On Coding

Jon Reades - j.reades@ucl.ac.uk

12th October 2026

According to the BBC & Google, programming is about:

Decomposition: breaking down a complex problem or system into smaller, more manageable parts.
Pattern recognition: looking for similarities among and within problems.
Abstraction: focusing on the important information only, ignoring irrelevant detail.
Algorithms: developing a step-by-step solution to the problem, or the rules to follow to solve the problem.

What About Computational Thinking?

Computational thinking is not thinking like a Computer Scientist. It is about recognising how to code can help us to understand, and manipulate, the world.

Key Features

Aspects of computational thinking include:

Recognising how one problem connects to other problems.
Recognising when and how to make things simpler and faster
Recognising how different ways of tackling a problem gives you power to tackle new problems.

See this keynote by Lorena Barba (2014); esp. from 52:00 onwards.

Why Are These Virtues?

According to Larry Wall the three virtues of the programmer are:

Laziness
Impatience
Hubris

These are not to be taken literally (see Larry Wall’s “Three Virtues of a Programmer” are Utter Bull💩).

Four Quotes to Remember

Computers make very fast, very accurate mistakes.
A computer program does what you tell it to do, not what you want it to do.
Only half of programming is coding. The other 90% is debugging.
Weeks of coding can save you hours of planning.

And One More…

> Experience is the name everyone gives to their mistakes.

Oscar Wilde

Algorithm as Recipe…

Following a Recipe is Easy, Right?

Source

Calculating the Mean

Given these numbers, what’s the average?

1, 4, 7, 6, 4, 2

As a Recipe

Take a list of numbers
Start a count of numbers in the list at 0
Start a sum of numbers in the list at 0
Take a number from the list:
- Add 1 to the count
- Add the value of the number to the sum
Repeat step #4 until no numbers are left in the list.
Divide the sum by the count
Report this number back to the user

As Python

numbers = [1, 4, 7, 6, 4, 2]
total   = 0
count   = 0
for num in numbers:
  total = total + num 
  count = count + 1
mean = total / count
print(mean)

Why We Still Haven’t ‘Solved It’

Source

Computers are good at:

Doing exactly what they are told.
Doing it over and over indefinitely.

Computers are not good at:

Solving problems that you can’t define.
Creating new knowledge.

Languages

Computer languages come with all of the ‘baggage’ of human languages; they have:

A vocabulary (reserved words)
A grammar (syntax)
Rules about the kinds of things you can say (grammar)
Styles and idiosyncrasies all their own (history)

In this module we will use the Python programming language. We could also teach this same content in R.

Python

numbers = [1, 4, 7, 6, 4, 2]
total   = 0
count   = 0
for num in numbers:
  total = total + num 
  count += 1 # An alternative to count = count + 1
mean = total / count
print(mean)

R

numbers = c(1, 4, 7, 6, 4, 2)
total   = 0
count   = 0
for (num in numbers) {
  total = total + num
  count = count + 1
}
mean = total / count
print(mean)

Finally: Style

Although all programmers develop their own style (see: writing in any language), Python encourages coders to use a consistent style so that others can pick up your code and make sense of what’s going on (see: comments!).

Two useful resources:

> It’s okay to figure out murder mysteries, but you shouldn’t need to figure out code. You should be able to read it.

Steve McConnell

Source: xkcd

Science is what we understand well enough to explain to a computer. Art is everything else we do.

Donald Knuth, Things a Computer Scientist Rarely Talks About