 2 Non-functional requirements and soft goals fits into the same BPs as functional requirements BP2-1 The <system> shall be able to <capability> BP12 …for a sustained period of at least <number> < unit> Maturity:The <system > shall be able to <operate without failure> for a sustained period of at least <quantity> <time unit> TDT 4242

  25. Non functional requirement example – 3 BP43 While <operational condition> BP2 The <system> shall be able to <action> <entity> While <normal operational condition> the <system> shall be able to <tolerate> <90% of software faults of category...>

  26. Summing up The use of boiler plates and ontologies will • Enforce a uniform use of terms • Reduce the variability of presentations – requirements that are similar will look similar • Reduced variation in form and contents simplifies the use of automatic and semi-automatic tools for • Checking requirement quality – e.g completeness and consistency • Creating test cases TDT 4242