Problem Solving

Question 1

What is algorithmic thinking?

Answer 1

Algorithmic thinking is a way of solving problems by producing algorithms.

Question 2

What is an algorithm?

Answer 2

An algorithm is a reusable set of instructions (a series of steps) to solve a given problem.

Question 3

How do we represent algorithms in computing?

Answer 3

In computing, we often represent algorithms using pseudocode or flow diagrams.

Question 4

How do we interpret algorithms?

Answer 4

Look out for identifiers, identify inputs and outputs, examine output messages and looking for comments.

Question 5

What are identifiers?

Answer 5

Identifiers are the names of variables, constants and subroutines. These give clues bout the purpose of an algorithm.

Question 6

What are comments?

Answer 6

Comments are descriptions of the code. They often state the purpose of the algorithm. They are often the clearest way to identify an algorithm.

Question 7

What is pseudocode?

Answer 7

Pseudocode is a way to write out algorithms using code-like statements. It is intended to be very readable, and easy to understand.

Question 8

What is the purpose of pseudocode?

Answer 8

Pseudocode is not an actual programming language, it is used to plan algorithms, focusing on the logic and steps rather than language-specific syntax.

Question 9

What are flow charts?

Answer 9

Flow charts are used to visually represent the steps that make up an algorithm.

Question 10

What are ovals used for in flow charts?

Answer 10

An oval is used for the start and end of a program.

Question 11

What are rectangles used for in flow charts?

Answer 11

A rectangle is used to represent a process.

Question 12

What are parallelograms used for in flow charts?

Answer 12

A parallelogram is used to represent an input or an output.

Question 13

What are diamonds used for in flow charts?

Answer 13

A diamond is used to represent a decision.

Question 14

Why do the diamonds have labelled arrows coming out of it in flow charts?

Answer 14

A diamond/decision has two labelled arrows coming out of it to represent what happens if the condition in the diamond was true or false. ‘Yes’ arrows are for true, and ‘No’ arrows are for false.

Question 15

What are the common mistakes in programming?

Answer 15

Incorrect identifiers - such as lowercase and uppercase letters and similar looking character like 0 and O.
Incorrect operators - like less than signs put in the wrong way.
Missing processes - like when line of codes are forgotten.

Question 16

What is a search algorithm?

Answer 16

A search algorithm is a set of instructions for finding a specific item of data within a data set.

Question 17

What are examples of search algorithms?

Answer 17

Linear search and binary search.

Question 18

What is the concept of linear search?

Answer 18

If you were looking for a specific piece of paper in a stack of papers, then one way to find it would be to work from the top of the stack to the bottom, checking each paper on the way.

Question 19

How does linear search work in a program?

Answer 19

Check the first item in the dataset:
If it is what we are looking for, return it.
This is repeated for the rest of the items.
If the end of the data is reached, then the item was not in our data set.

Question 20

What are the pros and cons of linear search?

Answer 20

Pros - very easy to implement

Cons - slow on a long list

Question 21

What is the concept of binary search?

Answer 21

If you try to find a certain page in a book, it’s unlikely that you check every page. You are more likely to split the book in two and see if the page you need is before or after the split, and repeat.

Question 22

How does binary search work in a program?

Answer 22

Find the middle of the dataset.
If the middle value is > the target:
Repeat on the first half of dataset.
If the middle value is < the target:
Repeat on the second half of dataset.
If the middle value is the target:
The target has been found.
Stop repeating when the size of the dataset is zero.

Question 23

What are the pros and cons of binary search?

Answer 23

Pros - faster than linear search on a large dataset

Cons - dataset must be sorted before starting

Question 24

What is a sort algorithm?

Answer 24

A sort algorithm is a set of instructions to arrange a dataset into a particular order.

Question 25

What is efficient sorting?

Answer 25

An efficient sort algorithm is one which can sort a dataset in a short time.

Question 26

What are examples of sorting algorithms?

Answer 26

Bubble sort, merge sort and insertion sort.

Question 27

What is the concept of bubble sort?

Answer 27

There is a set of cards face up on a desk. If the first two cards are in the wrong order, you swap them. Do the same for the second and third cards, a continue in the same pattern until the end of the pack of cards. This is known as a pass. The highest value will ‘bubble’ up to the top of the pack each pass. By repeating this enough times, the pack of cards will be sorted.

Question 28

What is bubble sort in programming?

Answer 28

Compare the first two items of the dataset. If they are in the wrong order, swap them. Continue for the rest of the items of the dataset. Repeat the whole process, until a pass with no swaps happens.

Question 29

What are the pros and cons of bubble sort?

Answer 29

Pros - easy to implement and doesn’t use much memory

Cons - poor for efficiency

Question 30

What is the concept of a merge sort?

Answer 30

If there are two packs of cards, which are both already in order and want to combine them. The solution is to consider the top card of each pile only, and create a new deck starting from the smaller of the two cards. This will give us a combined sorted pack.

Question 31

What is merge sort in programming?

Answer 31

Split the lists in lists of size one. Merge each pair of sub lists by comparing the first value of each list and putting the smaller value into the new list first. Continue merging until there is only one list.

Question 32

What are the pros and cons of merge sort?

Answer 32

Pros - a very efficient algorithm

Cons - can be slower for small lists and needs additional memory

Question 33

What is abstraction?

Answer 33

Abstraction is a technique that simplifies a problem by removing unnecessary detail so that you can focus on the important parts that are relevant to the problem.

Question 34

What is decomposition?

Answer 34

Decomposition means breaking a complex problem, into smaller, more manageable sub-problems.
Each smaller part can then be solved individually, before all the sub-solutions are combined to solve the original problem.

Question 35

What are the advantages of decomposition?

Answer 35

It allows large teams to each take a part of a problem and work on it. It allows seemingly impossible problems to be solved by splitting them into simple tasks.

Question 36

What are structure charts?

Answer 36

Structure charts are used to visually represent breaking a large problem down into the smaller parts that make it up. Each box represents a smaller problem to be solved. Lines show which bigger problem the box is a part of.