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Requirements Quality Suite

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José M. Fuentes

on 13 July 2015

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Transcript of Requirements Quality Suite

Requirements Quality Suite
Main ideas
IBM Rational DOORS

Visure Requirements

CATIA Reqtify

Microsoft Excel

Current connections for RQS
Define, Measure, Manage and improve requirements quality
PDCA process
Core elements of RQS
Individual metrics

Quality functions

Global metrics



Semantic analysis

Semantic representation
The SMARTer way to manage requirements quality
Based on a CCC approach:
A set of tools
A pre-defined methodology
A definition or roles
RQA - Requirements Quality Analyzer
Configure RQS according to your quality policies
CCC: Correctness, Completeness, Consistency
Suitable for peer-review meetings
RAT - Requirements Authoring Tool
CCC on the fly
Authoring assistant:
Write terms based on intelisense
Follow the proper grammar based on boilerplates
Suitable for requirements authors
kM - knowledgeMANAGER
Manage the controlled vocabulary
Manage boilerplates
Manage suggestions from authors
Manage the ontology
Suitable for domain architects
Build or reuse a vocabulary
Take initial measurements of the metrics
Identify the set of metrics that better represents your current policies
Adjust the quality functions for those metrics
Let the authors use RAT
Use RQA in peer-reviews
Use RQA for Project managers and Quality control
Is quality evolving as expected?

Which other metrics should be introduced to keep enhancing the quality?

Which quality functions should be adjusted?

Should our authors be trained in some way?
Manage suggestions: ontology and boilerplates
Fine tune metrics and quality functions

Provide training to the team according to the quality results

Evolve the ontology definition
Individual metrics
Analyzed requirement by requirement:

For atomicity: requirements length, number of verbs and nouns, number of shall...
Use of the proper voice and tense
Use of the proper controlled vocabulary
Use of fuzzy terms
Follow the proper structure/syntax (boilerplate)
Quality functions
Transform every metric from a quantitative value to a qualitative value

For example:
Global metrics
Analyzed for a whole requirements document:

Correctness: based on the aggregation of individual metrics
Completeness: based on the number of requirements matching every group of boilerplates
Completeness: based on a report of missing links
Consistency: based on the use of measurement units
Coupling: based on a semantic search engine
Suggest the agreed upon structure (grammar/syntax) for the requirements

Used for correctness purposes

Used for completeness purposes
Semantic Analysis
Used for coupling analysis

Used for traceability analysis

Provides semantic capabilities for a reuse system
Semantic formalization
Evolve the ontology
SKB: System Knowledge Base
The representation of the ontology
Can be made up of many sub-SKB

SAS: System Asset Storage
Storing the formalization of the requirement
Not storing the requirement itself
Full transcript