Author: Paul Curzon

A recipe for programming

A bowl of hunnus
Bowl of Hummus by Image by Dana from Pixabay

How is a computer program like a recipe? Let’s see, and as a bonus, here’s how to cook a quick pasta dish (for International Hummus Day).

Programmers are the master chefs of the computing world – except the recipes they invent don’t just give us a nice meal, they change the way we live.

Programs are very similar to recipes. They both give instructions that, if followed, achieve something. There is a difference between them, though, and it has to do with language. When chefs invent recipes they write them out in human languages like English. Programmers write programs in special languages. Why’s that? It’s all about being precise enough to be sure exactly the same thing happens every time. Recipes are often ambiguous which is why when I follow one it sometimes goes wrong. Programs tie down every last detail.

Let’s apply some ideas from programming languages to making meals. One of my favourite recipes is a hummus-based pasta dish (see box) so we’ll use that.

Hummus and Tomato Pasta
Serves 2
This is a very quick 20-minute after work dish.

Olive oil
1 teaspoon of whole cumin seeds
1 large chopped onion
400g chopped plum tomatoes
200g hummus 150g pasta

1. Add the pasta to a large pan of boiling water. Simmer for 10 minutes.
2. Fry the cumin in the olive oil for a few minutes. Add the onions and fry gently.
3. Stir in the tomatoes and the hummus and leave to simmer for 5 minutes.
4. Drain the pasta and serve.

Structure it!

The first thing to notice about a recipe book is there is a clear structure. Each recipe is obviously separate from the others. Each has a title and a brief description of how it might be used. Each has an ingredients list and then a series of steps to follow. Programs follow a similar structure.

Cookery books use page layout to show their structure. Programmers use language: grammar, symbols and keywords. A keyword is a word that means something special. Once you have decided a word is a keyword you only ever use it for that purpose.

Let’s invent a keyword RECIPE to mean we’re starting a new recipe. The only time that word will appear in our recipes is to start a new recipe. What follows it will always be the name of the recipe. We will also need to know when the name ends. To make that clear we will use a special symbol made up of open and close brackets ().

We also want to be absolutely sure what is part of this recipe and what isn’t. We will use curly brackets: everything between the brackets is part of the named recipe.

RECIPE Hummus and Tomato Pasta ()
{
...
}

No comment?

Recipes usually include a brief description that isn’t part of the actual instructions. It is just there to help someone understand when you might use the recipe. Programs have descriptions like this too. Programmers call them ‘comments’. Remove the comments and the recipe will still work. We need a clear way to show when a comment starts and ends. We will start them with a special symbol ‘/*’ and end them with ‘*/’.

RECIPE Hummus and Tomato Pasta ()
{
/* Serves 2
This is a very quick 20-minute after work dish.
*/
...
}

Variable storage

What comes next in a recipe is usually a list of ingredients. The idea is to list everything you need so you can have it all ready before you start. I often have a problem following recipes, though, as they don’t list absolutely everything. Mid- recipe I might suddenly find I need a frying pan…when mine is crusted with burnt cheese sauce from last night! To avoid that, let’s list all the pans we need too. For our recipe we need a frying pan and a saucepan.

Something used to store things (like pans do) in a program is called a ‘variable’. Program variables hold things like numbers. The equivalent of the ingredients list ‘declares’ the variables. Declarations give each variable a unique name used to refer to it and also give each a ‘type’ – is it a saucepan or a frying pan we need? To be clear about when a declaration ends we add in some punctuation. Programming languages tend to use a semicolon for that – it’s a bit like a full stop in English.

Saucepan pan1;
Fryingpan pan2;

This says that in the rest of the recipe when we say pan1 (the variable name) we mean a particular pan: a saucepan (its type). When we say pan2 we mean a particular frying pan.

New assignment

Assignment does NOT move things around, it makes new copies

We will make a distinction between things to hold stuff, like pans (variables) and the actual ingredients that go in them: ‘values’. We will also follow the TV chefs and start by setting out all the ingredients in little dishes at the start so they are at hand – and make that part of the instructions.

We will need to declare a dish to hold each ingredient, giving its type and giving the dish a name. At the same time we will say what should be put in it before the recipe proper is started. We will use an ‘=’ symbol to mean put something in a variable (i.e., dish or pan). In programs, this action of putting something in a variable is called ‘assignment’. So, for example, we will declare that we need a dish to hold the hummus (called hummusDish). We assign 200g of hummus to it.

Dish hummusDish = 200g hummus;

We are now ready for the recipe proper. We can use assignment as a precise way of moving things from one place to another too. So if we say, for example:

pan2 = oilDish;

We mean empty the contents of the dish of oil into the frying pan. Programs are slightly different here, as when they do an assignment they don’t move things from one place to the other, they copy it. That would be like having a dish that automatically refilled itself whenever it was emptied.

Often we want to add to whatever is already in a pan. Programmers leave nothing to doubt and say explicitly that is what they mean:

pan2 = pan2 + onionDish;

This tells us to mix what is in the onion dish with what is in the frying pan, and then leave the result in the frying pan. We will use the + symbol to mean add together and stir.

Methods in my madness

So far all we’ve done is put ingredients in things and copied them around. To make a meal we need to do various basic cooking things like heat a pan or drain a pan. Rather than spell out every step of how you do that in every recipe, we will use a short hand. We create mini-recipes that say how to do it and just refer to them by name. They are often called ‘methods’ by programmers. Each is written out just like our recipe. In fact to a programmer our recipe is a method too. When we want to use it we just give its name followed by any extra information needed. For example to heat a pan, we need to know which pan, how high a heat and for how long. We write, for example:

Heat (pan1, medium, 12 minutes);

This format helps make sure we don’t miss something (like the time for example). We need similar methods for draining a pan and serving the meal. We won’t give the actual instructions here. In a full program they would be written down step-by- step too and not left to chance.

Time to do it right

We have come up with a language for recipes similar to the ones used for programming. We’ve used symbols, keywords and very precise punctuation – the language’s ‘syntax’ – to help us be precise. On its own that’s not enough – each part of the language has to have a very clear meaning too – the language’s ‘semantics’. Together they make sure in following a recipe we know exactly what each step involves. There is then less scope for a cook (or computer) to get it wrong. Computers, of course, have no intelligence of their own. All they can do is exactly follow the instructions someone wrote for them (a bit like me cooking).

Here’s what our complete recipe looks like as a program.

RECIPE Hummus and Tomato Pasta ()
{
  /* Serves 2

  This is a very quick after work dish.
  It only takes about 20 minutes from start to finish.

  Saucepan pan1;
  Fryingpan pan2;

  /* Ingredients */
  Dish oilDish = 1 tablespoon of olive oil;
  Dish cuminDish = 1 teaspoon of whole cumin seeds;
  Dish onionDish = 1 large onion, chopped;
  Dish tomatoDish = 400g chopped plum tomatoes;
  Dish hummusDish = 200g hummus;
  Dish pastaDish = 150g pasta;
  Kettle kettle = 500ml boiling water;

  /* Cook the pasta */
  pan1 = kettle + pastaDish;
  Heat (pan1, high, 2 minutes);
  Heat (pan1, medium, 10 minutes);

  /* Make the sauce */
  pan2 = oilDish + cuminDish;
  Heat (pan2, high, 2 minutes);
  pan2 = pan2 + onionDish;
  Heat (pan2, medium, 5 minutes);
  pan2 = pan2 + tomatoDish + hummusDish;
  Heat (pan2, low, 5 minutes);

  /* serve */
  Drain (pan1);
  Serve (pan1, pan2);
}

Paul Curzon, Queen Mary University of London

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Florence Nightingale: rebel with a cause

Kerosene lamp
Image by Agnieszka from Pixabay modified by CS4FN

Florence Nightingale, the most famous female Victorian after Queen Victoria, is known for her commitment to nursing, especially in the Crimean War. She rebelled against convention to become a nurse at a time when nursing was seen as a lowly job, not suitable for ‘ladies’. She broke convention in another less well-known, but much more significant way too. She was a mathematician – the first woman to be elected a member of the Royal Statistical Society. She also pioneered the use of pictures to present the statistical data that she collected about causes of war deaths and issues of sanitation and health. What she did was an early version of the current Big Data revolution in computer science.

Soldiers were dying in vast numbers in the field hospital she worked in, not directly from their original wounds but from the poor conditions. But how do you persuade people of something that (at least then) is so unintuitive? Even she originally got the cause of the deaths wrong, thinking they were due to poor nutrition, rather than the hospital conditions as her statistics later showed. Politicians, the people with power to take action, were incapable of understanding statistical reports full of numbers then (and probably now). She needed a way to present the information so that the facts would jump out to anyone. Only then could she turn her numbers into life-saving action. Her solution was to use pictures, often presenting her statistics as books of pie charts and circular histograms.

Nightingale's rose chart
Florence Nightingale Rose Chart, Public domain, via Wikimedia Commons

Whilst she didn’t invent them, Florence Nightingale certainly was responsible for demonstrating how effective they could be in promoting change, and so subsequently popularising their use. She undoubtedly saved more lives with her statistics than from her solitary rounds at night by lamplight.

She had collected data on the reason each person died but to present the data in ways that were convincing she also had to act as a human computer doing computation on the basic data. For each month based on the raw data, she computed annual rate of mortality per 1,000. Then to present it in a circular histogram, where the area represents deaths she calculated the appropriate radius for each segment, allowing the charts to then be drawn.

FLorence Nightingale portrait
Florence Nightingale by Augustus Egg. Public domain, via Wikimedia Commons

Big Data is now a big thing. It is the idea that if you collect lots of data about something (which computers now make easy) then you (and computers themselves) can look for patterns and so gain knowledge and, for people, ultimately wisdom from it. Florence Nightingale certainly did that. Data visualisation is now an important area of computer science. As computers allow us to collect and store ever more data, it becomes harder and harder for people to make any sense of it all – to pick out the important nuggets of information that matter. Raw numbers are little use if you can’t actually turn them into knowledge, or better still wisdom. Machine Learning programs can number crunch the data and make decisions from it, but its hard to know where the decisions came from. That often matters if we are to be persuaded. For humans the right kind of picture for the right kind of data can do just that as Florence Nightingale showed.

‘The Lady of the Lamp’: more than a nurse, but also a remarkable statistician and pioneer of a field of computer science…a Lady who made a difference by rebelling with a cause.

Paul Curzon, Queen Mary University of London

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HMS Belfast: destroying the destroyer

by Paul Curzon, Queen Mary University of London

HMS Belfast

On the South Bank of the Thames in the centre of London lies the HMSBelfast. Now a museum ship, it once took part in one of the most significant sea battles of the Second World War. It fought the Scharnhorst in the last great sea battle based on the power of great guns. The Belfast needed more than just brilliant naval tactics to stand a chance. It needed help from computer science and electronic engineering too. In fact, without some brilliant computer science the battle would never have been fought in the first place. It came about because of the work of the code crackers at Bletchley Park.

Getting supplies across the Atlantic and then round to Russia was critical to both the British and Russian’s survival. By 1943 the threat of submarines had been countered. The battleship Tirpitz had also been disabled. However, the formidable battle cruiser Scharnhorst was left and it was the scourge of the Allied convoys. It sank 11 supply ships in one operation early in 1941. In another, it destroyed a weather station on Spitzbergen island that the Allies used to decide when convoys should set off.

By Christmas 1943 something had to be done about the Scharnhorst, but how to catch it, never mind stop it? A trap was needed. A pair of convoys going to and from Russia were a potential bait. The Nazis knew the target was there for the taking: the Scharnhorst was in a nearby port. Would they take that bait though, and how could the British battle ships be in the right place at the right time to not only stop it, but destroy it?

The Allies had an ace up their sleeve. Computer Science. By this point in the war a top secret team at Bletchley Park had worked out how to crack the Enigma encryption machine that was used to send coded messages by the German Navy. It was always easy to listen in to radio broadcasts, you just needed receivers in the right places, but if the messages were in code that didn’t help. You had to crack the day’s code to know what they were saying. Based on an improved approach, originally worked out by Polish mathematicians, the Brits could do it using special machines that were precursors to the first electronic computers. They intercepted messages that told them that Scharnhorst was preparing to leave. It was taking the bait.

The British had two groups of ships. The Belfast, the Norfolk and the Sheffield were coming from Russia protecting the returning convoy. The HMS Duke of York was tracking the new convoy heading to Russia. Both were keeping their distance so the convoys looked unprotected. They needed to know when and where the Scharnhorst would attack. Bletchley Park were listening in to everything though, and doing it so well they were reading the messages almost as soon as the Germans. At 2am on Boxing Day morning the Belfast got the message from Admiralty Head quarters that SCHARNHORST PROBABLY SAILED AT 1800 25 DECEMBER. A further radio signal from the Scharnhorst asking for a weather report allowed the spies to work out exactly where the ship was by picking up the signal from different listening stations and triangulating: drawing a line on a map from each station in the direction the radio signal came from. The point they meet is the ship’s location. This is an example of meta-data (information about a message rather than the message itself) giving vital information away. The spies had done their job. It was enough to tell Vice Admiral Burnett on the Belfast where the Scharnhorst was aiming to attack the convoys. They could lie in wait. At this point, electronic engineering mattered. The Belfast had better radar than the Scharnhorst. They detected its approach without the Scharnhorst having any idea they were there. The first the Captain of the Scharnhorst knew was when they were hit by shells from the Norfolk. The Belfast ended up out of position at the critical point though and couldn’t join in. The faster Scharnhorst turned tail and ran. The Brits had had their chance and blown it!

Burnett now needed luck and intuition. He guessed the Scharnhorst would try another attack on the convoy. They took up a new waiting position rather than actively trying to find the Scharnhorst as others wanted them to do. By midday the radar picked it up again. The trap was reset, though this time the initial surprise was lost. An all out battle began, with radar helping once again, this time as a way to aim shells even when the enemy wasn’t in sight. Having failed to reach the convoy undetected a second time the Scharnhorst retreated as the battle continued. What they didn’t know was that they were retreating deeper into the trap: heading directly towards the waiting Duke of York. The chasing Belfast stopped firing and dropped back, making the Scharnhorst crew think they were safe. In fact, they were still being followed and tracked by radar once more, though only by the Belfast as the other ships had actually been partially disabled. Had the Scharnhorst known, they could have just stopped and taken out the Belfast. After several hours of silent shadowing, the Belfast picked up the Duke of York on the radar, and were able to communicate with them. The Scharnhorst’s radar had been crippled in the battle and thought it was alone.

The Belfast fired shells that lit up the sky behind the Scharnhorst as seen from the Duke of York, then largely watched the battle. Luck was on their side: the Scharnhorst was crippled and then sunk by torpedoes. Over a thousand German sailors sadly died. The crew of the Belfast were well aware that it could just as easily have been them, sealed in to a giant metal coffin, as it sank, and so held a memorial for the dead Germans afterwards.

The Belfast didn’t fire the torpedoes that finally sank the Scharnhorst and was not the key player in the final battle. However, it was the one that was in the right place to save the convoy, thanks to the Enigma decrypts combined with the Vice Admiral’s intuition. It was also the one that pushed the Scharnhorst into the deadly trap, with its superior radar then giving it the advantage.

It is easy to under-estimate the importance of the Bletchley Park team to the war, but they repeatedly made the difference, as with the Scharnhorst, making Allied commanders look amazing. It is much easier to be amazing when you know everything the other side says! The Scharnhorst is just one example of how Computer Science and Electronic Engineering help win wars, and here, in the long run at least, save lives. Today having secure systems matters to everyone not just to those waging war. We rely on them for our bank system, our elections, as well as for our everyday privacy, whether from hacking newspapers or keeping our health records secret from ruthless companies wanting to exploit us. Cyber security matters.

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Machines Inventing Musical Instruments

cupped hands in dark Image by Milada Vigerova from Pixabay
Image by Milada Vigerova from Pixabay 

Machine Learning is the technology driving driverless cars, recognising faces in your photo collection and more, but how could it help machines invent new instruments? Rebecca Fiebrink of Goldsmiths, University of London is finding out.

Rebecca is helping composers and instrument builders to design new musical instruments and giving them new ways to perform. Her work has also shown that machine learning provides an alternative to programming as a way to quickly turn design ideas into prototypes that can be tested.

Suppose you want to create a new drum machine-based musical instrument that is controlled by the wave of a hand: perhaps a fist means one beat, whereas waggling your fingers brings in a different beat. To program a prototype of your idea, you would need to write code that could recognize all the different hand gestures, perhaps based on a video feed. You would then have some kind of decision code that chose the appropriate beat. The second part is not too hard, perhaps, but writing code to recognize specific gestures in video is a lot harder, needing sophisticated programming skills. Rebecca wants even young children to be able to do it!

How can machine learning help? Rebecca has developed a machine learning program with a difference. It takes sensor input – sound, video, in fact just about any kind of sensor you can imagine. It then watches, listens…senses what is happening and learns to associate what it senses with different actions it should take. With the drum machine example, you would first select one of the kinds of beats. You then make the gesture that should trigger it: a fist perhaps. You do that a few times so it can learn what a fist looks like. It learns that the patterns it is sensing are to be linked with the beat you selected. Then you select the next beat and show it the next gesture – waggling your fingers – until it has seen enough examples. You keep doing this with each different gesture you want to control the instrument. In just a few minutes you have a working machine to try. It is learning by example how the instrument you are wanting works. You can try it, and then adjust it by showing it new examples if it doesn’t quite do what you want.

It is learning by example how
the instrument you are wanting works.

Rebecca realised that this approach of learning by example gives a really powerful new way to support creativity: to help designers design. In the traditional ways machine learning is used, you start with lots of examples of the things that you want it to recognize – lots of pictures of cats and dogs, perhaps. You know the difference, so label all these training pictures as cats or dogs, so it knows which to form the two patterns from. Your aim is for the machine to learn the difference between cat and dog patterns so it can decide for itself when it sees new pictures.

When designing something like a new musical instrument though, you don’t actually know exactly what you want at the start. You have a general idea but will work out the specifics as you go. You tinker with the design, trying new things and keeping the ideas that work, gradually refining your thoughts about what you want as you refine the design of the instrument. The machine learning program can even help by making mistakes – it might not have learnt exactly what you were thinking but as a result makes some really exciting sound you never thought of. You can then explore that new idea.

One of Rebecca’s motivations in wanting to design new instruments is to create accessible instruments that people with a wide range of illness and disability can play. The idea is to adapt the instrument to the kinds of movement the person can actually do. The result is a tailored instrument perfect for each person. An advantage of this approach is you can turn a whole room, say, into an instrument so that every movement does something: an instrument that it’s impossible not to play. It is a play space to explore.

Playing an instrument suddenly really is just playing.

Paul Curzon, Queen Mary University of London based on a 2016 talk by Rebecca Fiebrink

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Return of the killer robot? Evil scientist?! Helpless woman?!?

(You can be the one to tell Angelina Jolie!)

Damsel tied to a tree being rescued by a hunky knight
Painting by Frank Bernard Dicksee, Public domain, via Wikimedia Commons

Lots of people think that Computer Science and IT are strictly for men only. That’s really bizarre given that right from the start women like Grace Hopper and Ada Lovelace played pivotal roles in the development of computers, and women are still at the leading edge today. To be a successful modern IT Pro you have to be a good team player, not to mention good at dealing with clients, which are skills women are generally good at.

‘Geeky male computer scientist’ is of course just a stereotype, like ‘helpless female in need of rescue by male hunk’, ‘scientist as mad eccentric in white coat’, or ‘evil robot wanting to take over the world’.

Where do false stereotypes come from? Films play a part in the way their (usually male, non-scientist) directors decide to represent characters.

Students on a ‘Gender in Computer Science’ course at Siena College in the US watched lots of films with Computer Science plots from as far back as 1928 to see how the way women, computers and computer scientists are portrayed has changed over time. Here are their views on some of those films.

Do you agree – when you are done read what the real IT Pros think of their jobs…and remember stereotypes are fiction, careers are what you make of them and real robots are (usually) nice!

1928: Metropolis

In a city of the future the ruling class live lavishly while the workers live poorly in the underworld. An evil scientist substitutes a robot for a female worker activist. It purposely starts a riot as an excuse so reprisals can be taken. All hell breaks loose until the male hero comes to the rescue…

X Computers: Evil

X Women as IT Pros: Helpless

X Computer Scientists: Evil

“Women are more or less portrayed as helpless … The computer scientist … as evil”

1956: Forbidden Planet

An all-male crew travel to Altair-4 to discover the fate of the colony there. They discover all that is left is scientist Dr Morbius, his beautiful daughter Altaira and a servant robot called Robby, programmed to be unable to harm humans. But what have Morbius’ machines and experiments to do with the colony’s fate?

✓ Computers: Helpful & Harmless

X Women as IT Pros: love interest

X Computer Scientists: Evil

“Altaira plays a typical woman’s role…helpless…unintelligent …Barbie-like”

1971: THX 1138

In an Orwellian future, an android controlled police state where everyone is made to take drugs that suppress emotion. LUH 3417 and THX 1138 stop taking their drugs, fall in love and try to escape…

X Computers: Evil Police

X Women as IT Pros: Few

X Computer Scientists: Heartless

“The computer scientists are depicted as boring, heartless and easily confused”

1982: Blade Runner

In the industrial wastelands of a future Los Angeles, large companies have all the power. Robotic ‘Replicants’ are almost indistinguishable from humans but have incredible strength and no emotions. Deckard (Harrison Ford) must find and destroy a group of Replicants that have developed emotions and so threaten humanity as they rebel against being ‘slaves’.

X Computers: Evil

X Women as IT Pros: None

X Computer Scientists: Caused the problem

“A woman plays the minor role of a replicant…but is portrayed as a topless dancer”

1986: Short Circuit

A comedy adventure about a robot that comes ‘alive’ after a power surge in a lightening storm. The robot, called ‘Number 5’ built for use by the US military and tries to escape its creators as it doesn’t want to ‘die’. It is helped by Stephanie Speck (Ally Sheedy) who realises, that like the animals she loves, it is sentient and helps it escape from the scientists of company Nova that built it.

✓ Computers: Nice

X Women as IT Pros: None

X Computer Scientists: Thick-headed

“The male computer scientists are often thick-headed… introverted…no life skills…There were no female computer scientists”

1995: Hackers

A group of genius teenage hackers become the target of the FBI after they unknowingly tap into a high-tech embezzling scheme that could cause a horrific environmental disaster. Dade Murphy and Kate Libby (Angelina Jolie) square off in a battle of the sexes and computer skills.

X Computers: Used illegally

✓ Women as IT Pros: Elite…but illegal

X Computer Scientists: Criminals

“Angelina plays a hard hitting, elite hacker who is better than everyone in her group except Dane who is her equal”

So it wasn’t great. Robots were killers, scientists evil. Computer scientist’s were introverted and thickheaded. Women were either sexbots or helpless love interest to be rescued by the hunky male star. 1995’s film Hackers was about as good as it got. At last a woman had expert computing skills. It’s hardly surprising some girls were led to believe computing isn’t for them with a century-long “conspiracy” aiming to convince them their role in life is to be helpless.

As our area on women in computing shows the truth is far more interesting. Women have always played a big part in the development of modern technology. So have things improved in films in the 21st century? There are more films with strong action-heroine stars now, though until very recently few films passed the Bechdel test: do two women ever talk together about anything other than a man? So can we at least find any 21st century films with realistic main character roles for women as computer experts? Here goes…

1999-2003: Matrix Trilogy

Hero Neo discovers reality isn’t what it seems. It is all a virtual reality. Trinity is there to be his romantic interest – she’s been told by the Oracle that she will fall in love with the “One” (that’s him). It’s not looking good. In film 2 Neo has to save her. Oh dear. At least she is supposed to be a super-hacker famous for cracking an uncrackable database. Oh well.

X Computers: Enslaving humanity

✓ Women as IT Pros: Elite…but illegal (there to be saved)

✓ Computer Scientists: The resistance

2009: The Girl With the Dragon Tattoo

This is the story of super-hacker Lisbeth Salander. Both emotionally and sexually abused as a child she looks after herself, and that includes teaching herself to be an expert with computers. She uses her immense skills to get what she wants. She is cool and clever and absolutely not willing to let the men treat her as a victim. Wonderful.

X Computers: used for hacking

✓ Women as IT Pros: Elite…but illegal look after themselves)

X Computer Scientists: hackers

2014: Captain America: The Winter Soldier

This film is all about a male hunk, so it’s not looking good, but then early on we see Agent Natasha Romanoff, (also known as superheroine the Black Widow). She is the brains to Captain America’s brawn and from the start she is clearly the expert with computers. While Captain America beats people up, her mission is to collect data. And she even gets her own film series…eventually!

X Computers: used for hacking

✓ Women as IT Pros: Elite…superheroes

X Computer Scientists: hackers

2015: Star Wars: Episode VII – the Force Awakens

Rey is a scavenger with engineering skills. She is very smart, and can look after herself without expecting men to save her. She’s not a hacker! Instead, she creates and mends things. She repurposes parts she finds on wrecked spaceships to sell to survive. She learnt her engineering skills tinkering in old ships and fixes the Millennium Falcon’s electro-mechanical problems. She is even the main character of the whole film!

✓ Computers: make the universe work

✓ Women as IT Pros: Elite, scavenges and fixes things

✓ Computer Scientists: at least some build and fix things

There are plenty of moronic films, made by men who can’t portray women in remotely realistic ways, but at least things are a bit better than they were last century. The women are already here in the real world. They are slowly getting there in the movies. Let’s just hope the trend speeds up, and we have more female leads who create things, like the real female computer scientists.

Paul Curzon, Queen Mary University of London

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Who invented Morse code?

Morse Code
Morse Code: Image by CS4FN

Who invented Morse code? Silly question, surely! Samuel Morse, of course. He is one of the most celebrated inventors on the planet as a result. Morse code helped revolutionise global communications. It was part of the reason the telegraph made fast, world-wide communication a practical reality. Morse did invent a code to use for the telegraph, but not Morse code. His code was, by comparison, a poor, inflexible solution. He was a great businessman, focussed on making his dream a reality, but perhaps not so good at computational thinking! The code that bears his name was largely invented by his partner Alfred Vail.

Samuel Morse was originally a painter. However, his life changed when his wife died suddenly. He was away doing a portrait commission at the time. On hearing of his wife’s illness he rushed home, but the message, delivered by a horse rider had taken too long to reach him and she died and was buried before he got there. He dedicated his life to giving the world a better way of communicating as a result. Several different people were working on the idea of a way to send messages by electricity over wires, but no one had really come up with a usable, practical system. The physics had largely been sorted, but the engineering was still lacking.

Morse came up with a basic version of an electrical telegraph system and he demonstrated it. Alfred Vail saw the demonstration and persuaded Morse to take him on as a partner. His father built a famous ironworks, and so he had worked as a machinist. He improved Morse’s system enormously including making the tapping machine used to send messages.

He wasn’t just good at engineering though. He was good at computational thinking, so he also worked on the code used for sending messages. Having a machine that can send taps down a wire is no use unless you can also invent a simple, easy to use algorithm that turns words into those taps, and back again once it arrives. Morse came up with a code based on words not letters. It was a variation of the system already used by semaphore operators. It involved a code book: essentially a list of words. Each word in the book was given a number. A second code turned numbers in to taps – in to dots and dashes. The trouble with this system is it is not very general. If the word you want to send isn’t in the code book you are stuffed! To cover every possibility it has to be the size of a dictionary, with every word numbered. But that would make it very slow to use. Vail came up with a version where the dots and dashes represented letters instead of numbers, allowing any message to be sent letter by letter.

He also realised that some letters are more common than others. He therefore included the results of what we now call “frequency analysis” to make the system faster, working out the order of letters based on how common they are. He found a simple way to do it. He went to his local newspaper offices! To print a page of text, printing presses used metal letters called movable type. Each page was built up out of the individual metal letters slotted in to place. Vail realised that the more common a letter was, the more often it appeared on any page, and the more metal versions the newspaper office would therefore need if they weren’t to keep running out of the right letters before the page was done. He therefore counted how many of each “movable type” letter the newspaper printers had in their trays. He gave the letters that were most common the shortest codes. So E, for example, is just a single dot as it is the most common letter in American English. T, which is also common, is a single dash. It is this kind of attention to detail that made Morse code so successful. Vail was really good at computational thinking!

Morse and Vail worked really well as a team, though Morse then took all the credit because the original idea to solve the problem had been his, and their agreement meant the main rights were with Morse. They almost certainly worked together to some extent on everything to do with the telegraph. It is the small details that meant their version of the telegraph was the one that took over the world though and that was largely down to Vail. Morse may be the famous one but the invention of the telegraph needed them both working together.

Paul Curzon, Queen Mary University of London

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Cyber Security at the Movies: Guardians of the Galaxy (Fail Secure security)

[Spoiler Alert]

If you are so power hungry you can’t stand the idea of any opposition; if you want to make a grab for total power, so decide to crush everyone in your way, then you might want to think about the security of your power supply first. Luckily, all would-be dictators who crush everyone who gets in their way as they march towards total domination of the galaxy, tend to be very naive about cyber-security.

Take Ronan the Accuser in the original Guardian of the Galaxy film. He’s a villain with a religious streak, whose belief that strength is virtue and weakness is sin leads to his totally corrupted morality. To cut to the guts of the story he manages to get the “Infinity Stone” that gives unimaginable power to its owner. With it he can destroy anyone who gets in his way so sets out to do so.

Luckily for the Galaxy, good-guy Peter Quill, or Star-Lord as he wants to be known, and his fellow Guardians have a plan. More to the point they have Gamora. She is an assassin originally sent to kill Quill, but who changes sides early on. She is an insider who knows how Ronan’s security system works, and it has a flaw: its big, heavy security doors into his control room.

Security Lesson 1. It should still be secure even when the other side know everything about how it works. If your security relies on no one knowing, its almost certainly bad security!

Once inside his ship, to get to Ronan the Guardians will need to get through those big heavy security doors. Now once upon a time big, heavy doors were locked and barred with big, heavy bolts. Even in Roman times you needed a battering ram to get in to a besieged city if they had shut the doors before you got there. Nowadays, how ever big and heavy the door, you may just need some cyber skills to get in if the person designing it didn’t think it through.

Electromagnetic locks are used all over the place and they give some big advantages, such as the fact that they mean you can program who is and isn’t allowed entry. Want to keep someone out – you can just cancel their keycard in the system. They are held locked by electromagnets: magnets that are switched on and off using an electric current. That means computers can control them. As the designer of an electromagnetic lock you have a choice, though. You can make them either “fail safe” or “fail secure”. With a fail safe lock, when the power goes, the doors automatically unlock. With fail secure, instead they lock. Its just a matter of whether the magnet is holding the door open or closed. Which you choose when designing the lock depends on your priorities.

Fail safe is a good idea, for example, if you want people to be able to escape in an emergency. If a fire cuts the electricity you want everyone to still be able to get out, not be locked in with no chance of escape. Fail secure on the other hand is good if you don’t want thieves to be able to get in just by cutting the power. The magnets hold the bolts open, so when the power goes, the spring shut.

Security Lesson 2. If you want the important things to stay secure, you need a fail secure system.

This is Ronan’s problem. Zamora knows that if you cut the power supply then the doors preventing attackers getting to him just open! He needed a fail secure door, but instead had a fail safe one installed. On such small things are galaxies won and lost! All Zamora has to do is cut the power and they can get to him. This of course leads to the next flaw in his security system. It wouldn’t have mattered if the power supply was on the secure side of that door, but it wasn’t. Ronan locks himself in and Zamora can cut the power from the outside … Dhurr!

There is one last thing that could have saved Ronan. It needed an uninterruptible power supply.

Security Lesson 3. If your system is reliant on the power supply, whether a door, your data, your control system or your life-support system, then it should keep going even if the power is switched off.

After all, what if the space ships cleaners (you never see them but they must be there somewhere!) unplug the door lock by mistake just because they need somewhere to plug in the hoover.

The solution is simple: use an “uninterruptible power supply”. They are just very fast electricity storage systems that immediately and automatically take over if the main power cuts out. The biggest on Earth keeps the power going for a whole city in Alaska (you do not want to lose the power running your heating mid-winter if you live in Alaska!). Had Ronan’s doors had a similar system, the doors wouldn’t have just opened as the power would not have been cut off.It’s always the small details that matter in cyber security (and in successfully destroying your enemies and so ruling the universe). As with all computational thinking, you have to think about everything in advance. If you don’t look after your power supply, then you may well lose all your power over the galaxy too (and your life)!

by Paul Curzon, Queen Mary University of London

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