IB Year 1 Higher Level Computer Science

Tuesday 1 April 2025 - Block 1

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Daily Note

Today we will start learning about abstract data structures.

If you recall, your homework was to watch a 10 minute video prior to todays class. We will start off by taking a short quiz to get our brains working. 

 

What is an Abstract Data Structure?

An abstract data structure (ADS) is a way of organizing and storing data so it can be accessed and modified efficiently. It’s abstract because we care more about what it does than how it does it.

Think of ADSs as specialized tools in a toolbox:

• Some are fast at adding/removing items.

• Others are excellent for sorting, searching, or keeping things in order.

• Each one is suited for a particular kind of problem.

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Why Do We Need Different Data Structures?

Let’s say you’re building:

• A music playlist → you may want to add/remove songs in order → queue.

• An undo button → you need to go back to the most recent change → stack.

• A family tree → you need relationships like parents and children → tree.

• A chessboard → you need a grid with rows and columns → 2D array.

Choosing the right data structure is like choosing the right vehicle for a journey:

• You could use a bicycle for a road trip… but wouldn’t a car be better?

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Real-World Analogy

Let’s say you’re organizing a classroom:

• A stack is like a pile of trays — last one added is the first one you remove.

• A queue is like students waiting in line — first in, first out.

• A 2D array is like a seating chart — you can quickly find who’s in row 3, column 2.

• A linked list is like a scavenger hunt — each clue (node) tells you where to go next.

• A tree is like a company org chart — with branches and hierarchies.

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Recursion? What’s That?

Later, we’ll also explore recursive thinking — solving a problem by solving smaller versions of the same problem. Think of Russian nesting dolls or breaking down a big problem into tiny repeatable steps.

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Where We’re Headed

Over the next few weeks, you'll learn to:

• Recognize when and why to use each structure.

• Build and manipulate arrays, stacks, queues, linked lists, collections, and trees.

• Write efficient, elegant algorithms using these structures.

• Trace and understand recursion, an essential problem-solving strategy in CS.

• Develop the ability to choose the best structure for a specific problem.

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Today’s Focus: 2D Arrays (wiki article here) 

To begin our journey, we’re going to dive into two-dimensional arrays — one of the most useful static data structures for games, simulations, and tables. By the end of today’s lesson, you’ll know how to:

• Visualize and describe a 2D array.

• Access and update elements using row/column indices.

• Structure: A 2D array is essentially an array of arrays.

  seats = [["Alice", "Bob"],
           ["Carol", "Dave"]]

• Accessing an element:

  • seats[0][1] → "Bob"

  • seats[1][0] → "Carol"

• Updating an element:

  • seats[1][1] = "Eve" changes "Dave" to "Eve"

  • Updated seats:

    [["Alice", "Bob"],
     ["Carol", "Eve"]]

• Looping through a 2D array:

  for row in range(len(seats)):
      for col in range(len(seats[row])):
          print(seats[row][col])

• Common mistakes:

  • Mixing up row and column order

  • Using out-of-bounds indices (e.g., seats[2][0] in the example above would cause an error)

• Write algorithms to iterate through them.

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Let’s open our minds, get comfortable with abstract thinking, and start organizing data in powerful new ways.

Your homework will be to work through this 2D array problem

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Reminders & routines:

Please read and follow these reminders:

1. IF this_class == first_class_of_day:
        read_daily_bulletin()
    
2. IF today == Friday:
        careers_in_computing()

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