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SMART

SMART. S ystem M odel A cquisition from R equirements T ext BPM 2004 Potsdam, Germany, June 17-18, 2004. Dov Dori Nahum Korda Avi Soffer Shalom Cohen Technion – Israel Institute of Technology. Introduction.

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SMART

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  1. SMART System Model Acquisition from Requirements Text BPM 2004 Potsdam, Germany, June 17-18, 2004 Dov Dori Nahum Korda Avi Soffer Shalom Cohen Technion – Israel Institute of Technology

  2. Introduction • Transformation of free-format business and user requirements into a formal system specification is a complex and laborious operation. • The clutter of details prevents seeing ‘the big picture’ and focusing on the system goals Freely expressed ideas, Concepts, and intentions Formal System Specification System Inception SMART - System Model Acquisition from Requirements Text Technion – Israel Institute of Technology

  3. SMART Processing • The challenge: convert free natural language requirements text into a formal, machine-processable model • The SMART idea: acquire the system model through an automated process based on extracting semantics from free-format text SMART Freely expressed ideas, Concepts, and intentions SMART - System Model Acquisition from Requirements Text Technion – Israel Institute of Technology

  4. Two required SMART technologies: • Information Extraction Technology, capable of: • Identifying elements that are key concepts for the domain and problem at hand • Deriving a semi-formalized representation of the underlying documentation. • A system modeling environment, capable of: • Human-oriented intuitive expression of complex system structure and behavior • Formalism that allows machine processing SMART - System Model Acquisition from Requirements Text Technion – Israel Institute of Technology

  5. WhatisOPM - Object-Process Methodology? A comprehensive paradigm for • modeling • engineering • lifecycle support of complex, multi-disciplinary systems SMART - System Model Acquisition from Requirements Text Technion – Israel Institute of Technology

  6. OPM’s Building Blocks are Things: Objects andProcesses Object Process SMART - System Model Acquisition from Requirements Text Technion – Israel Institute of Technology

  7. Entities: Objects, Processes, States • Objects and processes are two types of equally important things (entities) required to describe a system in a single, unifying model • At any point in time, each object is at some state • Object states are transformed through the occurrence of a process SMART - System Model Acquisition from Requirements Text Technion – Israel Institute of Technology

  8. A process changes an object’s state SMART - System Model Acquisition from Requirements Text Technion – Israel Institute of Technology

  9. A process generates a new object SMART - System Model Acquisition from Requirements Text Technion – Israel Institute of Technology

  10. OPM has a single model with abimodal representation A single diagram type: Object-Process Diagram (OPD) A corresponding subset of language: Object-Process Language (OPL) SMART - System Model Acquisition from Requirements Text Technion – Israel Institute of Technology

  11. Resources: OPM book Dov Dori Object-Process Methodology - A Holistic Systems Paradigm, Springer Verlag, Berlin, Heidelberg, New York, 2002 SMART - System Model Acquisition from Requirements Text Technion – Israel Institute of Technology

  12. Resources: OPM Websitewww.ObjectProcess.org Free OPCAT downloads Publications SMART - System Model Acquisition from Requirements Text Technion – Israel Institute of Technology

  13. Input Output The SMART System Framework System Architecting Team handles System Model Acquisition. System Model Acquisition requires System Requirements In Natural Language. System Model Acquisition yields System Model. OPD OPL SMART - System Model Acquisition from Requirements Text Technion – Israel Institute of Technology

  14. OPCAT – Object-Process CASE Tool Tree OPD OPL SMART - System Model Acquisition from Requirements Text Technion – Israel Institute of Technology

  15. SMART - System Diagram SMART Categorization Engine OPL Generator OPCAT System Model Acquisition System Requirements Unstructured Text System Architecting Team System Model SMART - System Model Acquisition from Requirements Text Technion – Israel Institute of Technology

  16. System ModelAcquisition System Model Acquisition Process In-zoomed SMART System Requirements Unstructured Text Category Extraction Categorization Engine Category List edited raw System Architecting Team List Editing Relation Formulating Relation Set OPL Generator OPL Sentence Generating OPL Sentence Set OPCAT OPD Constructing System Model SMART - System Model Acquisition from Requirements Text Technion – Israel Institute of Technology

  17. SMART – Procedural Steps • Automatic Extraction of Categories from Unstructured Text • Manual Manipulation of Categories • Automatic Search of OPM Relations • Automatic Generation of OPL Sentences • Manual Enhancement of the Results Free-Format Text SMART - System Model Acquisition from Requirements Text Technion – Israel Institute of Technology

  18. 1. Automatic Extraction of Categories from Unstructured Text • Categories = idiomatic phrases (word sequences) • Reflect the underlying topics in a given corpus of documents • Categorization engine based on heuristics • Implemented in Common LISP • Can combine external • Ontologies • Taxonomies • Thesauri SMART - System Model Acquisition from Requirements Text Technion – Israel Institute of Technology

  19. 2. Manual Manipulation of Categories • Selecting categories that can be things in the OPM model • Classifying them as either objects or processes • Clustering of alternative formulations for the selected OPM things based on their semantic similarity • Option for manually adding OPM things that did not show up among the extracted categories SMART - System Model Acquisition from Requirements Text Technion – Israel Institute of Technology

  20. 3. Automatic Search of OPM Relations • Utilizes a set of configurable, predefined templates: • Template consists of two things and the relation between them, expressed in alternative ways • Utilizes second order regular expressions defined on any lexical or grammatical attribute (part‑of‑speech, capitalization, punctuation) • Finite‑state automaton that operates on a suffix‑tree index consisting of tokens • Word-based: Instead of comparing character strings, compares word sequences SMART - System Model Acquisition from Requirements Text Technion – Israel Institute of Technology

  21. 4. Automatic Generation of OPL Sentences • Every extracted natural language sentence is s translated into OPL • Reformulation of outcome to better reflect the underlying relations: • Custom relations transformed into processes (cached into=> Caching) • Complex relations transformed into two equivalent simple sentences: Actual Documents cached into Document Repositories. => • CachingrequiresActual Documents. • CachingyieldsDocument Repositories. • Transformations maintain original underlying semantics of the NL sentence SMART - System Model Acquisition from Requirements Text Technion – Israel Institute of Technology

  22. 5. Manual Enhancement of the Results • Non-semantic corrections– extraction did not depict all of the existing or implied relations • Additions and eliminations - semantically modify original output • Scaling applied to simplify results without losing details SMART - System Model Acquisition from Requirements Text Technion – Israel Institute of Technology

  23. The SMART Experiment • Demonstrates the feasibility of automating the most critical step in the system engineering process. • Based on GRACE (Grid Retrieval And Categorization Engine), a European Community Information Society Technology (IST) project. • Designed as proof-of-concept, offering hands-on experience required for the development of a future full-scale industrial application. SMART - System Model Acquisition from Requirements Text Technion – Israel Institute of Technology

  24. SMART Benefits • Reduces the initial level of conceptual complexity when starting to build a system • Significantly reduces the quantity of material that needs to be processed manually • Graphic manipulation (in OPD) much easier than text editing • Quality, accuracy, and conciseness of the system architecture is higher due to the discipline OPM introduces at an early stage • Capable of automatic generation of UML diagrams SMART - System Model Acquisition from Requirements Text Technion – Israel Institute of Technology

  25. The Future of SMART • Component in 6th Framework EEC IST-202-507126 COCOON (Building Knowledge-driven and Dynamically Networked Communities within European Healthcare Systems) • Further R&D: more sophisticated extraction templates, increased level of automation, improved performance • Commercial pilot application planned SMART - System Model Acquisition from Requirements Text Technion – Israel Institute of Technology

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