c. Practical Examples

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Example 1 — TXT (simple settings)

Scenario: A game needs to store user preferences that are loaded each time the program runs.

File: settings.txt

theme=dark
fontSize=14
musicOn=true
username=PlayerOne
difficulty=medium
volume=75

Structure breakdown:

• Each line contains one configuration setting
• Uses key=value pattern for easy parsing
• No headers or delimiters needed
• Simple string processing to read each line

Why TXT works: Small amount of simple data, easy to read/write quickly.

Reading this in C#:

// Read all lines from TXT file
string[] lines = File.ReadAllLines("settings.txt");

// Process each line
foreach (string line in lines)
{
    // Split on '=' to get key and value
    string[] parts = line.Split('=');
    string key = parts[0];      // e.g., "theme"
    string value = parts[1];    // e.g., "dark"

    Console.WriteLine($"{key}: {value}");
}

When to use TXT

• Configuration files with simple key=value pairs
• Small amounts of unstructured data
• Single values per line
• Quick and simple to implement

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Example 2 — CSV (tabular data / 2D array)

Scenario: A school needs to store student records in a format that can be opened in Excel and processed by a program.

File: students.csv

StudentID,FirstName,LastName,Score,Grade,House
1023,Aisha,Khan,87,A,Kendall
1024,Luca,Rossi,91,A,O'Brien
1025,Emma,Smith,76,B,Mackillop
1026,Noah,Patel,82,A,Kendall
1027,Sophie,Lee,69,C,O'Brien

Structure breakdown:

• Line 1 (header row): Field names separated by commas
• Lines 2-6 (data rows): Each line = one complete record
• Each value separated by a delimiter (comma in this case)
• Can be opened directly in spreadsheet software
• Represents a 2D array (rows × columns)

Each line = a record

Each value separated by a delimiter (comma)

Reading this in C#:

// Read all lines from CSV file
string[] lines = File.ReadAllLines("students.csv");

// First line is the header (skip it when processing data)
Console.WriteLine("Header: " + lines[0]);

// Process data rows (starting from index 1)
for (int i = 1; i < lines.Length; i++)
{
    // Split each line by comma to get individual fields
    string[] fields = lines[i].Split(',');

    string studentID = fields[0];   // "1023"
    string firstName = fields[1];   // "Aisha"
    string lastName = fields[2];    // "Khan"
    string score = fields[3];       // "87"
    string grade = fields[4];       // "A"
    string house = fields[5];       // "Kendall"

    Console.WriteLine($"{firstName} {lastName} scored {score} ({grade})");
}

When to use CSV

• Tabular data with consistent fields across all records
• Need to transfer data between programs and spreadsheets
• Simple row/column structure
• Smaller file size compared to XML

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Example 3 — XML (hierarchical / nested)

Scenario: A library system needs to store book information with multiple authors and categories, supporting complex nested relationships.

File: library.xml

<?xml version="1.0" encoding="utf-8"?>
<library>
  <!-- First book in the library -->
  <book id="101">
    <title>Clean Code</title>
    <author>Robert Martin</author>
    <year>2008</year>
    <categories>
      <category>Programming</category>
      <category>Software Engineering</category>
    </categories>
    <available>true</available>
  </book>

  <!-- Second book with multiple authors -->
  <book id="102">
    <title>Design Patterns</title>
    <authors>
      <author>Erich Gamma</author>
      <author>Richard Helm</author>
      <author>Ralph Johnson</author>
      <author>John Vlissides</author>
    </authors>
    <year>1994</year>
    <categories>
      <category>Programming</category>
      <category>Design</category>
    </categories>
    <available>false</available>
  </book>

  <!-- Third book with nested publisher information -->
  <book id="103">
    <title>The Pragmatic Programmer</title>
    <author>Andrew Hunt</author>
    <publisher>
      <name>Addison-Wesley</name>
      <location>Boston</location>
    </publisher>
    <year>1999</year>
    <categories>
      <category>Programming</category>
    </categories>
    <available>true</available>
  </book>
</library>

Structure breakdown:

• Prolog (line 1): <?xml version="1.0" encoding="utf-8"?> declares this is an XML file
• Root element: <library> wraps all data
• Parent elements: Each <book> contains child elements
• Child elements: <title>, <author>, <year>, etc.
• Nested structures: <categories> contains multiple <category> tags
• Self-describing: Tags make it obvious what each value represents
• Attributes: id="101" provides additional metadata

Tags make it obvious what each value represents

Nested structure supports more complex data

Why XML is better here than CSV:

• Books can have different numbers of authors (1 author vs 4 authors)
• Books can have multiple categories
• Nested publisher information can't be represented well in flat CSV
• Structure can evolve (add new fields without breaking existing data)

Reading this in C# using XDocument:

using System.Xml.Linq;

// Load the XML file
XDocument doc = XDocument.Load("library.xml");

// Get all book elements
var books = doc.Descendants("book");

// Process each book
foreach (var book in books)
{
    // Extract data using tag names
    string id = book.Attribute("id").Value;
    string title = book.Element("title").Value;
    string year = book.Element("year").Value;
    string available = book.Element("available").Value;

    Console.WriteLine($"Book {id}: {title} ({year})");

    // Handle multiple authors (if present)
    var authors = book.Descendants("author");
    foreach (var author in authors)
    {
        Console.WriteLine($"  Author: {author.Value}");
    }

    // Handle multiple categories
    var categories = book.Descendants("category");
    foreach (var category in categories)
    {
        Console.WriteLine($"  Category: {category.Value}");
    }

    Console.WriteLine($"  Available: {available}\n");
}

When to use XML

• Hierarchical/nested data structures
• Variable number of child elements (e.g., multiple authors)
• Self-describing data (tags explain meaning)
• Need flexibility for structural changes
• Data with parent-child relationships

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Comparison Summary

Feature	TXT	CSV	XML
Structure	Unstructured or simple patterns	Rows and columns with delimiter	Hierarchical with tags
Best for	Simple settings/config	Tabular data	Complex nested data
File size	Smallest	Small	Largest
Human readable	Very easy	Easy	Easy but verbose
Flexibility	Limited	Limited	Very flexible
Example use	Game settings	Student grades	Family trees, product catalogs

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Example 4 — Comparing file types for the same data

Scenario: Store information about 3 employees.

TXT version (employees.txt)

John Smith
Developer
50000
Sarah Jones
Manager
75000
Mike Chen
Designer
55000

Problem: No clear structure - which line is name/role/salary? Hard to parse reliably.

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CSV version (employees.csv)

Name,Role,Salary
John Smith,Developer,50000
Sarah Jones,Manager,75000
Mike Chen,Designer,55000

Better: Clear columns, easy to process as a table, works well in spreadsheets.

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XML version (employees.xml)

<?xml version="1.0" encoding="utf-8"?>
<company>
  <employee id="101">
    <name>John Smith</name>
    <role>Developer</role>
    <salary currency="AUD">50000</salary>
  </employee>
  <employee id="102">
    <name>Sarah Jones</name>
    <role>Manager</role>
    <salary currency="AUD">75000</salary>
  </employee>
  <employee id="103">
    <name>Mike Chen</name>
    <role>Designer</role>
    <salary currency="AUD">55000</salary>
  </employee>
</company>

Most flexible: Self-describing tags, can add attributes (id, currency), can easily extend with nested elements (e.g., contact details, skills).

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Exam Tip

When comparing file types in an exam:

1. Describe the structure of each format
2. Explain why one is better for the specific scenario
3. Use phrases like:
   • "CSV uses delimiters to separate fields in a tabular structure"
   • "XML uses tags that describe what each field contains"
   • "XML is better here because the data is hierarchical/nested"
   • "CSV is better here because the data is tabular with consistent fields"