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Lopata, A., Ambraziunas, M., Gudas, S. (2012), “Knowledge Based MDA Requirements Specification and Validation Technique”, Transformations in Business & Economics, Vol. 11, No 1 (25), pp.248260.
BUSINESS & ECONOMICS © Vilnius University, 2002-2012 © Brno University of Technology, 2002-2012 © University of Latvia, 2002-2012
KNOWLEDGE BASED MDA REQUIREMENTS SPECIFICATION AND VALIDATION TECHNIQUE 1
Audrius Lopata
Affiliation 1: Department of Informatics Kaunas Faculty of Humanities Vilnius University Muitines str. 8 LT-44280 Kaunas Lithuania Tel.: +370 37 422566
2
Martas Ambraziunas
Department of Informatics Kaunas Faculty of Humanities Vilnius University Muitines str. 8 LT-44280 Kaunas Lithuania Tel.: +370 37 422566 E-mail:
[email protected]
3
Saulius Gudas
E-mail:
[email protected]
Affiliation 1: Department of Informatics Kaunas Faculty of Humanities Vilnius University Muitines str. 8, LT-44280 Kaunas Lithuania Tel.: +370 37 422566 E-mail:
[email protected]
Affiliation 2: Department of Information Systems Faculty of Informatics Kaunas University of Technology Studentu str. 50 LT-51368 Kaunas Lithuania Tel.: +370 37 453445
Affiliation 2: Department of Information Systems Faculty of Informatics Kaunas University of Technology Studentu str. 50, LT-51368 Kaunas Lithuania Tel.: +370 37 453445 1
Audrius Lopata, PhD, is Assoc. Prof. at Kaunas Faculty of Humanities, Vilnius University (Lithuania) and Kaunas University of Technology (Lithuania). Dr. A. Lopata is the author and co-author of more than 35 research publications in English and Lithuanian languages published in Springer’s Lecture Notes of Computer Science (2004), Business Information Processing (2009, 2010), Lecture Notes in Artificial Intelligence (2010) and other ISI Web of Science indexed and local Lithuanian journals. The main fields of scientific research incorporate Knowledge Based Information Systems Engineering, Requirements Management Techniques, Knowledge Based CASE tools. Dr. A. Lopata has experience in international (Nordforsk MINE, EUREKA, ERASMUS) as well as in Lithuanian (BPD2004 – ESF – 2.5.0 – 03 – 05/0010, ESF/2004/2.4.0-K02-VS-01/SUT-219, VP2-1.3ŪM-02-K-01-043) projects related activities.
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Martas Ambraziunas received Bachelor degree from Vytautas Magnus University (Lithuania) in 2006, MSc from Kaunas Faculty of Humanities Vilnius University (Lithuania) in 2008. Currently, he is a PhD student at Kaunas Faculty of Humanities, Vilnius University (Lithuania). The main fields of scientific research are Knowledge Based Information Systems Engineering, Requirements Management Techniques, Model Driven Information Systems Engineering. Ambraziunas has five-year work experience in developing business information systems. 3
Saulius Gudas, PhD, is Full Professor at the Department of Informatics, Kaunas Faculty of Humanities, Vilnius University (VUKHF), Lithuania. Since 2008, Dean of VU KHF. Education: in 1969–1974, studied at Kaunas University of Technology, Lithuania; in 1982 defended the PhD dissertation on the topic „Synthesis of Algorithmic Structure of Information Systems for Manufacturing Objects”; in 2005, passed the Doctor Habilitation procedure on the topic „Modelling of Knowledge-based Information Systems Engineering Processes“. Research directions are as follows: knowledge-based enterprise modelling, knowledge-based information system engineering and CASE methods. Prof. S. Gudas is the author and co-author of more than 135 research publications. Received: August, 2011 1st Revision: October, 2011 2nd Revision: January, 2012 Accepted: April, 2012
ABSTRACT. The scope of this survey is to present the main steps of Knowledge- Based MDA related Computation Independent Model’s (CIM) creation technique. The survey covers problem domain analysis and user requirements specification stages of information system’s engineering life cycle. The main idea of this research is to improve the problem domain analysis and user requirements specification stages in order to create a better quality user requirements specification document. The survey proposes knowledge-based subsystem integration into MDA approach, thus improving and intellectualizing information system engineering process in order to reduce the quantity of errors and increase the quality of final product- information system.
KEYWORDS: Business and IT Alignment Model, Strategic Alignment Model, Knowledge-Based Information System Engineering, Model Driven Architecture, Enterprise Meta-Model, UML, Computation Independent Model, Platform Independent Model, Platform Specific Model. JEL classification: M15, Y80.
Introduction The alignment of business and information technology is a key issue for top level managers of both (Information Technology and Business) fields. There is a wide range of such models, methods and recommendations including Zachman framework (Zachman, 2009), J. Henderson and N. Venkatraman Business and IT strategic alignment model (Henderson, Venkatraman, 1999) as well as various information system engineering TRANSFORMATIONS IN BUSINESS & ECONOMICS, Vol. 11, No 1 (25), 2012
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IT Applications in Economic and Managerial Studies frameworks (Centers for Medicare & Medicaid Services) but most of them propose guidelines on the abstract theoretical level only and practical implementation solutions on engineering level is still not sufficient. Problem domain analysis and user requirements specification are the initial stages of information systems engineering process. These stages are directly related with user of final information system because he directly participates in problem domain analysis and user requirements specification processes as the main actor. It is very important because all the errors made during these processes will be transferred to the following information engineering stages (design stage, development stage, and implementation stage), thus will negatively influence the final information system engineering product called information system. The usage of formal structure called Knowledge-Based Subsystem consisting of Enterprise Model and Enterprise Meta-Model in order to improve the quality of problem domain analysis and user requirements specification processes from user point of view is presented in the article. The main elements of Knowledge-Based Subsystem are Enterprise Model and Enterprise Meta-Model. The Enterprise Meta-Model is supposed to be the basic formal structure for domain knowledge accumulation for the Information System development purposes. The particular Enterprise Meta-Model (Gudas et al., 2005, 2009; Lopata, Gudas, 2008) used in this survey has been presented by joined scientific group of Vilnius University and Kaunas University of Technology. The Enterprise Meta-Model’s internal structure is based on the best practice of Enterprise Modeling standards including: CEN EN 12204 (ENV 12 204, 1996), CEN EN 40003 (CIMOSA) (ENV 40 003, 1990), UEML (Vernadat, 2001) as well as process and function interaction specified in Control Theory (Gupta, Sinha, 1996). In 2001 OMG presented Model Driven Architecture MDA approach which specifies the appliance of system models in the software development life cycle. A model of a system is a description or specification of that system and its environment for some certain purpose. A model is often presented as a combination of drawings and a text (OMG, 2003). Our survey proposes Knowledge-Based Subsystem’s integration into MDA approach, thus improving and intellectualizing information system engineering process in order to reduce the quantity of errors and increase the quality of final product – information system. MDA approach supplemented by Knowledge-Based subsystem is called Knowledge-Based MDA (Lopata, Ambraziunas, 2010a, 2010b). The main concept of Knowledge-Based MDA is to separate the specification of system functionality from the specification of the implementation of that functionality on a specific technology platform (OMG, 2003) (“What” to do from “How” to do). The main elements of Knowledge-Based MDA approach are divided into four main groups: Modeling Languages, Models, Processes and Model Transformation. The main Knowledge-Based MDA elements are presented in Figure 1. The first step of Knowledge-based MDA process is problem domain knowledge acquisition. Acquired problem domain knowledge and user requirements are the main sources for creation of Computation Independent Model (CIM) which specifies system requirements of a particular problem domain. CIM can also be named as Business Model. This step is performed manually (using specific software) participating by user and system analyst. There are four types of Unified Modeling Language (UML) diagrams used for creation of CIM: Use Case Diagram, Activity Diagram, Requirements Diagram and Block Definition Diagram. The relationships among the elements of these diagrams and elements of Enterprise Meta-Model are described below in this article. The next step is CIM transformation to Platform Independent Model (PIM).
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Source: created by the authors. Figure 1. Knowledge-Based MDA Elements
Source: created by the authors. Figure 2. The Main Steps of Knowledge-Based MDA Process
Transformation of acquired problem domain knowledge and user requirements specifications will be converted to system’s architecture components and functionality methods during this process. Transformation of PIM to Platform Specific Model (PSM) where abstract system model (“What” to do) is upgraded with targeted platform specific information TRANSFORMATIONS IN BUSINESS & ECONOMICS, Vol. 11, No 1 (25), 2012
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IT Applications in Economic and Managerial Studies (“How” to do). This step is performed semi- automatically. It means that the system analyst uses analysis and design tools that allow performing model creation and transformation process more efficiently. PIM provides system’s architecture and functionality without platform specific information and technical details. PSM is constructed on the basis of PIM enhancing it with platform specific details. The last step of Knowledge-Based MDA process is transformation of PSM to the code of particular programming platform. This step is performed automatically using particular Computer Aided System’s Engineering (CASE) tools or other specific solutions used for code generation activities. The main steps of Knowledge-Based MDA process are presented in Figure 2. 1. Knowledge-Based User Requirements Specification Process User requirements specification process is a set of activities intended to acquire, analyze and specify user’s requirements of all types. Traditionally, user requirements are classified into two main groups: functional and non-functional requirements. Functional requirements specify the particular functions of a software system or its component. Nonfunctional requirements define the overall qualities or attributes of the resulting system. The final result of user requirements specification process is user requirements specification document. Requirements engineering where the computerized problem domain analysis, user requirements acquisition and specification tools are used is called computerized user requirements specification process. Requirements engineering process can be divided into the following steps: requirements formulation, requirements acquisition, requirements specification, requirements analysis and negotiation and requirements validation. These steps in traditional user requirements specification process are performed by user and system’s analyst. The main problems of traditional user requirements specification process are listed below: • User is the only information source which provides problem domain knowledge to system analyst; • Problem domain knowledge provided by user are not verified against formal criteria; • User requirements model and specification are empirically formed by system analyst, thus negatively influences the quality of user requirements specification document. All these problems negatively influence the quality of user requirements specification document. In case incomplete or improper specified user requirements are used in the next information systems engineering stages, the final product (information system) will not work properly as well as it will not correspond to real user requirements and needs. In order to avoid such problems Knowledge-Based Subsystem should be used in user requirements specification process. The main difference between requirement engineering and KnowledgeBased requirements engineering is participating of additional actor called Knowledge-Based Subsystem. Knowledge-Based Subsystem generates constrains that are used for user requirements and problem domain knowledge validation against formal criteria specified in Knowledge-Based Subsystem component called “Enterprise Meta-Model“. Usage of Knowledge-Based Subsystem in problem domain analysis and user requirements specification stage gives the following advantages: • Knowledge Based Subsystem as additional actor of problem domain analysis and user requirements specification process specifies the set of necessary components that should be collected mandatory in order to create complete user requirements specification document. TRANSFORMATIONS IN BUSINESS & ECONOMICS, Vol. 11, No 1 (25), 2012
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IT Applications in Economic and Managerial Studies • Knowledge-Based Subsystem verifies collected problem domain knowledge and specified user requirements according to the main principles of Control Theory (i.e. each organizational process must be controlled by at least one management function, etc.) (Gupta, Sinha, 1996), thus ensuring the lower level of errors in final user requirements specification document as well as in final product- information system. The main steps of Knowledge-Based user requirements specification process are presented in Figure 3.
Source: created by the authors. Figure 3. Knowledge - Based User Requirements Specification Process
The main difference between Knowledge-Based requirements specification process and traditional user requirements specification process is the use of Knowledge- Based subsystem for Enterprise knowledge validation against formal criteria. These criteria reduce empirical factors impact on user requirements specification process and ensure that necessary information for the next stages of IS development are collected. 2. Knowledge-Based MDA’s CIM In MDA methodology CIM stands for model which defines user requirements and business rules as well as business processes. In order to create this type of model specific modeling language should be used. In our research SysML modeling language has been used for that process. This language was selected due to the following reason: SysML is modeling language created for user requirements specification and business modeling activities. This language emerged as an open source initiative and currently is developed and supported by TRANSFORMATIONS IN BUSINESS & ECONOMICS, Vol. 11, No 1 (25), 2012
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IT Applications in Economic and Managerial Studies Object Management Group (OMG), which is MDA’s founder. SysML is heavily related to UML. In fact more than half diagrams (with some modifications) are shared by SysML and UML. The common core for many diagrams ensures smooth and consistent model transformation process among the two languages in most cases (it’s worth mentioning that not all diagrams are directly compatible and there are some issues mapping SysML and UML elements). For PIM and PSM creation UML is used, so the overall Knowledge-Based MDA method is created on basis of OMG standards, that ensures reusability and integration possibilities with third-party users/providers that use the same OMG standards. There is no predefined structure of CIM as well as standardized user requirements acquisition methodologies using UML, however some authors are proposing wide usage of UML and SysML languages to heavily improve this stage of IS development (Silingas, Butleris, 2008, 2009). As mentioned OMG provides guidelines only what data should be acquired in CIM and for what purpose. SysML diagrams of four types are selected for Knowledge-Based MDA’s CIM. These diagrams are depicted in Figure 4 and described below.
Source: created by the authors. Figure 4. SysML Diagrams Intended to be used for Knowledge-Based MDA’s CIM
• Block Definition diagram – captures system’s static structure. The main element of this diagram is block which represents some part of the particular system. Blocks can have internal structure as well as definition elements like properties and operations. Blocks are related with each other with relation elements that could be of the following types: associations, generalizations, and dependencies. Block Definition diagrams can have different abstraction levels. • Use Case diagram – captures system’s functional requirements and basic behavior. The main elements are actor and use case that represent goals. Use cases can be associated with actors and another use cases. Basically, Use Case diagrams are modeling usage of the system. Use Case diagrams in most cases are the first diagrams that are created when the development of system begins. These diagrams can be as a starting point for more specific diagrams. • Activity diagram – captures system’s behavior. The main element is action, which represents an atomic operation performed by a particular actor. Actions are connected using informational and object flows as well as some specific nodes (merge node, decision node) that manage the control flows. These diagrams are used as a business model. • Requirements diagram – captures system’s non-functional requirements. The main element is requirement and relationships among requirements. Requirement (in a scope of requirements diagram) is a graphical element that represents text-based information about systems requirements. Each defined model (diagram) has its own complex internal structure – Meta-Model. These Meta-Models should be mapped to Enterprise Meta- Model in order to perform CIM to Enterprise Model transformations. TRANSFORMATIONS IN BUSINESS & ECONOMICS, Vol. 11, No 1 (25), 2012
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3. Mappings among Elements of CIM and Enterprise Meta- Model Models mapping specifies how element from one model is represented in another model. Mappings among CIM internal models (Use Case diagram, Activity diagram, Block Definition diagram, Requirements diagram) and Enterprise Meta-Model are presented in Figure 5 and Table 1. In order to perform mapping both Meta-Models should be defined. EMM consists of eleven classes, the basic of which are Process, Function and Actor. These classes can have an internal hierarchical composition and create a complex structure. The class Process according to aggregation relationship is related to the class Material Flow. Class Process, according to association relationships is related to the classes of Function, Actor and Event. According to aggregation relationship class Function is related to classes Information Flow, Information Activity as well as association relationship defines connections with Process, Actor, Goal and BusinessRule. Package is related to Event, Function and Actor. This class represents a grouping element.
Source: created by the authors. Figure 5. Mappings among Elements of CIM and EMM
The core elements of the Use Case diagram are as follows: Actor, Use Case, Extension Point, Include Point, Package and Relationships. Relationships among elements are common for all diagrams and can be of the following types: Generalization, Association, and Aggregation. Actors, Use Cases and Packages can have internal hierarchical structure. Activity diagram contains these basic elements: Action, Control Flow, Decision Point, Merge Point, Object Flow, Accept Event Action, Swimline. Requirements diagram contains these basic elements: Requirement (can have internal hierarchical structure), Relationship. Block Definition diagram contains the following basic elements: Block, Interface, Operation, ItemFlow, Property, and Relationship. Blocks can have the internal hierarchical structure.
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Attribute
Package
X
Actor
X
Business Rule
Material Flow
X
Information Activity
X
Event
Use Case Actor IncludePoint Use Case ExtentionPoint Package Relationship Action ControlFlow ObjectFlow Accept event Activity action DesitionPoint MergePoint Swimline Block Block Definition Property Method Relationship Requirements Requirement Relationship Source: created by authors.
Process
Model/elements
Function
EMM elements
Information Flow
Table 1. Mappings among Elements of CIM and EMM
X X X X X
X
X X X X X X X X X
X
X
X X
Table 1 show that some CIM internal model’s elements (e.g. Use Case, Action) can be represented by several elements of Enterprise-Meta-Model. Using defined mappings transformations from CIM to Enterprise Model can be performed automatically when UML models are consistent with each other. 4. CIM Transformations to Enterprise Model Algorithm CIM creation process begins as an interaction between system’s analyst and system’s user. System’s user provides information about system’s functional and non-functional requirements as well as structure. System’s analyst captures this information in form of predefined SysML models (diagrams). Next stage is UML models validation with each other. This process ensures that models are consistent with each other. In case UML models validation process is completed successfully, CIM transformation to Enterprise Model process can be performed. Using mappings described above CIM’s elements are transformed to EM elements. After this step is performed successfully Enterprise Model can be validated against formal criteria that are defined by Enterprise Meta-Model. In case this process is successful the next steps of Knowledge-Based MDA can be performed. If the process fails, system analyst makes decisions what additional information is needed to correct errors (e.g. missing/redundant elements, missing relationships etc.) and repeats the necessary steps. A detailed process is presented in Figure 6 and described in Table 2.
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Source: created by the authors. Figure 6. CIM Transformation to EM Transformation Process
The described process is part of larger process and represents abstract definition of requirements acquisition and validation in Knowledge-Based MDA methodology. The main difference between traditional MDA and Knowledge-Based MDA is that validation of CIM is performed twice: validation of internal UML models consistency and validation against formal criteria defined by EMM. It ensures that CIM’s syntax as well as semantics are correct. TRANSFORMATIONS IN BUSINESS & ECONOMICS, Vol. 11, No 1 (25), 2012
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IT Applications in Economic and Managerial Studies Table 2. CIM transformation to EM transformation process STEP NAME
ACTOR
Provide information systems requirements
about
Create Use Case Diagram
System Analyst System Analyst
Create Activity Diagram Provide information systems structure Create diagram
Block
User
about
definition
User System Analyst
Provide information about non-functional requirements
User
Create Requirements Diagram
System Analyst
Validate UML models Generate UML validation report
models
Analyze validation report Create EM Validate EM against EMM Generate validation report Analyze validation report Proceed to next KB-MDA steps
KnowledgeBased Subsystem KnowledgeBased Subsystem System Analyst KnowledgeBased Subsystem KnowledgeBased Subsystem Knowledge BasedSubsystem System Analyst KnowledgeBased Subsystem
STEP DESCRIPTION User communicates with system analyst and provides system requirements and information about expectable system behavior. On the basis of information provided by user system analyst creates Use Case diagram. On the basis of information provided by user system analyst creates Activity diagram. User communicates with system analyst and provides information about organization structure and elements On the basis of information provided by user system analyst creates systems structure defining Block Definition diagram. User provides information regarding systems nonfunctional requirements. On the basis of information provided by user system analyst creates systems requirements defining Requirements diagram. UML models consistency validation is performed using predefined rules. Missing/ redundant elements are specified during this process. Depending on parameters set, Knowledge-Based subsystem generates report about occurred consistency errors. System analyst decides if process can proceed to next steps or some additional information is needed and models (diagrams) should be appended with new data. Using defined mappings EM is created from CIM data. EM is validated against formal criteria that are defined by EMM. Depending on parameters set, Knowledge-Based subsystem generates report about occurred errors. System Analyst decides whether process can be proceeded to next Knowledge-Based MDA steps. Next transformations can be performed: EM to PIM, PIM to PSM and PSM to code.
Source: created by the authors.
Conclusions Knowledge-Based MDA requirements specification and validation technique is presented in the article. MDA improved by Knowledge-Based Subsystem gives user and system analyst a competitive advantage as by using the proposed technique the acquired problem domain knowledge is verified against formal criteria defined by Knowledge-Based subsystem’s main component-Enterprise Meta-Model. It influences lower level of errors in final problem domain analysis and user requirements specification result-user requirements specification document. Problem domain knowledge and user requirements should be TRANSFORMATIONS IN BUSINESS & ECONOMICS, Vol. 11, No 1 (25), 2012
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IT Applications in Economic and Managerial Studies specified using Computation Independent Model consisting of the following SysML models: Use Case, Activity, Requirements, and Block Definition. The main steps of Knowledge-Based MDA process as well as the main stages of user requirements specification process and CIM model elements mappings with Enterprise Meta-Model elements are presented in the article. The survey proposes Knowledge-Based Subsystem integration into MDA approach, thus improves and intellectualizes information systems engineering process in order to reduce the quantity of errors and increase the quality of final product- information system. References ENV 12 204 (1996), Advanced Manufacturing Technology Systems Architecture - Constructs for Enterprise Modelling, CEN TC 310/WG1. ENV 40 003 (1990), Computer Integrated Manufacturing Systems Architecture - Framework for Enterprise Modelling, CEN/CENELEC. Gudas, S., Pakalnickas, E. (2009), “Enterprise Management view based Specification of Business Components”, 15th international conference on Information and software technologies, IT’2009, pp.417-426. Gudas, S., Lopata, A., Skersys T. (2005), “Approach to Enterprise Modeling for Information Systems Engineering”, Informatica, Vol. 16, No 2, pp.175-192. Henderson, J., Venkatraman N. (1999), “Strategic Alignment: Leveraging Information Technology for Transforming Organizations”, IBM Systems Journal, Vol. 38, No 2/3, pp.472-484. Lopata, A., Gudas, S. (2008), “Enterprise model based computerized specification method of user functional requirements”, International conference 20th EURO mini conference Continuous optimization and Knowledge-based Technologies (EuroOpt-2008), pp.456-461. Silingasn, D., Butleris, R. (2008), “UML-intensive framework for modeling software requirements”, Information Technologies’ 2008, Proceedings of the 14th International Conference on Information and Software Technologies, IT 2008, Kaunas, Lithuania, April 24-25, 2008, Kaunas University of Technology, pp.334342. Lopata, A., Ambraziunas, M. (2010a), “Knowledge Subsystem’s Integration into MDA Based Forward and Reverse IS Engineering”, Proceedings of 16th International Conference on Information and Software Technologies “Information Technologies 2010”, pp.205-210. Lopata, A., Ambraziunas, M. (2010b), “MDA Compatible Knowledge- Based IS Engineering Approach”, International Conference, AICI 2010, pp.386. Vernadat, F. (2001), “UEML: Towards a Unified Enterprise modelling language”, International Conference on Industrial Systems Design, Analysis and Management (MOSIM’01), available at, http://www.univtroyes.fr/mosim01, referred on 18/12/2010. OMG: MDA Guide Version 1.0.1// (2009), available at, www.omg.com, referred on 15/09/2009. Zachman J.A. (2009), Zachman Framework, available at, http://zachmaninternational.com/2/Home.asp, referred on 15/07/2011. Gupta, M.M., Sinha, N.K. (1996), Intelligent Control Systems: Theory and Applications, The Institute of Electrical and Electronic Engineers Inc., New York. Silingas D., Butleris R. (2009), “Towards Implementing a Framework for Modeling Software Requirements in MagicDraw UML”, Information Technology And Control, Vol. 38, No 2, pp.153-164. Centers for Medicare & Medicaid Services (2008), Selecting a Development approach, available at, www.cms.gov/SystemLifecycleFramework/Downloads/SelectingDevelopmentApproach.pdf, referred on 15/07/2011.
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IT Applications in Economic and Managerial Studies ŽINIOMIS GRINDŽIAMOS MDA ARCHITEKTŪROS SPECIFIKAVIMO IR VALIDAVIMO BŪDAS
VARTOTOJO
REIKALAVIMŲ
Audrius Lopata, Martas Ambraziūnas, Saulius Gudas SANTRAUKA Straipsnyje analizuojamas žinios grindžiamos informacijos sistemų inžinerijos taikymo veiklos modeliavimo ir vartotojo reikalavimų specifikavimo etapuose būdas. Veiklos modeliavimas ir vartotojo reikalavimų specifikavimas- pradiniai informacijos sistemos kūrimo etapai, todėl būtina užtikrinti juose vykstančių procesų kokybę, nes šiuose etapuose įvykusios klaidos neigiamai įtakos tolimesnius informacijos sistemos kūrimo etapus (projektavimą, programavimą, testavimą, diegimą), o taip pat atsispindės ir galutiniame produkte- sukurtoje informacinėje sistemoje. Straipsnyje pateikiama CIM modelio sudarymo technologija užtikrinanti kokybiškesnį veiklos modeliavimo ir vartotojo reikalavimų specifikavimo procesą tuo užtikrinanti mažesnį klaidų kiekį pradiniuose informacijos sistemų inžinerijos etapuose. REIKŠMINIAI ŽODŽIAI: veiklos ir IT suderinamumo modelis, strateginio suderinamumo modelis, žiniomis grindžiama IS inžinerija, modeliais grindžiama architektūra, veiklos metamodelis, UML.
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