System Analysis Study Guide

Course Learning Outcome

Chapter 3: System Analysis

3.1 Conduct Preliminary Analysis

3.2 Understand Data and Process Modelling

• Overview of Data and Process Modelling Concepts and Tools:

  • Data Flow Diagrams (DFDs)

  • Data Dictionary

  • Process Descriptions

• Symbols Used in Data Flow Diagrams:

  • Understand the meanings and uses of various symbols

• Drawing Data Flow Diagrams:

  • Draw in a sequence from general to specific

• Leveling and Balancing DFDs:

  • Ensure consistency

• Purpose of Data Dictionary:

  • Usage and contents

  • Relationship between logical and physical models

Data and Process Modelling

• Purpose of Data and Process Modelling:

  • Techniques are used to develop a logical model of the proposed system and document requirements.

  • Logical Model: Shows what the system must do.

  • Physical Model: Describes how the system will execute its functions.

Data Flow Diagrams (DFD)

• Definition: DFDs illustrate how an information system transforms input data into useful information.

  • Key Characteristics:

  • Displays data movement through the information system.

  • Does not indicate program logic or processing steps.

  • Focuses on what the system does not how it does it.

• Basic Symbols in DFDs:

  • Processes: Represented by rectangles with rounded corners showing input data and output data.

  • Data Flows: Illustrated by lines with arrowheads indicating the movement of data.

  • Data Stores: Shown as flat rectangles to indicate where the system stores data for future use.

  • External Entities: Rectangles representing outside sources or destinations of data.

• Symbol Sets:

  • Gane and Sarson Symbol Set

  • Yourdon Symbol Set

• Symbols are denoted in all capital letters for clarity.

DFD Symbols

1. Process

• Functionality: Receives input data and produces output with differing content or form.

  • Contains business logic or rules.

  • Symbol: Rectangle with rounded corners; names inside contain a verb and noun.

2. Data Flow

• Description: Path for data movement between different parts of the system.

  • Symbol: Line with an arrowhead; names consist of nouns and adjectives, as needed.

• Special Cases:

  • Spontaneous Generation: A process that generates output without an input (shown as a special case in DFD).

  • Black Hole: A process with no output.

  • Gray Hole: Insufficient input to produce an output.

3. Data Store

• Definition: Represents data stored within the system for later use by processes.

  • Importance of logical over physical characteristics.

  • Symbol: A flat rectangle with an open right side indicating stored data.

  • Naming convention: Plural nouns with adjectives, if necessary.

4. Entity

• Definition: External factors (people, places, things, events) for which data is collected.

  • Symbol: Rectangle that is sometimes shaded for clarity.

  • Differentiate between sources (suppliers of data) and sinks (receivers of data).

Guidelines for Drawing DFDs

• Best Practices:

  • Keep context diagrams on one page.

  • Use the system’s name as the process name in a context diagram.

  • Ensure unique names within sets of symbols (e.g., STUDENT).

  • Avoid crossing lines; limit symbols per DFD to maintain clarity.

  • Obtain user feedback to ensure accurate and understandable models.

Creating DFDs

Step 1: Draw a Context Diagram

• Top-level overview showing system boundaries and scope.

• Important Note: Do not show data stores in context diagrams as they are internal to the system.

Step 2: Draw a Diagram 0 DFD

• Zooms in on major processes, data flows, and data stores.

• Retains connections from the context diagram.

Step 3: Draw Lower-Level Diagrams

• Requires leveling and balancing techniques.

• Leveling: Series of increasingly detailed diagrams until all functional primitives are identified.

• Balancing: Ensures input/output data flows align across DFDs.

Data Dictionary

• Definition: A central repository of information about the system’s data components.

• Purpose: Collect, document, and organize facts about data flows, stores, entities, and processes.

• Elements Documented in Data Dictionary: Data Elements, Data Flows, Data Stores, Processes, Entities, Records, Reports.

Process Description Tools

• Documents details of functional primitives (specific processing step sets).

• Common tools include Structured English, Decision Tables, and Decision Trees.

Modular Design

• Based on three logical structures for processes:

  • Sequence: Completion of steps in a specific order.

  • Selection: Process completion based on condition outcomes.

  • Iteration (Looping): Repetition of steps until a condition changes.

Structured English

• A logical subset that describes processes clearly.

• Must include rules of sequence, selection, and iteration. Indentation for readability is essential.

Decision Table

• A logical structure featuring all combinations of conditions and resulting actions.

• Best used for complex conditions with various combinations of possibilities.

• Classifications of Conditions:

  • One Condition: Two possibilities (Yes/No).

  • Two Conditions: Every possibility must be listed clearly.

  • Additional conditions exponentially increase combinations.

Decision Tree

• Graphical representation of logical structures akin to a tree.

• Decisions and outcomes displayed left to right.

• Choice between tables and trees based on preference.

Logical vs. Physical Models

• Logical Models: Designed using structured analysis tools for new systems.

• Physical Models: Show how system requirements are practically implemented.

Summary of Data and Process Modelling

• Concepts and tools related to data and process modelling including:

  • Data flow diagrams

  • Data dictionaries

  • Process descriptions

• Emphasis on learning the symbols used in DFDs, drawing techniques, leveling and balancing DFDs, and understanding the contents of a data dictionary; along with the relationship between logical and physical models.