autonomous requirements specification processing using natural language processing - vivek punjabi
DESCRIPTION
Motivation Requirement artifacts Knowledge, experience, tools Requirements Specification Document Only knowledge Missing important information Consequences 40 – 60 % software defects due to errors in requirement stage Cost of correcting defects >> Cost to represent requirements correctly Risk of misinterpretationTRANSCRIPT
AUTONOMOUS REQUIREMENTS SPECIFICATION PROCESSING USINGNATURAL LANGUAGE PROCESSING
- Vivek Punjabi
Overview• Motivation• Background• Proposed system design• Architecture• Parsing System• Term Management System
• Conclusion
Motivation• Requirement artifacts• Knowledge, experience, tools
• Requirements Specification Document• Only knowledge
• Missing important information• Consequences• 40 – 60 % software defects due to errors in requirement stage• Cost of correcting defects >> Cost to represent requirements correctly• Risk of misinterpretation
Background• Use of formal languages for design• Still depends on knowledge
• Less research due to ambiguity of natural language requirements• Semi-automated generation of ER diagrams for database modelling• Requirements supplemented by glossary – a-priori knowledge• Pre-processing and application specific
System Design
Figure 1: Assisted Requirements Analysis Process
System Architecture
tokens
UniqueNounterms
Syntactic Parsing• Syntactic parser based on a chart parsing technique with a context-
free grammar (CFG) that is augmented with constraints.• Current prototype system • 32000 entries in Dictionary• 79 rules
• An example of context free rule:• S (i.e. LHS) NP VP (i.e. RHS)• well-formedness constraint (number-agreement NP VP)• “He see a car in the park”
• Current limitations – compound noun terms, disambiguation module
Syntactic Parsing (Contd.)• “A system requires entry of patient’s information”• (S (NP (DET “A”) (NOUN “system”))• (VP (VERB “requires”)• (NP (NP (NOUN “entry”)) (PP (OF “of”)• (NP (POSSADJ “patient’s”) (NOUN “information”))))))
• “Dunedin Podiatry requires an information system that allows entry and retrieval of patient's details and their medical histories.”• “Dunedin Podiatry”, “information system”, “entry”, “retrieval”, “(patient’s)
details”, and “(their medical) histories”
Term Extraction by a Syntactic Parser
Term Management System• Filter Entity• Manual option
• Create classes• Entity, Attribute, Function
• Manage• Knowledge base• (OBJECT (:TYPE FUNCTION) (:VALUE “entry”))• (OBJECT (:TYPE ENTITY) (:VALUE “patient”))• (OBJECT (:TYPE ATTRIBUTE) (:VALUE “age”))
Future Work• Add disambiguation module• Compound noun analysis and Proper noun processing• anaphoric resolution and semantic interpretation of terms• enhance the process of term extraction and enable term relationship
identification• “patient’s medical histories”
• One-many relationship between “patient” and “medical histories”
Conclusion• Utilize NLP to assist systems analysts in selecting and verifying objects
and relationships of relevance to any given project• Save burden of analysis for system analyst• The toolset will be intelligent enough to automatically parse, select
and relate the objects of interest from specification documents• Knowledge base helps in automatic generation of relevant design
artifacts – object models, data models, etc.
Questions?
Thank You