Chapter B2 · 12 available objectives

Programming

Data structures, algorithms, recursion, and file processing.

B2.1.1

Construct and trace programs using a range of global and local variables

Construct and trace programs using a range of global and local variables

1 min
B2.1.2

Construct programs that can extract or manipulate strings

Find the index when the substring first appears print(message.find("e")) 1 print(message.find("Hel")) 0

1 min
B2.1.3

Describe how programs use common exception handling techniques

Exception handling prevents programs from crashing when errors occur by catching them and responding gracefully.

2 min
B2.2.1

Compare static and dynamic data structures

Have a fixed size determined at compile time — size cannot change during execution.

1 min
B2.2.2

Construct programs that apply arrays and lists

A 1D list is a sequence of elements stored in a single row.

2 min
B2.2.3

Explain the concept of a stack as a "last in, first out" (LIFO) data structure

A stack is a linear data structure where elements are added and removed from the same end , called the top . The last element pushed onto the stack is the…

3 min
B2.2.4

Explain the concept of a queue as a "first in, first out" (FIFO) data structure

A queue is a linear data structure where elements are added at the rear (back) and removed from the front . The first element added is the first one to be…

2 min
B2.4.1

Describe the efficiency of specific algorithms by calculating their Big O notation to analyse their scalability

Big O notation describes the upper bound of an algorithm's growth rate — how time (or space) increases as input size ($n$) grows.

2 min
B2.4.2

Construct and trace algorithms to implement a linear search and a binary search for data retrieval

How it works: Sequentially checks each element from the start until the target is found or the list ends. Works on any list — sorted or unsorted.

2 min
B2.4.3

Construct and trace algorithms to implement bubble sort and selection sort, evaluating their time and space complexities

How it works: Repeatedly steps through the list, compares adjacent pairs, and swaps them if they are in the wrong order. After each full pass, the largest…

3 min
B2.4.4

Explain the fundamental concept of recursion and its applications in programming.

Recursion is a programming technique where a function calls itself with updated arguments to solve a problem by breaking it into smaller, self similar sub…

3 min
B2.5.1

Construct code to perform file-processing operations

A file is a named collection of data stored on secondary storage (e.g., hard drive, SSD). Files allow data to persist after a program ends — unlike…

4 min

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