UML Vs. IDEF: an ONTOLOGY-ORIENTED COMPARATIVE STUDY in VIEW of BUSINESS MODELLING
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Introduction Development Lifecycle Model
DeveIopment of a Comprehensive Software Engineering Environment Thomas C. Hartrum Gary B. Lamont Department of Electrical and Computer Engineering Department of Electrical and Computer Engineering School of Engineering School of Engineering Air Force Institute of Technology Air Force Institute of Technology Wright-Patterson AFB, Dayton, Ohio, 45433 Wright-Patterson AFB, Dayton, Ohio, 45433 Abstract The concept of an integrated software development environment The generation of a set of tools for the software lifecycle is a recur- can be realized in two distinct levels. The first level deals with the ring theme in the software engineering literature. The development of access and usage mechanisms for the interactive tools, while the sec- such tools and their integration into a software development environ- ond level concerns the preservation of software development data and ment is a difficult task at best because of the magnitude (number of the relationships between the products of the different software life variables) and the complexity (combinatorics) of the software lifecycle cycle stages. The first level requires that all of the component tools process. An initial development of a global approach was initiated at be resident under one operating system and be accessible through a AFIT in 1982 as the Software Development Workbench (SDW). Also common user interface. The second level dictates the need to store de- other restricted environments have evolved emphasizing Ada and di5 velopment data (requirements specifications, designs, code, test plans tributed processing. Continuing efforts focus on tool development, and procedures, manuals, etc.) in an integrated data base that pre- tool integration, human interfacing (graphics; SADT, DFD, structure serves the relationships between the products of the different life cy- charts, ...), data dictionaries, and testing algorithms. -
Infrastructure) IMS > J
NE DO-IT-O 0 16 <i#^^0%'IW#^#^#(Hyper-Intellectual-IT Infrastructure) IMS > J TO 1 3 ¥ 3 M NEDD H»* r— • ^ ’V^^ m) 010018981-0 (Hyper-Intellectual-IT fr9, (Hyper IT) i-6Z 6 & g 1% ^ L/bo i2 NEDO-IT-0016 < (Hyper-Intel lectual-IT Infrastructure) 9H3E>J 1 3 # 3 ^ lT5fe (%) B^f-r^'a'W^ZPJf (Summary) -f — t 7-j'<7)7*0- K/O- % -y f-7-? ±K*EL/--:#<<7)->5a.v-j'^T*-j'^-7OTSmiLr1 Eft • Skit • tWs§ (Otis ti® o T S T V' £ „ Ltf' U - 7- L*{Hffi,»ftffiIBIS<7)'> 5 a. V- -> 3 >^x- ? ^-Xfijfflic-7V>TI±#<<7)*®»:C0E@»S»6L, -en<b»sili*5tL^itn(i\ *7h Ty — t’ 4-^hLfcE&tt>fc1SSSeF% • Eft • KS& k" f> $ $ & b ttv>, (1) 3>ti- (2) f -^ (3) $-y t-7-7 (4) ->i ( 5 ) 7 7 t 73H7ft#-9— fxwilttas Sti:, ±EP$t t k ic, KSUWSSiaBF^ ■ Elt ■ # ## k T-<7)FB1«6 4-$v>tti u iirn *iiM LrtlSS-S k a6* 0 (1) Hyper-IT 4 7 —-y OEE$l&teH k $l!$ (2 ) Hyper-IT -f7-y*k##<7)tbK (3) KS<7)i5tv^k (4) #@<7)SEE • IISE<7)#S (5) Hwif^silftftkn-KvyT ’tt Summary In recently years, we have broad band network and The Internet environment , using these infrastructure, we will develop knowledge co-operate manufacturing support system, which can be use various kinds of simulators and databases. But knowledge co-operate manufacturing support system has a lot of problems, such as data format, legal problems, software support system and so no. -
Job Description - Software Engineer I
Job Description - Software Engineer I Department: Engineering - 2013-03 Exemption Status: Non-Exempt Summary: This position is responsible for software development in multi-application, multi-server, and hosted environments. The candidate will primarily provide system/configuration support with a focus in helping the needs of both internal and external customers. He or she will participate in all facets of software and system development life-cycle. The most qualified candidate for this role will have experience working with business intelligence in the public safety and/or public health software fields and have formal software education and/or a ton of practical experience. We develop primarily in C#, .NET, SQL, SSRS and mobile. Anyone that might fit well at FirstWatch must be hard-working, people-oriented, friendly, patient, a fast learner, think quickly on their feet, take initiative and responsibility, and LOVE providing our customers great and honest customer service. This person will need to maintain a high quality productivity level within a fast paced environment. This position shares responsibility (rotates) with other engineering staff for 24×7 on call duties and so must be able to thrive in this environment. Responsibilities: - Maintain and modify the software and system configurations of production, staged, and test applications. - Interface with different stakeholders to determine and propose appropriate and effective technology solutions to meet business and technical objectives. - Develop interfaces, applications and other technical solutions to support the business needs through the planning, analysis, design, development, implementation and maintenance phases of the software and systems development lifecycle. - Create system requirements, technical specifications, and test plans. -
Structured Programming - Retrospect and Prospect Harlan D
University of Tennessee, Knoxville Trace: Tennessee Research and Creative Exchange The aH rlan D. Mills Collection Science Alliance 11-1986 Structured Programming - Retrospect and Prospect Harlan D. Mills Follow this and additional works at: http://trace.tennessee.edu/utk_harlan Part of the Software Engineering Commons Recommended Citation Mills, Harlan D., "Structured Programming - Retrospect and Prospect" (1986). The Harlan D. Mills Collection. http://trace.tennessee.edu/utk_harlan/20 This Article is brought to you for free and open access by the Science Alliance at Trace: Tennessee Research and Creative Exchange. It has been accepted for inclusion in The aH rlan D. Mills Collection by an authorized administrator of Trace: Tennessee Research and Creative Exchange. For more information, please contact [email protected]. mJNDAMNTL9JNNEPTS IN SOFTWARE ENGINEERING Structured Programming. Retrospect and Prospect Harlan D. Mills, IBM Corp. Stnuctured program- 2 ' dsger W. Dijkstra's 1969 "Struc- mon wisdom that no sizable program Ste red .tured Programming" articlel could be error-free. After, many sizable ming haxs changed ho w precipitated a decade of intense programs have run a year or more with no programs are written focus on programming techniques that has errors detected. since its introduction fundamentally alteredhumanexpectations and achievements in software devel- Impact of structured programming. two decades ago. opment. These expectations and achievements are However, it still has a Before this decade of intense focus, pro- not universal because of the inertia of lot of potentialfor gramming was regarded as a private, industrial practices. But they are well- lot of fo puzzle-solving activity ofwriting computer enough established to herald fundamental more change. -
Data Model Standards and Guidelines, Registration Policies And
Data Model Standards and Guidelines, Registration Policies and Procedures Version 3.2 ● 6/02/2017 Data Model Standards and Guidelines, Registration Policies and Procedures Document Version Control Document Version Control VERSION D ATE AUTHOR DESCRIPTION DRAFT 03/28/07 Venkatesh Kadadasu Baseline Draft Document 0.1 05/04/2007 Venkatesh Kadadasu Sections 1.1, 1.2, 1.3, 1.4 revised 0.2 05/07/2007 Venkatesh Kadadasu Sections 1.4, 2.0, 2.2, 2.2.1, 3.1, 3.2, 3.2.1, 3.2.2 revised 0.3 05/24/07 Venkatesh Kadadasu Incorporated feedback from Uli 0.4 5/31/2007 Venkatesh Kadadasu Incorporated Steve’s feedback: Section 1.5 Issues -Change Decide to Decision Section 2.2.5 Coordinate with Kumar and Lisa to determine the class words used by XML community, and identify them in the document. (This was discussed previously.) Data Standardization - We have discussed on several occasions the cross-walk table between tabular naming standards and XML. When did it get dropped? Section 2.3.2 Conceptual data model level of detail: changed (S) No foreign key attributes may be entered in the conceptual data model. To (S) No attributes may be entered in the conceptual data model. 0.5 6/4/2007 Steve Horn Move last paragraph of Section 2.0 to section 2.1.4 Data Standardization Added definitions of key terms 0.6 6/5/2007 Ulrike Nasshan Section 2.2.5 Coordinate with Kumar and Lisa to determine the class words used by XML community, and identify them in the document. -
Best Practices in Business Instruction. INSTITUTION Delta Pi Epsilon Society, Little Rock, AR
DOCUMENT RESUME ED 477 251 CE 085 038 AUTHOR Briggs, Dianna, Ed. TITLE Best Practices in Business Instruction. INSTITUTION Delta Pi Epsilon Society, Little Rock, AR. PUB DATE 2001-00-00 NOTE 97p. AVAILABLE FROM Delta Pi Epsilon, P.O. Box 4340, Little Rock, AR 72214 ($15). Web site: http://www.dpe.org/ . PUB TYPE Collected Works General (020) Guides Classroom Teacher (052) EDRS PRICE EDRS Price MF01/PC04 Plus Postage. DESCRIPTORS Accounting; *Business Education; Career Education; *Classroom Techniques; Computer Literacy; Computer Uses in Education; *Educational Practices; *Educational Strategies; Group Instruction; Keyboarding (Data Entry); *Learning Activities; Postsecondary Education; Secondary Education; Skill Development; *Teaching Methods; Technology Education; Vocational Adjustment; Web Based Instruction IDENTIFIERS *Best Practices; Electronic Commerce; Intranets ABSTRACT This document is intended to give business teachers a few best practice ideas. Section 1 presents an overview of best practice and a chart detailing the instructional levels, curricular areas, and main competencies addressed in the 26 papers in Section 2. The titles and authors of the papers included in Section 2 are as follows: "A Software Tool to Generate Realistic Business Data for Teaching" (Catherine S. Chen); "Alternatives to Traditional Assessment of Student Learning" (Nancy Csapo); "Applying the Principles of Developmental Learning to Accounting Instruction" (Burt Kaliski); "Collaborative Teamwork in the Classroom" (Shelia Tucker); "Communicating Statistics Measures of Central Tendency" (Carol Blaszczynski); "Creating a Global Business Plan for Exporting" (Les Dlabay); "Creating a Supportive Learning Environment" (Rose Chinn); "Developing Job Survival Skills"(R. Neil Dortch); "Engaging Students in Personal Finance and Career Awareness Instruction: 'Welcome to the Real World!'" (Thomas Haynes); "Enticing Students to Prepare for and to Stay 'Engaged' during Class Presentations/Discussions" (Zane K. -
Integration Definition for Function Modeling (IDEF0)
NIST U.S. DEPARTMENT OF COMMERCE PUBLICATIONS £ Technology Administration National Institute of Standards and Technology FIPS PUB 183 FEDERAL INFORMATION PROCESSING STANDARDS PUBLICATION INTEGRATION DEFINITION FOR FUNCTION MODELING (IDEFO) » Category: Software Standard SUBCATEGORY: MODELING TECHNIQUES 1993 December 21 183 PUB FIPS JK- 45C .AS A3 //I S3 IS 93 FIPS PUB 183 FEDERAL INFORMATION PROCESSING STANDARDS PUBLICATION INTEGRATION DEFINITION FOR FUNCTION MODELING (IDEFO) Category: Software Standard Subcategory: Modeling Techniques Computer Systems Laboratory National Institute of Standards and Technology Gaithersburg, MD 20899 Issued December 21, 1993 U.S. Department of Commerce Ronald H. Brown, Secretary Technology Administration Mary L. Good, Under Secretary for Technology National Institute of Standards and Technology Arati Prabhakar, Director Foreword The Federal Information Processing Standards Publication Series of the National Institute of Standards and Technology (NIST) is the official publication relating to standards and guidelines adopted and promulgated under the provisions of Section 111 (d) of the Federal Property and Administrative Services Act of 1949 as amended by the Computer Security Act of 1987, Public Law 100-235. These mandates have given the Secretary of Commerce and NIST important responsibilities for improving the utilization and management of computer and related telecommunications systems in the Federal Government. The NIST, through its Computer Systems Laboratory, provides leadership, technical guidance, -
DATA MODELS to SUPPORT METROLOGY by Saeed
DATA MODELS TO SUPPORT METROLOGY by Saeed Heysiattalab A dissertation submitted to the faculty of The University of North Carolina at Charlotte in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Mechanical Engineering Charlotte 2017 Approved by: ______________________________ Dr. Edward P. Morse ______________________________ Dr. Robert G. Wilhelm ______________________________ Dr. Jimmie A Miller ______________________________ Dr. M. Taghi Mostafavi ______________________________ Dr. Jing Xiao ii ©2017 Saeed Heysiattalab ALL RIGHTS RESERVED iii ABSTRACT SAEED HEYSIATTALAB. Data models to support metrology (Under the supervision of Dr. EDWARD P. MORSE) The Quality Information Framework (QIF) is a project initiated in 2010 by the Dimensional Metrology Standards Consortium (DMSC is an American Standards Developing Organization) to address metrology interoperability. Specifically, the QIF supports the exchange of metrology-relevant information throughout the product lifecycle from the design stage through manufacturing, inspection, maintenance, and recycling / end-of-life processing. The QIF standard is implemented through a set of XML schemas called "Application Schemas" along with common core "XML schema libraries". Of these schemas, QIF Measurement Resources and QIF Rules are the two application schemas on which this research is focused. QIF Measurement Resources is an application schema developed to provide standard representations of physical measuring tools and components, and can be used to support measurement planning, statistical studies, traceability, etc. The Resources schema was supported by the creation of a new hierarchy of metrology resources in support of the product lifecycle. The QIF Rules schema is under development to provide the language with which manufacturers can define how dimensional measurement equipment is selected for various tasks, and how this equipment is used during the measurement task. -
Identifying and Defining Relationships: Techniques for Improving Student Systemic Thinking
AC 2011-897: IDENTIFYING AND DEFINING RELATIONSHIPS: TECH- NIQUES FOR IMPROVING STUDENT SYSTEMIC THINKING Cecelia M. Wigal, University of Tennessee, Chattanooga Cecelia M. Wigal received her Ph.D. in 1998 from Northwestern University and is presently a Professor of Engineering and Assistant Dean of the College of Engineering and Computer Science at the University of Tennessee at Chattanooga (UTC). Her primary areas of interest and expertise include complex process and system analysis, process improvement analysis, and information system analysis with respect to usability and effectiveness. Dr. Wigal is also interested in engineering education reform to address present and future student and national and international needs. c American Society for Engineering Education, 2011 Identifying and Defining Relationships: Techniques for Improving Student Systemic Thinking Abstract ABET, Inc. is looking for graduating undergraduate engineering students who are systems thinkers. However, genuine systems thinking is contrary to the traditional practice of using linear thinking to help solve design problems often used by students and many practitioners. Linear thinking has a tendency to compartmentalize solution options and minimize recognition of relationships between solutions and their elements. Systems thinking, however, has the ability to define the whole system, including its environment, objectives, and parts (subsystems), both static and dynamic, by their relationships. The work discussed here describes two means of introducing freshman engineering students to thinking systemically or holistically when understanding and defining problems. Specifically, the modeling techniques of Rich Pictures and an instructor generated modified IDEF0 model are discussed. These techniques have roles in many applications. In this case they are discussed in regards to their application to the design process. -
Using Telelogic DOORS and Microsoft Visio to Model and Visualize Complex Business Processes
Using Telelogic DOORS and Microsoft Visio to Model and Visualize Complex Business Processes “The Business Driven Application Lifecycle” Bob Sherman Procter & Gamble Pharmaceuticals [email protected] Michael Sutherland Galactic Solutions Group, LLC [email protected] Prepared for the Telelogic 2005 User Group Conference, Americas & Asia/Pacific http://www.telelogic.com/news/usergroup/us2005/index.cfm 24 October 2005 Abstract: The fact that most Information Technology (IT) projects fail as a result of requirements management problems is common knowledge. What is not commonly recognized is that the widely haled “use case” and Object Oriented Analysis and Design (OOAD) phenomenon have resulted in little (if any) abatement of IT project failures. In fact, ten years after the advent of these methods, every major IT industry research group remains aligned on the fact that these projects are still failing at an alarming rate (less than a 30% success rate). Ironically, the popularity of use case and OOAD (e.g. UML) methods may be doing more harm than good by diverting our attention away from addressing the real root cause of IT project failures (when you have a new hammer, everything looks like a nail). This paper asserts that, the real root cause of IT project failures centers around the failure to map requirements to an accurate, precise, comprehensive, optimized business model. This argument will be supported by a using a brief recap of the history of use case and OOAD methods to identify differences between the problems these methods were intended to address and the challenges of today’s IT projects. -
Modelling, Analysis and Design of Computer Integrated Manueactur1ng Systems
MODELLING, ANALYSIS AND DESIGN OF COMPUTER INTEGRATED MANUEACTUR1NG SYSTEMS Volume I of II ABDULRAHMAN MUSLLABAB ABDULLAH AL-AILMARJ October-1998 A thesis submitted for the DEGREE OP DOCTOR OF.PHILOSOPHY MECHANICAL ENGINEERING DEPARTMENT, THE UNIVERSITY OF SHEFFIELD 3n ti]S 5íamc of Allai]. ¿Hoot (gractouo. iHHoßt ¿Merciful. ACKNOWLEDGEMENTS I would like to express my appreciation and thanks to my supervisor Professor Keith Ridgway for devoting freely of his time to read, discuss, and guide this research, and for his assistance in selecting the research topic, obtaining special reference materials, and contacting industrial collaborations. His advice has been much appreciated and I am very grateful. I would like to thank Mr Bruce Lake at Brook Hansen Motors who has patiently answered my questions during the case study. Finally, I would like to thank my family for their constant understanding, support and patience. l To my parents, my wife and my son. ABSTRACT In the present climate of global competition, manufacturing organisations consider and seek strategies, means and tools to assist them to stay competitive. Computer Integrated Manufacturing (CIM) offers a number of potential opportunities for improving manufacturing systems. However, a number of researchers have reported the difficulties which arise during the analysis, design and implementation of CIM due to a lack of effective modelling methodologies and techniques and the complexity of the systems. The work reported in this thesis is related to the development of an integrated modelling method to support the analysis and design of advanced manufacturing systems. A survey of various modelling methods and techniques is carried out. The methods SSADM, IDEFO, IDEF1X, IDEF3, IDEF4, OOM, SADT, GRAI, PN, 10A MERISE, GIM and SIMULATION are reviewed. -
Principles of the Concept-Oriented Data Model Alexandr Savinov
Principles of the Concept-Oriented Data Model Alexandr Savinov Institute of Mathematics and Computer Science Academy of Sciences of Moldova Academiei 5, MD-2028 Chisinau, Moldova Fraunhofer Institute for Autonomous Intelligent System Schloss Birlinghoven, 53754 Sankt Augustin, Germany http://www.conceptoriented.com [email protected] Principles of the Concept-Oriented Data Model Alexandr Savinov Institute of Mathematics and Computer Science, Academy of Sciences of Moldova Academiei 5, MD-2028 Chisinau, Moldova Fraunhofer Institute for Autonomous Intelligent System Schloss Birlinghoven, 53754 Sankt Augustin, Germany http://www.conceptoriented.com [email protected] In the paper a new approach to data representation and manipulation is described, which is called the concept-oriented data model (CODM). It is supposed that items represent data units, which are stored in concepts. A concept is a combination of superconcepts, which determine the concept’s dimensionality or properties. An item is a combination of superitems taken by one from all the superconcepts. An item stores a combination of references to its superitems. The references implement inclusion relation or attribute- value relation among items. A concept-oriented database is defined by its concept structure called syntax or schema and its item structure called semantics. The model defines formal transformations of syntax and semantics including the canonical semantics where all concepts are merged and the data semantics is represented by one set of items. The concept-oriented data model treats relations as subconcepts where items are instances of the relations. Multi-valued attributes are defined via subconcepts as a view on the database semantics rather than as a built-in mechanism.