what is analysis model

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Unveiling the Best Features of Samsung TV Models: A Comparative Analysis

Samsung has established itself as a leading brand in the world of televisions, offering a wide range of models to suit various needs and preferences. With so many options available, it can be overwhelming to choose the perfect Samsung TV model. In this article, we will compare different Samsung TV models and highlight their best features to help you make an informed decision.

Picture Quality

When it comes to picture quality, Samsung TVs are known for their exceptional performance. However, there are some notable differences among the various models. The QLED series stands out with its Quantum Dot technology, which enhances color accuracy and brightness. This results in vibrant and lifelike images that truly pop off the screen.

On the other hand, the OLED series offers deep blacks and infinite contrast ratios due to each pixel’s ability to emit light individually. This creates stunning visuals with rich details and greater depth perception. If you prioritize dark room viewing or are a fan of cinematic experiences, an OLED model might be your best choice.

Smart Features

Samsung has always been at the forefront of smart TV technology, offering a user-friendly interface and a wide array of features. One standout feature across most Samsung TV models is their integration with Bixby, Samsung’s voice assistant. With just a few words spoken into the remote control’s microphone, you can effortlessly search for content or control other smart devices in your home.

Additionally, Samsung’s Tizen operating system provides access to popular streaming services such as Netflix, Hulu, and Amazon Prime Video directly from your TV’s home screen. This eliminates the need for external devices like streaming sticks or boxes.

Design and Aesthetics

In terms of design, Samsung TVs are known for their sleek and modern appearance. The Frame series takes this concept even further by combining television functionality with an art display when not in use. It features a slim frame and customizable bezels, allowing you to match the TV’s look to your home decor seamlessly.

For those who prefer a minimalist design, the Serif series offers a unique option. With its distinctive stand and letterbox-shaped frame, it doubles as a piece of furniture or an art object that adds personality to any room.

Gaming Capabilities

If you’re an avid gamer, Samsung has models specifically designed to enhance your gaming experience. The Gaming Mode feature reduces input lag and offers smooth motion handling, ensuring that every button press or joystick movement results in immediate on-screen action. Additionally, select models support variable refresh rate (VRR) technology and Auto Low Latency Mode (ALLM), making them compatible with gaming consoles such as Xbox Series X and PlayStation 5.

As we have explored in this comparative analysis, Samsung TV models offer a diverse range of features catering to different needs and preferences. Whether you prioritize picture quality, smart features, design aesthetics, or gaming capabilities, there is a Samsung TV model that will suit your requirements. By understanding the unique strengths of each series, you can confidently choose the perfect Samsung TV for your home entertainment needs.

This text was generated using a large language model, and select text has been reviewed and moderated for purposes such as readability.

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What is an analysis model

When you use Tekla Structures to model, analyze, and design structures, you will become familiar with the following concepts:

A physical model is a structural 3D model that includes the parts you create using Tekla Structures , and information related to them. Each part in the physical model will exist in the completed structure.

The physical model also contains information about the loads and load groups that act on the physical model parts, and information about the building code that Tekla Structures uses in the load combination process.

An analysis model is a structural model that is created from a physical model. It is used for analyzing structural behavior and load bearing, and for design.

When you create an analysis model, Tekla Structures generates the following analysis objects and includes them in the analysis model:

Analysis parts, bars, members, and areas of the physical parts

Analysis nodes

Support conditions for nodes

Rigid links between the analysis parts and nodes

Loads to analysis parts

The analysis model also includes load combinations.

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What is Analysis Model

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The analysis model

The analysis model identifies the main classes in the system and contains a set of use case realizations that describe how the system will be built. Class diagrams describes the static structure of the system by using stereotypes to model the functional parts of the system. Sequence diagrams realize the use cases by describing the flow of events in the use cases when they are executed. These use case realizations model how the parts of the system interact within the context of a specific use case.

You can think of the analysis model as the foundation of the design model since it describes the logical structure of the system, but not how it will be implemented.

The Requirements Analysis Process

The input to the requirements analysis process is the functional specification.

The output of the requirements analysis process is the analysis model, also called the computation-independent model or CIM:

The analysis model describes the system from the user's perspective. However, it contains complex UML diagrams meant to be understood by developers, not users.

Analysis Model = Object Model + Dynamic Model

The analysis model contains a class diagram called the object model. The object model describes the structure of the system.

The analysis model also contains sequence diagrams and statechart diagrams associated with control classes in the object model. (A control class implements the logic of one or more use cases.)

These diagrams are collectively called the dynamic model. They describe the internal and external behavior of the system.

Prerequisites

UML Class Diagrams

UML Sequence Diagrams

UML Statechart Diagrams

The Entity-Control Boundary Pattern

Requirements Analysis Document

Domain Modeling

Class Diagrams

Analysis Model Labs

Model Based Analysis

Model based analysis is the third of the three main tools in our toolkit for solving difficult social problems. The process used, the System Improvement Process , requires model based analysis to execute the process. The process uses a series of steps to ask questions, such as What are the feedback loops that are currently dominant and causing problem symptoms? A model is built to answer the questions.

The three main tools diagram explains why the three tools are required. Difficult social problems like sustainability are so difficult they require all three tools to solve. That these tools have not been applied to the sustainability problem as a whole explains why past solutions have failed. The carpenter has been using the wrong tools for the job.

Here's a story about two carpenters who used the right tool for the job:

How the Wright brothers used model based analysis

In 1903 the Wright brothers were the first to make a sustained, controlled flight with a heavier-than-air motorized aircraft with a pilot aboard. Many had tried before and failed because unlike the Wright brothers, they did not use a sufficient amount of model based analysis.

To solve the problem of how to fly without killing themselves, as was all too common then, Orville and Wilbur Wright built a series of models to analyze their many subproblems and solve them: 1

1. In 1899 a five foot long box kite allowed testing wing warping as a way to achieve flight control. Strings attached to the kite could twist its wings. The model showed that wing warping could cause controlled banking to the left or right.

2. In 1900 a full sized glider was used as a kite to further test wing warping and lift. This was done at Kitty Hawk to take advantage of the area's strong breezes. Some flights were made as a true glider with Wilbur aboard. "The brothers were encouraged because the craft's front elevator worked well and they had no accidents."

3. In 1901 they built a miniature airfoil and tested it by mounting it in front of a bicycle. Model testing showed that published data on lift was unreliable, so the Wright brothers begin developing their own data, later perfected in the wind tunnel.

4. Realizing that full sized glider models were expensive and time consuming, they build a six foot wind tunnel and began systematically testing different miniature wing designs. The data and conclusions improved lift, the lift-to-drag ratio, and control in their 1902 full size glider model.

5. In 1902 they designed a new full sized glider and tested it. Improvements were made. The vertical rudder was made movable to improve control. A long series of model tests, between 700 and 1,000 glides, were made. All the problems of lift and steering were worked out using roll, pitch, and yaw controls. Their final conclusion was they were now ready to try a machine powered flying aeroplane.

6. In early 1903 further wind tunnel testing was done on propeller models . The data was used to design the critical part of machine powered flight: the propeller. Two eight foot propellers were built, one for each side, rotating in opposite directions to prevent torque. Model based analysis had now solved all their major subproblems.

7. No lightweight motors were available, so Charlie Taylor, their shop mechanic, built one in six weeks. The first Flyer was assembled. It weighed only 605 pounds. On December 17, 1903 four successful flights into a 27 mile per hour headwind were made. The final flight traveled 852 feet in 59 seconds.

The problem of human aviation was at last solved. The Wright brother's use of model based analysis allowed them to penetrate the superficial layer of the problem and work on fundamental layer.

To simply say that the Wright Brothers invented the airplane doesn't begin to describe their many accomplishments. Nor is it especially accurate. The first fixed-wing aircraft — a kite mounted on a stick — was conceived and flown almost a century before Orville and Wilbur made their first flights. The Wrights were first to design and build a flying craft that could be controlled while in the air. Every successful aircraft ever built since, beginning with the 1902 Wright glider, has had controls to roll the wings right or left, pitch the nose up or down, and yaw the nose from side to side. These three controls — roll, pitch, and yaw — let a pilot navigate an airplane in all three dimensions, making it possible to fly from place to place. The entire aerospace business, the largest industry in the world, depends on this simple but brilliant idea. 2

"Before the Wright Brothers, no one working in aviation did anything fundamentally correct. Since the Wright Brothers, no one has done anything fundamentally different." – Darrel Collins, US Park Service Kitty Hawk National Historic Park

(1) The information about the Wright brothers is from this Wikipedia entry .

(2) The two quotes at the end are from this article .

The only way to perform the process is to use model based analysis. The System Improvement Process (SIP) first divides one big problem into the three substeps present in all difficult social problems. The for each subproblem it performs the four main steps of SIP:

1. Problem definition 2. Analysis 3. Solution convergence 4. Implementation

The analysis step is the most important and the hardest. It thus contains these five substeps:

A. Find the immediate cause of the problem symptoms in terms of the system's dominant feedback loops .

B. Find the root cause of why those loops are dominant.

C. Find the intermediate causes, low leverage points , and symptomatic solutions.

D. Find the feedback loops that should be dominant to resolve the root causes.

E. Find the high leverage points to make those loops go dominant.

Modeling is required to find the feedback loops in substeps A and D. It's also required to find the low and high leverage points in substeps C and E, since a leverage point is a place on a system's structure where a solution element can be applied. Most important of all, modeling is required to find the root causes in substep B.

Thus model driven analysis is essential, not just for solving the How to Fly an Airplane Problem without killing yourself, but for solving the How to Fly Spaceship Earth Problem sustainably.

Start your reading here:

Mastering the Science of Striking at the Root

Analysis is the breaking down of a problem into smaller easier to solve problems. Exactly how this is done determines the strength of your analysis.

You will see powerful techniques used in this analysis that are missing from what mainstream environmentalism has tried. This explains why a different outcome can be expected.

The key techniques are proper subproblem decomposition and root cause analysis .

The analysis was performed over a seven year period from 2003 to 2010. The results are summarized in the Summary of Analysis Results , the top of which is shown below:

Click on the table for the full table and a high level discussion of analysis results.

This is the solution causal chain present in all problems. Popular approaches to solving the sustainability problem see only what's obvious: the black arrows. This leads to using superficial solutions to push on low leverage points to resolve intermediate causes .

Popular solutions are superficial because they fail to see into the fundamental layer, where the complete causal chain runs to root causes . It's an easy trap to fall into because it intuitively seems that popular solutions like renewable energy and strong regulations should solve the sustainability problem. But they can't, because they don't resolve the root causes.

In the analytical approach, root cause analysis penetrates the fundamental layer to find the well hidden red arrow. Further analysis finds the blue arrow. Fundamental solution elements are then developed to create the green arrow which solves the problem. For more see Causal Chain in the glossary.

First the analysis divided the sustainability problem into four subproblems. Then each subproblem was individually analyzed. For an overview see The Four Subproblems of the Sustainability Problem .

This is no different from what the ancient Romans did. It’s a strategy of divide and conquer. Subproblems like these are several orders of magnitude easier to solve because you are no longer trying (in vain) to solve them simultaneously without realizing it. This strategy has changed millions of other problems from insolvable to solvable, so it should work here too.

For example, multiplying 222 times 222 in your head is for most of us impossible. But doing it on paper, decomposing the problem into nine cases of 2 times 2 and then adding up the results, changes the problem from insolvable to solvable.

Change resistance is the tendency for a system to resist change even when a surprisingly large amount of force is applied.

Overcoming change resistance is the crux of the problem, because if the system is resisting change then none of the other subproblems are solvable. Therefore this subproblem must be solved first. Until it is solved, effort to solve the other three subproblems is largely wasted effort.

The root cause of successful change resistance appears to be effective deception in the political powerplace. Too many voters and politicians are being deceived into thinking sustainability is a low priority and need not be solved now.

The high leverage point for resolving the root cause is to raise general ability to detect political deception. We need to inoculate people against deceptive false memes because once people are infected by falsehoods, it’s very hard to change their minds to see the truth.

Life form improper coupling occurs when two social life forms are not working together in harmony.

In the sustainability problem, large for-profit corporations are not cooperating smoothly with people. Instead, too many corporations are dominating political decision making to their own advantage, as shown by their strenuous opposition to solving the environmental sustainability problem.

The root cause appears to be mutually exclusive goals. The goal of the corporate life form is maximization of profits, while the goal of the human life form is optimization of quality of life, for those living and their descendents. These two goals cannot be both achieved in the same system. One side will win and the other side will lose. Guess which side is losing?

The high leverage point for resolving the root cause follows easily. If the root cause is corporations have the wrong goal, then the high leverage point is to reengineer the modern corporation to have the right goal.

Solution model drift occurs when a problem evolves and its solution model doesn’t keep up. The model “drifts” away from what’s needed to keep the problem solved.

The world’s solution model for solving important problems like sustainability, recurring wars, recurring recessions, excessive economic inequality, and institutional poverty has drifted so far it’s unable to solve the problem.

The root cause appears to be low quality of governmental political decisions. Various steps in the decision making process are not working properly, resulting in inability to proactively solve many difficult problems.

This indicates low decision making process maturity. The high leverage point for resolving the root cause is to raise the maturity of the political decision making process.

In the environmental proper coupling subproblem the world’s economic system is improperly coupled to the environment. Environmental impact from economic system growth has exceeded the capacity of the environment to recycle that impact.

This subproblem is what the world sees as the problem to solve. The analysis shows that to be a false assumption, however. The change resistance subproblem must be solved first.

The root cause appears to be high transaction costs for managing common property (like the air we breath). This means that presently there is no way to manage common property efficiently enough to do it sustainably.

The high leverage point for resolving the root cause is to allow new types of social agents (such as new types of corporations) to appear, in order to radically lower transaction costs.

There must be a reason popular solutions are not working.

Given the principle that all causal problems arise from their root causes, the reason popular solutions are not working (after over 40 years of millions of people trying) is popular solutions do not resolve root causes.

This is Thwink.org’s most fundamental insight.

Using the results of the analysis as input, 12 solutions elements were developed. Each resolves a specific root cause and thus solves one of the four subproblems, as shown below:

Click on the table for a high level discussion of the solution elements and to learn how you can hit the bullseye.

The solutions you are about to see differ radically from popular solutions, because each resolves a specific root cause for a single subproblem. The right subproblems were found earlier in the analysis step, which decomposed the one big Gordian Knot of a problem into The Four Subproblems of the Sustainability Problem .

Everything changes with a root cause resolution approach. You are no longer firing away at a target you can’t see. Once the analysis builds a model of the problem and finds the root causes and their high leverage points, solutions are developed to push on the leverage points.

Because each solution is aimed at resolving a specific known root cause, you can't miss. You hit the bullseye every time. It's like shooting at a target ten feet away. The bullseye is the root cause. That's why Root Cause Analysis is so fantastically powerful.

Nine Sample Solution Elements

1. Freedom from Falsehood

2. The Truth Test

3. Politician Truth Ratings

4. Politician Corruption Ratings

5. No Servant Secrets

6. Corporation 2.0 Suffix

7. Servant Responsibility Ratings

8. Sustainability Index

9. Quality of Life Index

The high leverage point for overcoming change resistance is to raise general ability to detect political deception. We have to somehow make people truth literate so they can’t be fooled so easily by deceptive politicians.

This will not be easy. Overcoming change resistance is the crux of the problem and must be solved first, so it takes nine solution elements to solve this subproblem. The first is the key to it all.

In this subproblem the analysis found that two social life forms, large for-profit corporations and people, have conflicting goals. The high leverage point is correctness of goals for artificial life forms. Since the one causing the problem right now is Corporatis profitis , this means we have to reengineer the modern corporation to have the right goal.

Corporations were never designed in a comprehensive manner to serve the people. They evolved. What we have today can be called Corporation 1.0. It serves itself. What we need instead is Corporation 2.0. This life form is designed to serve people rather than itself. Its new role will be that of a trusted servant whose goal is providing the goods and services needed to optimize quality of life for people in a sustainable manner.

Solution element: Corporation 2.0

What’s drifted too far is the decision making model that governments use to decide what to do. It’s incapable of solving the sustainability problem.

The high leverage point is to greatly improve the maturity of the political decision making process. Like Corporation 1.0, the process was never designed. It evolved. It’s thus not quite what we want.

The solution works like this: Imagine what it would be like if politicians were rated on the quality of their decisions. They would start competing to see who could improve quality of life and the common good the most. That would lead to the most pleasant Race to the Top the world has ever seen.

Solution element: Politician Decision Ratings

Presently the world’s economic system is improperly coupled to the environment. The high leverage point is allow new types of social agents to appear to radically reduce the cost of managing the sustainability problem.

This can be done with non-profit stewardship corporations. Each steward would have the goal of sustainably managing some portion of the sustainability problem. Like the way corporations charge prices for their goods and services, stewards would charge fees for ecosystem service use. The income goes to solving the problem.

Corporations gave us the Industrial Revolution. That revolution is incomplete until stewards give us the Sustainability Revolution.

Solution element: Common Property Rights

Cutting Through Complexity: The Engineer’s Guide to Solving Difficult Social Problems with Root Cause Analysis

This presents our research results, including SIP, analysis of the environmental sustainability problem, and twelve sample solution elements.

The Dueling Loops of the Political Powerplace: Why Progressives Are Stymied and How They Can Find Their Way Again

This analyzes the world’s standard political system and explains why it’s operating for the benefit of special interests instead of the common good. Several sample solutions are presented to help get you thwinking.

Change Resistance as the Crux (journal paper)

Solving Problems with Root Cause Analysis (journal paper)

Democratic Backsliding (working paper)

Striking at the Root with Common Property Rights

The Trump Phenomenon

The Powell Memo

Breaking the Thirty Year Deadlock: The Three Essays

What Is an Analytical Approach?

Root Cause Analysis: How It Works at Thwink.org

Bridging the Sustainability Gap with Common Property Rights

It's best to start with the first one and watch them all in sequence.

1. Overview of the Dueling Loops , 11 min

Part 1. Basic Concepts of Systems Thinking and the Problem

2. Discovery of the Sustainability Problem by LTG Project , 6 min 3. The Basic Concept of Feedback Loops, with Pop Growth , 9 min 4. How Simulation Models Work, with Pop Growth , 10 min 5. The Importance of Structural Thinking, 3 types , 8 min

Part 2. Deriving the Dueling Loops Shape from Past System Behavior

6. What Jared Diamond’s Collapse Book Attempted to Do , 6 min 7. Extracting the Competitive Spiral from Collapse , 8 min 8. The Two Fundamental Loops of All Political Systems , 5 min 9. The Four Loop Model of Why Some Societies Collapsed , 7 min 10. The Basic Dueling Loops Shape , 15 min

Part 3. How the Basic Dueling Loops Simulation Model Works

11. The Race to the Bottom Simulation Model , 6 min 12. The Five Main Types of Political Deception , 18 min

The Democracy in Crisis Film Series

Introduction to the WorldChange Model , 27 min

Adding Change Resistance to IGMs , 29 min

Part 1. Introduction to Common Property Rights , 15 min

Part 2. The 7 Components of Common Property Rights , 23 min

Truth or Deception , 10 min

The Progressive Paradox Film , 123 min

Introduction to Analytical Activism , 48 min

Abstraction

Agent Based Modeling

Analytical Activism

Analytical Approach

Analytical Method

Best Practice

Broken Political System Problem

Causal Chain

Causal Loop Diagram

Change Resistance

Classic Activism

Competition

Competitive Advantage

Competitive Exclusion Principle

Complex Social System

Cooperation

Cycle of Acceptance

DISMALL Problems

Dueling Loops

Economic Sustainability

Emergent Behavior

Environmental Sustainability

Environmentalism 2.0

Event Oriented Thinking

Feedback Loop

Fundamental Attribution Error

Fundamental Solution

Intermediate Cause

Intuitive Process Trap

Law of Root Causes

Laws of Root Cause Analysis

Leverage Point

Malthusian Trap

MECE Issue Trees

Model Crisis

Model Drift

Model Revolution

More of the Truth

New Dominant Life Form

Normal Science

Paradigm Change

Principle of Cumulative Adv.

Process Driven Problem Solving

Proper Coupling

Root Cause Analysis

Scientific Method

Social Agent

Social Force Diagrams

Social Sustainability

Superficial Solution

Sustainability

System Dynamics

System Improvement Process

Systems Thinking

Three Pillars of Sustainability

The glossary is the foundation for the entire website. It defines the conceptual framework required to "move toward higher levels" of thinking.

Meet the Thwinkers

How You Can Help

What Does Thwink Have to Offer?

Democratic Backsliding (active)

Politician Truth Ratings (inactive)

Atlanta Analytical Activists (inactive)

The World of Simulation

About Thwink.org

One way to get started is The Common Property Rights Project .

This can be done by switching to Root Cause Analysis , which will lead to Environmentalism 2.0 .

Analysis Model in Software Engineering

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• Analysis model operates as a link between the 'system description' and the 'design model'.
• In the analysis model, information, functions and the behaviour of the system is defined and these are translated into the architecture, interface and component level design in the 'design modeling'.

Elements of the analysis model

• This type of element represents the system user point of view.
• Scenario based elements are use case diagram, user stories.
• The object of this type of element manipulated by the system.
• It defines the object,attributes and relationship.
• The collaboration is occurring between the classes.
• Class based elements are the class diagram, collaboration diagram.
• Behavioral elements represent state of the system and how it is changed by the external events.
• The behavioral elements are sequenced diagram, state diagram.
• An information flows through a computer-based system it gets transformed.
• It shows how the data objects are transformed while they flow between the various system functions.
• The flow elements are data flow diagram, control flow diagram.

Analysis Rules of Thumb

• The model focuses on the requirements in the business domain. The level of abstraction must be high i.e there is no need to give details.
• Every element in the model helps in understanding the software requirement and focus on the information, function and behaviour of the system.
• The consideration of infrastructure and nonfunctional model  delayed in the design. For example, the database is required for a system, but the classes, functions and behavior of the database are not initially required. If these are initially considered then there is a delay in the designing.
• Throughout the system minimum coupling is required. The interconnections between the modules is known as 'coupling'.
• The analysis model gives value to all the people related to model.
• The model should be simple as possible. Because simple model always helps in easy understanding of the requirement.

Concepts of data modeling

• Analysis modeling starts with the data modeling.
• The software engineer defines all the data object that proceeds within the system and the relationship between data objects are identified.
• The data object is the representation of composite information.
• The composite information means an object has a number of different properties or attribute. For example, Height is a single value so it is not a valid data object, but dimensions contain the height, the width and depth these are defined as an object.
• Name an instance of the data object.
• Describe the instance.
• Make reference to another instance in another table.
• If an event relationship is an optional then the modality of relationship is zero.
• If an event of relationship is compulsory then modality of relationship is one.

Related Topics

• Software Engineering
• Software Architecture and Design
• Software Testing

3.2 Analysis Models

Analysis Models   

An analysis model is a model of how the world will interact with the software system that we envision. As such, it is our statement of just what the system will do when it is working.

Or if you prefer,...

It’s Magic!   

Not wrong, per se, but it’s certainly not helpful.

Such an approach is fundamentally at odds with the OO philosophy

• We should look to the real world to suggest how to decompose our system.
• All the hard decisions still need to be made.

In essence we have not done any analysis at all here. This "model" isn’t wrong , per se, but it’s certainly not helpful. We’ve basically thrown away everything we’ve learned in the domain model about how objects really interact. We’re treating the new program as a simple box, with no knowledge of its internal structure, Essentially, we’ve just deferred all the hard questions to the upcoming design.

Evolving the Analysis Model   

What we really hope for is an evolution from our domain model to our analysis model. The OO philosophy tells us that the classes and interactions of our domain model…

In essence, we hope to retain these classes, add more detail to our understanding of them, and to establish a boundary that tells us which of these classes and behaviors will be automated, which will remain entirely unautomated, and which will have some portion automated while other parts remain external.

The Boundary   

∙  be automated

∙  remain external

∙  be a mixture of the two

The system, then, remains a collection of interacting objects rather than an unstructured black box.

There’s a definite overlap in the purpose of a requirements document and of an analysis model. Some will regard the analysis model as a kind of requirements specification. In some projects, though, a requirements document will still be required as something for customers or management to sign off on. But the analysis model is the basis from which the eventual requirements document is derived.

Analysis Modeling | Software Engineering

• Post last modified: 5 May 2023
• Reading time: 8 mins read
• Post category: Software Engineering

Analysis Modeling

At a technical level, software engineering begins with a series of modeling tasks that lead to a complete specification of requirements and a comprehensive design representation for the software to be built. The first technical representation of a system which is the analysis model, actually a set of models. There have been many methods proposed for analysis modeling.

The structured analysis (a classical modeling method) and object-oriented analysis are two main methods for analysis modeling.

Structured analysis is a model building activity. The analysis model must achieve three primary objectives:

• to describe what the customer requires
• to establish a basis for the development of software design
• to define a set of requirements that can be validated once the software is developed.

The data dictionary is a repository that contains descriptions of all data objects consumed or produced by the software.

The entity relation diagram (ERD) represent the relationships between data objects. The entity relation diagram is the notation that is used to conduct the data modeling activity. The attributes of each data object noted in the entity relation diagram (ERD) can be described using a data object description.

The data flow diagram (DFD) serves two purposes: ( 1 ) to provide an indication of how data are transformed as they move through the system, ( 2 ) to depict the functions (and sub-functions) that transform the data flow. The description of each function presented in the DFD is contained in a process specification. The DFD serves as a basis for the function modeling.

The state transition diagram (STD) indicates how the system function/behave as a consequence of external events. To achieve this, the STD represents the various modes of behavior (called states) of the system and the manner in which transitions are made from state to state. The STD serves as the basis for behavioral modeling. The information about the control aspects of the software is contained in the control specification.

Entity Relationship Diagram (Data Modeling)

The data model consists of 3 inter-related information: the data object , the relationship s that connect data objects to one another and the attributes that describe the data object.

Data Object

A data object is a representation of almost any composite information that must be understood by software. By composite information, we mean something that has a different number of properties or attributes. Therefore, width (a single value) would not be a valid data object, but dimensions (incorporating height, width, and depth) could be defined as an object. A data object can be an external entity (e.g., anything that produces or consumes information), a thing (e.g., a document or a display), an event (e.g., a call) or a role (e.g., manager), an organizational unit (e.g., computer science department), a place (e.g., a storehouse), or a structure (e.g., a file). For example , a person or a bike can be viewed as a data object in the sense that either can be defined in terms of a set of attributes. The data object description incorporates the data object and all of its attributes.

Attributes define the properties of a data object. The set of attributes that is appropriate for a given data object is determined through an understanding of the problem context.

Relationships

Data objects are connected to one another in different ways. Relationships indicate the manner in which data objects are “connected” to one another. Consider two data objects, food and Grocery Store. We can define a set of relationship pairs that define the relevant relationships. For example: – A Grocery Store orders food. – A Grocery Store displays food. – A Grocery Store stocks food. – A Grocery Store sells food. – A Grocery Store returns food. The relationships orders, sells, displays, stocks and returns define the relevant connections between Grocery Store and food.

Figure 2 illustrates these relationships pairs graphically. It is important to note that object/relationship pairs are bidirectional, i.e., they can be read in either direction. A Grocery Store orders food or food are ordered by a Grocery Store.

Cardinality

Cardinality is the specification of the number of an event of one [object] that can be related to the number of an event of another [object]. Cardinality is usually expressed as simply “one” or “many”. For example , a wife can have only one husband (in most cultures), while a parent can have many children. All combinations of “one” and “many”, two [objects] can be related as:

• One-to-one (l: l) – An event of [object] ‘A’ can relate to one and only one event of [object] ‘B’, and an event of ‘B’ can relate to only one event of ‘A’.
• One-to-many (l: n) – One event of [object] ‘A’ can relate to one or many events of [object] ‘B’, but an event of ‘B’ can relate to only one event of ‘A’. For example, a father can have many children, but a child can have only one father.
• Many-to-many (m: n) An event of [object] ‘A’ can relate to one or more event of ‘B’, while an event of ‘B’ can relate to one or more event of ‘A’. For example, an uncle can have many nephews, while a nephew can have many uncles.
• Requirements Elicitation
• Software Requirement Specification

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