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M1: Introduction to Data Structures in Real Systems

Prof. Justin David Pineda CISSP, CISM

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Why This Course Matters

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What Happens When You Open an App?

  • User → Application → Data Processing → Database → Results

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  • Millions of data operations happen instantly.

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Data Structures Behind Social Media

  • Friend relationships → Graph
  • Notifications → Queue
  • User lookup → Hash Table
  • News feed ranking → Priority Queue

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Learning Objectives

  • Explain the concept of data structures
  • Identify structures used in real systems
  • Distinguish linear vs non‑linear structures
  • Understand algorithms and data structures relationship
  • Analyze applications and identify structures used

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What is a Data Structure?

  • A method for organizing and storing data efficiently.

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Data Structures vs Algorithms

  • Data Structure → How data is stored
  • Algorithm → How data is processed

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Types of Data Structures

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Static vs Dynamic Structures

  • Static: Fixed memory allocation (Array)
  • Dynamic: Memory allocated during runtime (Linked List, Trees)

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Linear Data Structures

  • Elements arranged sequentially
  • Examples:
  • • Arrays
  • • Stacks
  • • Queues
  • • Linked Lists

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Non‑Linear Data Structures

  • Hierarchical or network relationships
  • Examples:
  • • Trees
  • • Graphs

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Arrays in Real Systems

Characteristics:

  • Fast indexed access
  • Fixed memory layout

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Linked Lists in Real Systems

  • Nodes connected through pointers

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Advantages:

  • Dynamic size
  • Efficient insertion

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Stacks in Real Systems

  • LIFO – Last In First Out

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Applications:

  • Function calls
  • Undo operations
  • Expression evaluation

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Queues in Real Systems

  • FIFO – First In First Out

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Applications:

  • Print jobs
  • Message queues
  • Network packet processing

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Trees in Real Systems

  • Hierarchical structure

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Applications:

  • File systems
  • Database indexing
  • Decision trees

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Graphs in Real Systems

  • Represents relationships between entities

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Applications:

  • Social networks
  • Internet routing
  • Fraud detection

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Hash Tables in Real Systems

  • Key → Value mapping

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Applications:

  • Login authentication
  • Caching
  • Database indexing

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Data Structures in Cybersecurity

  • Log ingestion pipelines → Queues
  • Network analysis → Graphs
  • Credential storage → Hash tables
  • Malware detection → Trees

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Choosing the Right Data Structure

Consider:

  • Data size
  • Operation frequency
  • Memory constraints
  • Performance needs

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Session Summary

  • Data structures organize information efficiently
  • Algorithms rely on data structures
  • Real systems depend on optimized structures
  • Choosing the right structure improves performance

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Knowledge Check

  1. What is the purpose of a data structure?
  2. Difference between linear and non‑linear structures?
  3. Which structure follows FIFO?
  4. Which structure is used for key‑value lookup?
  5. Which structure models relationships between entities?

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Exercise: Identify Data Structures in Real Systems

Choose a platform:

  • Facebook, YouTube, BPI Online, Lazada, Grab, GCash, Netflix, Gmail, Spotify, Microsoft Teams
  • Identify possible data structures used internally.

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Student Presentation – Next Session

Prepare 3–5 slides

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Discuss:

  • System overview
  • Types of data handled
  • Possible data structures used
  • Why they are appropriate
  • Performance considerations

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Presentation time: 15 minutes