The Sysml Modelling Language
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INCOSE: the FAR Approach “Functional Analysis/Allocation and Requirements Flowdown Using Use Case Realizations”
in Proceedings of the 16th Intern. Symposium of the International Council on Systems Engineering (INCOSE'06), Orlando, FL, USA, Jul 2006. The FAR Approach – Functional Analysis/Allocation and Requirements Flowdown Using Use Case Realizations Magnus Eriksson1,2, Kjell Borg1, Jürgen Börstler2 1BAE Systems Hägglunds AB 2Umeå University SE-891 82 Örnsköldsvik SE-901 87 Umeå Sweden Sweden {magnus.eriksson, kjell.borg}@baesystems.se {magnuse, jubo}@cs.umu.se Copyright © 2006 by Magnus Eriksson, Kjell Borg and Jürgen Börstler. Published and used by INCOSE with permission. Abstract. This paper describes a use case driven approach for functional analysis/allocation and requirements flowdown. The approach utilizes use cases and use case realizations for functional architecture modeling, which in turn form the basis for design synthesis and requirements flowdown. We refer to this approach as the FAR (Functional Architecture by use case Realizations) approach. The FAR approach is currently applied in several large-scale defense projects within BAE Systems Hägglunds AB and the experience so far is quite positive. The approach is illustrated throughout the paper using the well known Automatic Teller Machine (ATM) example. INTRODUCTION Organizations developing software intensive defense systems, for example vehicles, are today faced with a number of challenges. These challenges are related to the characteristics of both the market place and the system domain. • Systems are growing ever more complex, consisting of tightly integrated mechanical, electrical/electronic and software components. • Systems have very long life spans, typically 30 years or longer. • Due to reduced acquisition budgets, these systems are often developed in relatively short series; ranging from only a few to several hundred units. -
CDA Logical Data Design
DEPARTMENT OF HEALTH & HUMAN SERVICES Centers for Medicare & Medicaid Services 7500 Security Boulevard, Mail Stop N2-14-26 Baltimore, Maryland 21244-1850 Central Data Administration ________________________ Logical Data Design ________________________ September 1, 2013 Prepared by: Centers for Medicare & Medicaid Services (CMS) Office of Information Services (OIS) Enterprise Data Group (EDG) Division of Data Enterprise Services (DDES) 7500 Security Boulevard, Baltimore, Maryland 21244-1850 Logical Data Design Revision\Change Description History Log Revision Date Revision\Change Description Pages Affected Version 1.0 12/13/2005 Initial Draft All Version 2.0 11/13/2009 Added role descriptions and All differentiated between local DA and central DA responsibilities. Version 3.0 3/23/2010 Added new reference to Section 1.7.1 pp 25 Version 4.0 9/27/2010 Add an additional Logical Model review pp 7 - 30 after the Design Phase Version 5.0 10/30/2012 Update seeding Logical Model with pp 13, 24, 26-27 ELDM. Changed EDM to ELDM. Added 1.8.2 Update ELDM from PLDM. Replace a reference to DM OP-023 (obsolete) to the New Model Design Review document. Version 6.0 9/01/2013 Updated references to the DM OP&G All document. Replaced all guidelines with operating procedures. Moved sections 1.2.4 and 1.2.5 to 1.3.3 and 1.3.4. 09/01/2013 Logical Data Design Page 2 Logical Data Design Table of Contents 1. LOGICAL DATA DESIGN .................................................................................................................................................... 4 1.1. INITIATE DATA DESIGN SERVICES ....................................................................................................................................... 7 1.2. ASSESS DATA DESIGN NEED ............................................................................................................................................... 9 1.3. START THE PROJECT LOGICAL DATA MODEL FROM THE ELDM ...................................................................................... -
SE SECTION B.Pdf
DEPARTMENT OF COMPUTER SCIENCE AND ENGG. SOFTWARE ENGG. SECTION-B Requirement Engineering The process to gather the software requirements from client, analyze and document them is known as requirement engineering. The goal of requirement engineering is to develop and maintain sophisticated and descriptive ‘System Requirements Specification’ document. Requirements analysis, also called requirements engineering, is the process of determining user expectations for a new or modified product. These features, called requirements, must be quantifiable, relevant and detailed. In software engineering, such requirements are often called functional specifications. Requirements engineering (RE) refers to the process of defining, documenting and maintaining requirements to the sub-fields of systems engineering and software engineering concerned with this process. The activities involved in requirements engineering vary widely, depending on the type of system being developed and the specific practices of the organization(s) involved. These may include: 1. Requirements inception or requirements elicitation - 2. Requirements identification - identifying new requirements 3. Requirements analysis and negotiation - checking requirements and resolving stakeholder conflicts 4. Requirements specification (e.g., software requirements specification; SRS) - documenting the requirements in a requirements document 5. Systems modeling - deriving models of the system, often using a notation such as the Unified Modeling Language (UML) or the Lifecycle Modeling Language -
L5 Sod System-Analysis-And-Design
[1] Module: SFDAD501-SYSTEMS ANALYSIS AND DESIGN Competence: SFDAD501-Perform systems analysis and design Sector: ICT Trade: Software Development Level: 5 LU1: Describe information systems concepts LO 1.1. Identify information systems Context of Information system: Data is unprocessed facts and figures without any added interpretation or analysis. "The price of crude oil is $80 per barrel." Information is data that has been interpreted so that it has meaning for the user. "The price of crude oil has increased from $70 to $80 per barrel" gives meaning to the data and so is said to be information to someone who tracks oil prices. Knowledge : *is a combination of information, experience and insight that may benefit the individual or the organization. *is the state of knowing about or being familiar with something. Systems categories with examples The systems can be divided into two categories namely: i. Natural systems ii. Artificial systems i. Natural Systems Natural systems are systems that have not been established by man. They exist in nature to accomplish their goals. These systems are divided into three categories: Stellar Systems: galaxies (the very large group of stars in the universe), solar system etc... Geological systems: rivers, mountains etc... Molecular systems: organization of complex atoms [2] Natural systems can be divided into two parts: - Natural physical systems: these systems are interest of human beings because they look at any time how they can change them. They manufacture systems, some using computers that can easily interact with natural systems. (Not breath) - Living systems: they include the billions of animals and plants around us and humans. -
Augmenting Sadt with Uml
J10.4 AUGMENTING SADT WITH UML A HYBRID APPROACH FOR THE DESIGN OF OPERATIONAL SCIENCE ALGORITHMS John L. Baldwin *, Alexander Werbos, and T. Scott Zaccheo Atmospheric and Environmental Research (AER), Inc. 1. INTRODUCTION Science algorithms perform calculations for modeling This paper proposes a hybrid structured analysis and physical phenomena and estimating physical properties. object oriented design approach using SADT with UML They take input and control data to generate output toward developing science algorithms and documenting data. Implemented in software, science algorithms are legacy algorithms for incorporation into operational functional in nature and generally not user interactive. systems and environments. We present an introduction As such they can be designed as modular to GOES-R and its systems and software engineering computational units which may be run independently, as for context. This is followed by an introduction to SADT part of batch processing, or as components within a along with its strengths and drawbacks, a brief user or service interactive environment. Two introduction to UML, a working example of SADT, and contemporary approaches to address the analysis and then demonstrate how UML augments SADT for a design of such systems are Structured robust algorithm development approach. Analysis/Structured Design and Object Oriented Analysis and Design. Structured Analysis and Design 2. GOES-R OVERVIEW Technique (SADT) is a specific methodology which emerged out of the variety of different structured The National Oceanic and Atmospheric Administration’s analysis and structured design approaches. SADT was Geostationary Operational Environmental Satellite designed to simplify and provide a consistent model to system is a premier national asset with regard to describe hierarchical systems.