Beatrice Worsley: pioneering programmer

Female professional computer scientist working at a bank of screens — Image by Artista Digital from Pixabay

Many of the earliest programmers were women, just as before them many of the human computers were women. It was only later that somehow programming changed in people’s heads to be something men did. One of the earliest was Mexican born, Canadian, Beatrice Worsley. She wrote the first program to be run on the EDSAC computer and gained one of the earliest pure Computer Science PhDs on programming.

Beatrice was outstanding at both Maths and Science at school and at university demonstrated it by coming top in the class in many of the subjects she took during her degree, gaining grades corresponding to a First every year. She spent the war as a Wren in the Canadian Navy (including working as a researcher for the Navy) before going back to university to do a Masters at MIT. There she completed her project that involved surveying virtually all the computing devices of the time (whether completed or planned). Her survey not only included the very primitive computers being bulit immediately after the war, but also the earlier mechanical calculators, such as the ones IBM made its name creating, and differential analysers. The latter are analogue computing devices that were both precursors, and work in a completely different way, to today’s digital machines. Rather than converting data into 0s and 1s they manipulate physical equivalents of actual values as represented by wheels and discs. Unlike the digital computers to come which could be applied to any problem, they solved just one kind of mathematical problem so were not flexible in the way modern computers are.

This Masters thesis set her up for her future career as a computer scientist: she had realised by then that computing was the future. Initially, she got a job helping run IBM mechanical calculators in Toronto. As part of this job she actually built her own working differential anlalyser out of the children’s construction set Meccano.

At this point, Maurice Wilkes ar Cambridge University was building a new kind of machine called EDSAC. This differed from the very first digital computers in that it included stored programs – the program it followed was just data within computer memory, not something physically hard-wired into the machine. This followed the ideas first spelled out by Alan Turing in his description of a Turing Machine and developed by John von Neumann as the von Neumann architecture. It had the basic design we now think of as the basis of modern computers.

Beatrice was sent to Cambridge to find out more about it while it was being constructed, and got involved in getting it to work. It successfully ran its first stored program on 6 May 1949. That first program calculated a table of squares of numbers and it was written by Beatrice, making her the first programmer of what is arguably the first fully-fledged computer as we now know it (as opposed to a demonstration prototype). She also as a result wrote one of the earliest research papers about programs, describing this and other early programs and how they worked on EDSAC. She stayed on in Cambridge to do a PhD on the topic ultimately becoming one of the first people to gain a Computer Science PhD, and probably it was the first PhD about digital computers as we now know them. It built on the work of Computing giants, Alan Turing and Claude Shannon in discussing how programs could efficiently run not just on idealised machines such as Turing Machines, but on real ones like EDSAC. She also wrote more scientific programs for EDSAC, including one to correct pendulum measurements at sea, presumably in part due to her time as a WREN researcher Back in Canada. She also helped design an early programming language, Transcode, and co-wrote a sophisticated compiler for it based on their deep understanding of the hardware. This was because the computer at Toronto, the “Ferranti computer at the University of Toronto” was incredibly tricky to program in its machine code. Worsley could do it but many others struggled. Transcode in effect simulated an easy to program computer running on top of it, based on in idea by John Backus. As a result hundreds of people learnt to program it. Linked to this and starting with her PhD thesis she pioneered the use of programming libraries to make programming easier through her career.

Beatrice Worsley was not the very first person to write a program, or to get a Computing-linked PhD, but she was certainly one of the first, as well as one of the first people to work professionally as a computer scientist. She was certainly a computing pioneer whose programs made history and whose programming research made a solid contribution to the nascent discipline of programming. Computer Science certainly wasn’t a man’s world at the start, and there is no reason why it should be now.

Paul Curzon, Queen Mary University of London

The Proof of Love

A pseudocode poem in a red heart:
Violets are violet
if roses are red and violets are blue
then
Life is sweet
else
I love you — Image by CS4FN

For Valentine’s day we created this card with a pseudocode love poem. But what does it mean? Is it a statement of love or not? Now that Valentines Day is gone and logic and rational thinking are starting to reassert themselves, here is a logical argument of what it means: an informal proof of love.

We are using our own brand of poetic pseudocode here, and what matters is the formal semantics of the language (ie mathematical meaning).

What we will do is simplify the code to code that is mathematically equivalent but far simpler, explaining the semantics as we do. We will by reasoning in a similar way to doing algebra, just replacing equals with equals.

First let’s write the poem out in more program looking notation, making clearer what are statements (actions) and expressions (things that evaluate to a value. In the English reading version we are using the verb TO BE in both ways which confuses things a little.

Let’s make clear the difference between variables (that hold values and values). The colours are all values (data that can be stored) – so we will write them in capitals: RED, BLUE, VIOLET. The flowers are variables (places to store values) so we will leave them as lowercase: violets, roses. Then the title becomes an assignment (written more formally as :=). It sets the value of variable violets to value VIOLET. (We are pedantic and believe the colour of violet flowers is violet not blue!)

What comes after the keyword IF is an expression – it evaluates to a boolean (TRUE value or FALSE value) so is referred to as a boolean expression. You can think of boolean expressions as tests – true or false questions. We will use == to indicate a true/false question about whether two things are the same value.

The other two lines are statements – think of them as print statements that print a message as the action they do.

The algorithm of the poem then is:

violets := VIOLET;
IF ((roses == RED) AND (violets == BLUE))
THEN
    PRINT "Life is Sweet"
ELSE
    PRINT "I love you"

Now let us simplify the algorithm to an equivalent version a step at a time. In the assignment of the first line, the variable violets is set to value VIOLET and then not changed, so we can substitute the value (a colour in uppercase) VIOLET for variable violets (in lowercase) where it appears, and remove the assignment. This gives a simpler version of the algorithm that does exactly the same:

IF ((roses == RED) AND (VIOLET == BLUE))
THEN
    PRINT "Life is Sweet"
ELSE
    PRINT "I love you"

Now in the boolean expression, we have the subexpression

(VIOLET==BLUE)

but these are two different values and this is asking whether they are the same or not. It evaluates to true if they are the same and FALSE if they are different. It is therefore equivalent to FALSE so the whole expression becomes:

(roses==RED) AND FALSE

The original algorithm is equivalent to

IF ((roses == RED) AND FALSE)
THEN
    PRINT "Life is Sweet"
ELSE
    PRINT "I love you"

Now whatever X is a boolean expression (X & FALSE) will always evaluate to FALSE because it needs both to be TRUE for the whole to be TRUE. The whole boolean expression therefore simplifies to FALSE and the algorithm to:

IF (FALSE)
THEN
    PRINT "Life is Sweet"
ELSE
    PRINT "I love you"

Notice how this means it does not matter what colour the roses are at all. Whether roses are red, white, blue or something else, the algorithm result will not be affected.

The semantics of an IF statement is that it evaluates exactly one of its two statements. Where its test (boolean expression) evaluates to TRUE, it executes the first THEN branch (here the Life is Sweet branch) and ignores the other ELSE branch (the I love you branch). Where its test evaluates to FALSE it instead ignores the THEN branch completely and executes the ELSE branch.

Here the test is FALSE, so it ignores the THEN branch and is equivalent to the ELSE branch. The algorithm as a whole is exactly equivalent to the far simpler algorithm:

PRINT "I love you"

Going back to the poem, it is therefore logically completely equivalent to a poem
I Love You

We have given a mathematical proof of love! The idea though is that only computer scientists with a formal semantics (ie maths meaning) of the pseudocode language used would see it!

Lego Computer Science: Programming Creativity

White lego buildings rising from rubble — Image by Paul Curzon taken at Tate Modern London at Olafur Eliasson’s “The cubic structural evolution project” exhibition, 2019.

My absolute favourite example of interactive art is Olafur Eliasson‘s “The cubic structural evolution project” back in 2019 at Tate Modern. It was “just” two piles of standard white Lego bricks piled on two tables (but a tonne of Lego between the two …so a LOT of Lego). Anyone visiting the exhibit was invited to sit down and help create a city by building a building … and it was joyfully creative. Kids and adults mixed together building great architectural wonders, big and small, out of the bricks. Sometimes intentionally, but often accidentally, an existing building was demolished, but that was just an opportunity for new amazing buildings to emerge from the rubble. We visited twice that summer, and each time a totally different city was there that had emerged from this constant evolution of building. On each visit we built something new ourselves to add to the ever changing city.

The exhibit took Lego back to its roots – no instructions, no specific creation to reproduce, just the bare building blocks of creativity. You can still buy generic lego sets of course (if not with the same scope as a tonne of bricks). However, the high profile modern Lego sets are now used to build a specific thing designed by someone else, like a Star Wars Tie fighter, a Death Star, a Ferrari, a parrot or perhaps Notre Dame. This is one form of creativity – you are definitely creating something, and doing so gives you an amazing feeling of accomplishment and well-being. I strongly recommend it and of doing similar activities whether doing a tapestry, or building a jigsaw, or … It is good for your happiness and mental health more generally. But you are creating just by following instructions. In computer science terms, you are acting as a computational agent, following an algorithm that if followed precisely guarantees the same result every time (an exact copy of the lighthouse on the box perhaps…). A computer (with a suitably good robotic arm and vision system) could do it. That is the point of algorithms! They take no thought just an ability to follow instructions precisely: the thing computers are good at.

There is another sense we mean when we talk about creativity though and that was the original Lego idea. You have the bricks. You can build anything. It is down to you. Create something new! According to an exhibition on the history of play I went to early construction kits like the original Lego inspired a whole generation of architects to do completely new things with buildings (if you know your architecture think especially Frank Lloyd Wright whose mother bought him educational blocks called the Froebel Gifts, or perhaps Denys Lasdun – I lived in one of his “Lasdun building” block like buildings for a year in my younger days).

This kind of pure creativity is what being a programmer is about. Not just following instructions to create someone else’s creation, but creating your own totally novel, wondrous things from simple building blocks (and you don’t have to be part of the Lego design team to do it either). That is the lesson that collaboratively emerged in Olafur Eliasson’s exhibit over and over again. Just as the inventor of Lego, Ole Kirk Christiansen, in creating the toy went to yet another level of creativity in doing so, Olafur Eliasson did so to in creating the exhibition. They both created the opportunities for others to be creative.

Programming languages are very much like Lego in this sense. They just provide the building blocks to create any program you want. Learn how to use them and you you can do anything if you have the imagination as well as having built the skill. The different constructs are like different kinds of Lego bricks. Put them together in different ways and you create different things. You can stick with the basics and still build amazing creations even without learning about all the libraries methods that act like specialist bricks designed for specialist purposes. And of course the early Computer Scientists who invented the idea of programming languages were being creative in the way Ole Kirk Christiansen and Olafur Eliasson were, creating the possibility for others. Creating possibilities for you.

The Arts are about pure creativity but so is Computer Science…(and when they are brought together by creative people even more amazing things can be created (by everyone).

Paul Curzon, Queen Mary University of London

Sue Sentance: Teaching the world to program

A figure sprinting: silhouette binary — Image by Gerd Altmann from Pixabay (edited)

How do you learn to program? How do you best teach programming. When the English school curriculum changed, requiring even primary school students to learn programming, suddenly this became an important question for school teachers who had previously not had to even think about it. Teaching is about much more than knowing the subject, or even knowing how to teach. It also needs knowledge and skill in how to teach each specific subject. Many teachers had to learn these new skills often with no background at all. Luckily, Sue Sentance came to the rescue with PRIMM, a simple framework for how to teach programming suitable for schools. She was awarded the BCS Lovelace prize for the work.

If you were a novice wanting to develop maker skills, whether building electronics, making lego, doing origami or knitting, you might start by following instructions created by someone else for a creation of theirs. Many assumed that was a sensible way to teach programming too, but it isn’t. This approach, sometimes called “copy code” where a teacher provides a program, and students type it in, is a very poor way to learn to program. But if you can’t do the obvious, what do you do?

Sue came up with PRIMM as a way to help teachers. It stands for Predict, Run, Investigate, Modify and Make, giving a series of steps a programming lesson should follow.

The teacher still provides programs, but instead of typing the code in line by line the students first read it and try to predict what it does. This follows the way people learn to write – they first read (lots!)

Having made a prediction, the students run the program. (They don’t type it in at all, as there is little point in doing that, but are given the file ready to run), They now act like a scientist and see if their prediction is correct. Perhaps they predict the program prints

Hello World

all on one line. By running the program they find out if they were right or not. If they were then it confirms their understanding. If it doesn’t then this suggests there was something more to understand. If the program instead printed

Hello
World

over two lines, then there is something to work out about what makes a program move to another line. The class discuss the results and compare their predictions with the results. Can they explain why it behaved the way it did?

Next they investigate the program in more depth. The teacher can set a variety of exercises to do this. One very powerful way is stepping through program fragments line by line (doing what in industry is called a code walkthrough and is also called dry running or tracing the code).

Based on the deeper understanding gained by this they then attempt to modify the original program to do something very slightly different – for example, to print

Hello, Paul. 
How are you?

This is more exprementation to check and expand their understanding. By making deliberate changes with specific results in mind, they can now purposefully make sure they really do understand a programming construct. As before, if the program does something different to expected then the reason can be explored and that is used to correct what they thought.

If they have fully understood the code then this should by now be fairly easy.

Finally they make a program of their own. Based on the understanding gained they create a new specific program that uses the new constructs (like how to print a message, get input or make decisions) that they now understand. This program should solve a different problem. For example if they just played with a program containing an if statement, they might now write a simple quiz program, or simulates a vending machine where items cost different amounts. .

Part of the reason that PRIMM has been successful is that it is not only a good way to learnt to program but it gives a clear structure to lessons that can be repeated with each construct to be covered and so makes a natural framework for planning lessons around.

Sue originally developed PRIMM with local schools she was working with in mind, but it works so well, solving a specific problem teachers had everywhere, that it is now used worldwide in countries introducing programming in schools.

Women do not figure greatly in the early history of science and maths just because societal restrictions, prejudices and stereotypes meant few were given the chance. Those who were like Maria Cunitz, showed their contributions could be amazing. It just took the right education, opportunities, and a lot of dedication. That applies to modern computer science too, and as the modern computer scientist, Karen Spärck Jones, responsible for the algorithm behind search engines said: “Computing is too important to be left to men.”

– Paul Curzon, Queen Mary University of London

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Dina St Johnston: Kickstarting a software industry

Back in its early days, after the war, women played a pivotal role in the computing industry, originally as skilled computer operators. Soon they started to be taken on as skilled computer programmers too. The myth that programming is boys thing came much later. Originally it was very much a job for women too. Dina St Johnston was one such early programmer. And she personally went on to kick-start the whole independent UK software industry!

Departure Board Kings Cross showing times, platform, destinations — Image Public Domain from wikimedia

On leaving school, interested in maths, science and machines, she went to work for a metallurgy research company, and in parallel gained a University of London external Maths degree, but eventually moved on to get a job ultimately as a programmer at an early computer manufacturer, Elliot Brothers in 1053. Early software she was involved in writing was very varied, but whatever the application she excelled. For example, she was responsible for writing an in-house payroll program, as well as code for a dedicated direction finding computer of the Royal Navy. The latter was a system that used the direction of radio signals picked up by receivers at different listening stations to work out where the source was (whether friend or foe). She also wrote software for the first computer to be used by a local government, Norwich City Council. She had the kind of attention to detail and logical thinking skills that meant she quickly became an incredibly good programmer, able to write correct code. Bugs for others to find in her code were rare. “Whereas the rest of us tested programs to find the faults, she tested them to demonstrate that they worked.”

Towards the end of the 1960s though she realised there was a big opportunity, a gap in the market, for someone with programming skills and a strong entrepreneurial spirit like her. All UK application software at the time was developed either by computer manufacturers like Elliot Brothers, by service companies selling time on their computers, by consultancy firms or in-house by people working directly for the companies who bought the computers. There was, she saw, potential to create a whole new industry: an applications software industry. What there was a need for, were independent software companies whose purpose was to write bespoke application programs that were just what a client company needed, for any who needed it, big or small. She therefore left Elliot Brothers and founded her own company (named after her maiden name), Vaughan Programming Services, to do just that.

Despite starting out working from her dining room table, it was a big success, working in a lot of different application areas over the subsequent decades, with clients including massive organisations such as the BBC, BAA, Unilever, GEC, the nuclear industry (she wrote software for what is now called Sellafield, then the first ever industrial nuclear power plant), the RAF and British Rail. Part of the reason she made it work was she was a programmer who was “happy to go round a steel works in a hard hat”, She made sure she understood her clients needs in a direct hands-on way.

Eventually, Dina’s company started to specialise in transport information systems and that is where it really made its name…with early work for example on the passenger display boards at London Bridge, but eventually to hundreds of stations, driven from a master timetable system. So next time you are in a train station or airport, looking at the departure board, think of Dina, as it was her company that wrote the code driving the forerunner of the display you are looking at.

More than that though, the whole idea of a separate software industry to create whatever programs were needed for whoever needed them, started with her. If you are a girl wondering about whether a software industry job is for you, as she showed, there is absolutely no reason why it should not be. Dina excelled, so can you.

by Paul Curzon, Queen Mary University of London

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Peter Landin: Elegance from Logic

Celebrating LGBTQ+ Greats

Thousands of programming languages have been invented in the many decades since the first. But what makes a good language? A key idea behind language design is that they should make it easy to write complex algorithms in simple and elegant ways. It turns out that logic is key to that. Through his work on programming language design, Peter Landin as much as anyone, promoted both elegance and the linked importance of logic in programming.

Pride flag with lambda x.x (identity) superimposed — Pride image by Image by Pete Linforth from Pixabay. Composite by PC

Peter was an eminent Computer Scientist who made major contributions to the theory of programming languages and especially their link to logic. However, he also made his mark in his stand against war, and support of the nascent LGBTQ+ community in the 1970s as a member of the Gay Liberation Front. He helped reinvigorate the annual Gay Pride marches as a result of turning his house into a gay commune where plans were made. It’s as a result of his activism as much as his computer science that an archive of his papers has been created in the Oxford Bodleian Library.

However, his impact on computer science was massive. He was part of a group of computing pioneers aiming to make programming computers easier, and in particular to move away from each manufacturer having a special programming language to program their machines. That approach meant that programs had to be rewritten to work on each different machine, which was a ridiculous waste of effort! Peter’s original contribution to programming languages was as part of the team who developed the programming language, ALGOL which most modern programming languages owe a debt to.

ALGOL included the idea of recursion, allowing a programmer to write procedures and functions that call themselves. This is a very mathematically elegant way to code repetition in an algorithm (the code of the function is executed each time it calls itself). You can get an idea of what recursion is about by standing between two mirrors. You see repeated versions of your reflection, each one smaller than the last. Recursion does that with problem solving. To solve a problem convert it to a similar but smaller version of the same problem (the first reflection). How do you solve that smaller problem? In the same way, as a smaller version of the same problem (the second reflection)… You keep solving those similar but smaller problems in the same way until eventually the problem is small enough to be trivial and so solved. For example, you can program a factorial method (multiplying all numbers from 1 to n together),in this way. You write that to compute factorial of a number, n, it just calls itself and computes the factorial of (n-1). It just multiply that result by n to get the answer. In addition you just need a trivial case eg that factorial of 1 is just 1.

factorial (1) = 1
factorial (n) = n * factorial (n-1)

Peter was an enthusiastic and inspirational teacher and taught ALGOL to others. This included teaching one of the other, then young but soon to be great, pioneers of Programming Theory, Tony Hoare. Learning about recursion led Hoare to work out a way, using recursion, to finally explain the idea that made his name in a simple and elegant way: the fast sorting algorithm he invented called Quicksort. The ideas included in ALGOL had started to prove their worth.

The idea of including recursion in a programming language was part of the foundation for the idea of functional programming languages. They are mathematically pure languages that use recursion as the way to repeat instructions. The mathematical purity makes them much easier to understand and so write correct programs in. Peter ran with the idea of programming in this way. He showed the power that could be derived from the fact that it was closely linked to a kind of logic called the Lambda Calculus, invented by Alonso Church. The Lambda Calculus is a logic built around mathematical functions. One way to think about it is that it is a very simple and pure way to describe in logic what it means to be a mathematical function – as something that takes arguments and does computation on them to give results. This Church showed was a way to define all possible computation just as Turing’s Turing machine is. It provides a simple way to express anything that can be computed.

Peter showed that the Lambda Calculus could be used as a way to define programming languages: to define their “semantics” (and so make the meaning of any program precise).

Having such a precise definition or “semantics” meant that once a program was written it would be sure to behave the same way whatever actual computer it ran on. This was a massive step forward. To make a new programming language useful you had to write compilers for it: translators that convert a program written in the language to a low level one that runs on a specific machine. Programming languages were generally defined by the compiler up till then and it was the compiler that determined what a program did. If you were writing a compiler for a new machine you had to make sure it matched what the original compiler did in all situations … which is very hard to do.

So having a formal semantics, a mathematical description of what a compiler should do, really makes a difference. It means anyone developing a new compiler for a different machines can ensure the compiler matches that semantics. Ultimately, all compilers behave the same way and so one program running on two different manufacturer’s machines are guaranteed to behave the same way in all situations too.

Peter went on to invent the programming language ISWIM to illustrate some of his ideas about the way to design and define a programming language. ISWIM stands for “If you See What I Mean”. A key contribution of ISWIM was that the meaning of the language was precisely defined in logic following his theoretical work. The joke of the name meant it was logic that showed what he meant, very precisely! ISWIM allowed for recursive functions, but also allowed recursion in the definition of data structures. For example, a List is built from a List with a new node on the end. A Tree is built from two trees forming the left and right branches of a new node. They are defined in terms of themselves so are recursive.

Building on his ideas around functional programming, Peter also invented something he called the SECD machine (named after its components: a Stack, Environment, Control and Dump). It effectively implements the Lambda calculus itself as though it is a programming language.ISWIM provided a very simple but useful general-purpose low level language. It opened up a much easier way to write compilers for functional programming languages for different machines. Just one program needed to be written that compiled the language into SECD. Then you had a much simpler job of writing a compiler to convert from the low level SECD language to the low level assembly language of each actual computer. Even better, once written, that low level SECD compiler could be used for different functional programming languages on a single machine. In SECD, Peter also solved a flaw in ALGOL that prevented functions being fully treated as data. Functions as Data is a powerful feature of the best modern programming languages. It was the SECD design that first provided a solution. It provided a mechanism that allowed languages to pass functions as arguments and return them as results just as you could do with any other kind of data without problem.

In the later part of his life Peter focussed much more on his work supporting the LGBTQ+ community having decided that Computer Science was not doing the good for humanity he once hoped. Instead, he thought it was just supporting companies making profit, ahead of the welfare of people. He decided that he could do more good as part of the LGBTQ+ community. Since his death there has been an acceleration in the massing of wealth by technology companies, whereas support for diversity has made a massive difference for good, so in that he was prescient. His contributions have certainly, though, provided a foundation for better software, that has changed the way we live in many ways for the better. Because of his work they are less likely to cause harm because of programming mistakes, for example, so in that at least he has done a great deal of good.

by Paul Curzon, Queen Mary University of London

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Cooking up computer style

Spaghetti in a jar looking down from above so looks like a ball of spikes surrounded by ingredients below — Pasta image by Gentina Bintang Danurendra from Pixabay

Using clever computer vision techniques it’s now possible for your ingredients to tell you how they should be cooked in a kitchen. The system uses cameras and projectors to first recognise the ingredients on the chopping board, for example the size, shape and species of fish you are using. Then the system projects a cutting line on the fish to show you how to prepare it, and a speech bubble telling you how long it should be cooked for and suggesting ways it can be served. In the future these cooking support systems could take some of the strain from mealtimes. At least it will help to make us all better cooks, and perhaps with an added pinch of artificial intelligence we can all become more like Jamie Oliver.

Jo Brodie, Queen Mary University of London

Working in Computer Science: An Autistic Perspective (Part 2)

by Daniel Gill, Queen Mary University of London

5 paper planes going in the same straight line with one red one on a different curved path — Image by Rosy / Bad Homburg / Germany from Pixabay

In Part 1, we spoke to Stephen Parry about his experiences of working in computer science as an autistic person. In this second part, we discuss with him his change from this stressful working environment to teaching A-Level computer science, and how rewarding he has found teaching as a career.

Following a tough experience at his last workplace, Stephen decided he needed a change. He used this as a prompt to start thinking about alternatives:

“[When] things aren’t working out, you need to take a step back and work out what the problem is before it becomes really serious. I still hadn’t had a diagnosis by that point, so things probably would have gone very differently if I had, but I took a step back after that job. I was fed up of being stressed, trying to help people [who] have already got far too much money make more money, and then being told that I was being paid too much. That was kind of my experience from my last employer. And so, I decided that I wanted to get stressed for something worthwhile instead: my mum had been a teacher, so I’d always had it in mind as a possibility.”

Stephen did, of course, have some reservations financially.

“I’d always thought it was financially too much of a step down, which a lot of people in the computer science industry will find out. I did take pretty much a 50% pay cut to become a trainee teacher: in fact, worse than that. But it’s amazing when you want to do something, what differences that makes! And there’s plenty of people out there that will sacrifice a salary to start their own business, and all the power to them. But people don’t think [like this] when they’re thinking about becoming a teacher, for example, which I think is wrong. Yes, teachers should be better paid than they are, but they’re never going to be as well paid as programmers or team leaders or whatever in industry. You shouldn’t expect that to be the case, because we’re public servants at the end of the day, and we’re here for the job as much as we are for the money. We want our roof over our head, but we’re not looking to get mega rich. We’re there to make a difference.”

While considering this change of profession, Stephen reflected on his existing skills, and whether they fit the role of teaching. With support from his wife and a DWP (Department for Work and Pensions) work coach, he was reminded of his ability to “explain technical stuff to [people] in a language [they] could understand.”

Stephen had the opportunity to get his first experience of teaching as a classroom volunteer. Alongside a qualified teacher, he was able to lead a lesson – which he found particularly exciting:

“It was a bit like being on drugs. It was exhilarating. I sort of sat there thinking, you know, this is something I really want to do.”

It’s around this time that Stephen got his autism diagnosis. For autistic people who receive a diagnosis, there can be a lot of mixed emotions. For some, it can be a huge sense of relief – finally understanding who they are, and how that has affected their actions and behaviours throughout their life. And for others it can come as a shock [EXTERNAL]. For Stephen, this news meant reconsidering his choice of a career in teaching:

“I had to stop and think, because, when you get your diagnosis for the first time as an adult or as an older person anyway, it does make you stop and think about who you are. It does somewhat challenge your sense of self.”

“It kind of turns your world a bit on its head. So, it did knock me a fair bit. It did knock my sense of self. But then I began to sort of put pieces together and realise just what an impact it had on my working life up until that point. And then the question came across, can I still do the job? Am I going to be able to teach? Is it really an appropriate course of action to take? I didn’t get the answer straight away, but certainly over the months and the years, I came to the conclusion it was a bit like when I talk to students who say, ‘should I do computer science?’ And I say to them, ‘well, can you program?’ ‘Yes.’ ‘Yes, you do need to do computer science.’ It’s not just you can if you want to – it’s a ‘you should do CS.’ It’s the same thing if you’re on the spectrum, or you’re in another minority, a significant minority like that, where you’re able to engage with a teaching role: you should do.”

Stephen did go on to complete teacher training, and has now worked as an A-Level and GCSE teacher for 15 years. He still benefits from his time in work, however, as he is able to enlighten future computer science students about the workplace:

“Well, you know the experiences I’ve had as a person in industry, where else are the students going to be exposed to that second-hand? Hopefully they’ll be exposed to it first-hand, but, if I can give them a leg up, and an introduction to that, being forewarned and forearmed and all that, then that’s what should happen.

“I do spend a chunk of my teaching explaining what it’s like working in industry: explaining the difficulties of dealing with management; (1) when you think you know better, you might not know better – you don’t know yet; (2) if you do, keep your mouth shut until the problem occurs, then offer a positive and constructive solution. Hopefully they won’t say ‘why didn’t you say something sooner?’ If they do, just say, ‘Well, I wasn’t sure it was my place to, I’m only new.’”

Teaching is famously a very rewarding career path, and this is no different for Stephen. In our discussion, he outlined a few things that he enjoyed about teaching:

“It’s [a] situation where what you do, lives on. If I drop dead tomorrow, all that stuff that I learned about; how different procedure calls work or whatever, could potentially just disappear into the ether. But because I’ve shared it with all my students, they will hopefully make use of it, and it will carry on. And it’s a way of having a legacy, which I think we all want, to a certain extent.”

“Young people nowadays, particularly those of us on the spectrum, but it applies to all, the world does everything possible at the moment to destroy most young people’s self-esteem. Really, really knock people flat. Society is set up that way. Our social media is set up that way. Our traditional media is set up that way. It’s all about making people feel pretty useless, pretty rubbish in the hope, in some cases, of selling them something that will make them feel better, which never does, or in other cases, just make someone else feel good by making someone else feel small. It’s kind of the more the darker side of humanity coming out that teaching is an opportunity to counter that. If you can make a young person feel good about themselves; if you can help them conquer something that they’re not able to do; if you could help them realise that it doesn’t matter if they can’t, they’re still just as important and wonderful and valuable as a human being.”

“The extracurricular activities that I do: ‘Exploring the Christian faith’ here at college. And part of that is helping people [to] find a spiritual worth they didn’t realise they had. So, you get that opportunity as a teacher, which a bus driver doesn’t get, for example. Bus drivers are very useful – they do a wonderful job. But once they’ve dropped you off, that’s the end of the job. Sometimes we’re a bit like bus drivers as teachers. You go out the door with your grades, and that’s fine, but then some people keep coming back. I haven’t spotted the existential elastic yet, but it’s there somewhere. I’m sure I didn’t attach it. But that is another one of the things that motivates me to be a teacher.”

Stephen Parry now teaches at a sixth-form college near Sheffield. The author would like to thank Stephen for taking time out of his busy schedule to take part in this interview.

Magazines …

Issue 29 – Diversity

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This blog is funded by EPSRC on research agreement EP/W033615/1.

Working in Computer Science: An Autistic Perspective (Part 1)

by Daniel Gill, Queen Mary University of London

Autism is a condition with many associated challenges, but for some people it presents some benefits. This distinction is greatly apparent in the workplace, where autistic people often find it difficult to get along with others (and their boss), and to complete the work that has been set for them. It’s not all negatives though: many autistic people find the work in which they thrive, and given the right circumstances and support, an autistic person is able to succeed in such an environment.

We often rightly hear about the greats in computer science; Ada Lovelace, Alan Turing, Lynn Conway (who sadly passed away earlier this month) – but let us not forget the incredible teams of computer scientists working around the clock; maintaining the Internet, building the software we use every day, and teaching the next generation. For this two-part article, I have spoken with Stephen Parry, an autistic computer scientist, who, after working in industry for 20 years, now teaches the subject in a sixth-form college in Sheffield. His autistic traits have caused him challenges throughout his career, but this is not a unique experience – many autistic computer scientists also face the same challenges.

Stephen’s experience with programming started at the age of 14, after being introduced to computers at a curriculum enrichment course. He decided against taking a then “really rubbish” O-Level (now GCSEs) Computer Science course, and the existence of the accompanying A-Level “just didn’t come up on my radar”. He was, however, able to take home the college’s sole RML 380Z for the summer, a powerful computer for the time, with which, he was able to continue to practice programming.

When it came time to go to university, he opted first to study chemistry, a subject he had been studying at A-Level. Though after a short amount of time he realised that he wasn’t as interested in chemistry as he first thought – so he decided to switch to computer science. In our discussions, he praised the computer science course at the University of Sheffield:

“[I] really enjoyed [the course] and got on well with it. So, I kind of drifted into it as far as doing it seriously is concerned. But it’s been a hobby of mine since I was 14 years old, and once I was on the degree, I mean, the degree at Sheffield was a bit like a sweetie shop. It really was absolutely brilliant. We did all kinds of weird and wonderful stuff, all of it [was] really interesting and engaging, and the kind of stuff that you wouldn’t get by either playing around on your own or going out into [the] workplace. As I’ve always said, that’s what a university should be. It should expose you to the kind of stuff that you can’t get anywhere else, the stuff that employers haven’t realised they need yet.”

Of autistic people who go to university, research shows they are much more likely the general population to pick STEM subjects [EXTERNAL]. For lots of autistic people, the clear logical and fundamental understanding behind scientific subjects is a great motivator. Stephen describes how this is something that appeals to him.

“[What] I enjoy about computer science is how it teaches you how the computer actually works at a fundamental level. So, you’re not just playing with a black box anymore – it’s something you understand. And especially for someone on the [autism] spectrum, that’s a really important aspect of anything you do. You want to understand how things work. If you’re working with something, and you don’t understand how it works, usually it’s not very satisfying and kind of frustrating. Whereas, if you understand the principles going on inside of it then, when you know you’ve got it, it kind of unlocks it for you.”

While autistic traits often result in challenges for autistic people, there are some which can present a benefit to someone in computer science. A previous CS4FN article described how positive traits like ‘attention to detail’ and ‘resilience and determination’ link well to programming. Stephen agrees that these traits can help him to solve problems:

“If I get focused on a problem, the hyper focus kicks in, and I will just keep plugging away until it’s done, fixed or otherwise overcome. I know it’s both a benefit and hazard – it’s a double edged sword, but at the same time, you know you have to have that attention to detail and that, to put it another way, sheer bloody mindedness to be determined that you’re going to make it work, or you’re going to understand how it works, and that does come definitely from the [autism] spectrum.”

Although he enjoyed the content greatly, Stephen had a rocky degree, both in and out of lectures. However, some unexpected benefits arose from being at university; he both found faith and met his future wife. These became essential pillars of support, as he prepared to enter the workforce. This he did, working both as a programmer and in a variety of IT admin and technical support roles.

About 78% of autistic adults are currently out of work [EXTERNAL] (compared with 20% in the general population). This is, in part, reflective of the fact that some autistic people are unable to work because of their condition. But for many others, despite wanting to work, they cannot because they do not get the support they need (and are legally entitled to) within their workplace.

At this time, however, Stephen wasn’t aware of his condition, only receiving his diagnosis in his 40s. He described how this transition from university to work was very challenging.

“I moved into my first job, and I found it very, very difficult because I didn’t know that I’ve got this sort of difference – this different way my brain works that affects everything that you do. I didn’t know when I came across difficulties, it was difficult to understand why, at least to an extent, for me and for other people, it was deeply frustrating. I mean, speak to just about every manager I’ve ever had, and the same sort of pattern tends to come out. Most of them recognised that I was very difficult to manage because I found myself very difficult to manage. But time management is an issue with everything – trying to complete tasks to any kind of schedule, trying to plan anything. Oh, my days, when I hear the word SMART. [It’s an] acronym [meaning] specific, measurable, achievable, realistic and time specific. I hear that, and it just it makes me feel physically ill sometimes, because I cannot. I cannot SMART plan.”

However, during his time in work, he had some good luck. Despite the challenges associated with autism, some managers took advantage of the positive skills that he brings to the table:

“I found that a real challenge, interpersonally speaking, things like emotional regulation and stuff like that, which I struggle with, and I hate communicating on the phone and various other things, make me not the most promising employee. But the managers that I’ve had over the years that have valued me the most are the ones who recognised the other side of the coin, which is [that] over the years, I have absorbed so much knowledge about computer science and there are very [few] problems that you can come across that I don’t have some kind of insight into.”

This confidence in a range of areas in computer science is also a result of Stephen’s ability to link lots of areas and experiences together, a positive skill that some autistic people have:

“I found that with the mixture of different job roles I did, i.e. programming, support, network admin and database admin, my autism helped me form synergies between the different roles, allowing me to form links and crossover knowledge between the different areas. So, for example, as a support person with programming experience, I had insight into why the software I was helping the user with did not work as desired (e.g. the shortcuts or mistakes the programmer had likely made) and how maybe to persuade it to work. As a programmer with support experience, you had empathy with the user and what might give them a better UX, as well as how they might abuse the software. All this crossover, also set me up for being able to teach confidently on a huge range of aspects of CS.”

For autistic students who are planning on working in a computer science career, he has this to say:

“As an autistic person, and I would say this to anybody with [autism], you need to cultivate the part of you that really wants to get on well with people and wants to be able to care about people and understand people. Neurotypical people get that ability out of the box, and some of them take it for granted. I tend to find that the autistic people who actually find that they can understand people, that they work at it until they can, [are] often more conscientious as a result. And I think it’s important that if you’re an autistic person, to learn how to be positive about people and affirm people, and interact with them in positive ways, because it can make you a more caring and more valuable human being as a as a result.”

“Look for jobs where you can really be an asset, where your neurodiversity is the asset to what you’re trying to do, but at the same time, don’t be afraid to try to, and learn how to engage with people. Although it’s harder, it’s often more rewarding as a result.”

After working in industry for 20 years, the last half as which as a contractor, Stephen decided to take a considerable pay drop and become a computer science teacher. In the second part of this article, we will continue our conversation and find out what led him to choose a career change to teaching.

Magazines …

Issue 29 – Diversity

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This blog is funded by EPSRC on research agreement EP/W033615/1.

Double or nothing: an extra copy of your software, just in case

Ariane 5 on the launchpad — Ariane 5 on the launch pad. Photo Credit: (NASA/Chris Gunn) Public Domain via Wikimedia Commons.

If you spent billions of dollars on a gadget you’d probably like it to last more than a minute before it blows up. That’s what happened to a European Space Agency rocket. How do you make sure the worst doesn’t happen to you? How do you make machines reliable?

A powerful way to improve reliability is to use redundancy: double things up. A plane with four engines can keep flying if one fails. Worried about a flat tyre? You carry a spare in the boot. These situations are about making physical parts reliable. Most machines are a combination of hardware and software though. What about software redundancy?

You can have spare copies of software too. Rather than a single version of a program you can have several copies running on different machines. If one program goes wrong another can take over. It would be nice if it was that simple, but software is different to hardware. Two identical programs will fail in the same way at the same time: they are both following the same instructions so if one goes wrong the other will too. That was vividly shown by the maiden flight of the Ariane 5 rocket. Less than 40 seconds from launch things went wrong. The problem was to do with a big number that needed 64 bits of storage space to hold it. The program’s instructions moved it to a storage place with only 16 bits. With not enough space, the number was mangled to fit. That led to calculations by its guidance system going wrong. The rocket veered off course and exploded. The program was duplicated, but both versions were the same so both agreed on the same wrong answers. Seven billion dollars went up in smoke.

Can you get round this? One solution is to get different teams to write programs to do the same thing. The separate teams may make mistakes but surely they won’t all get the same thing wrong! Run them on different machines and let them vote on what to do. Then as long as more than half agree on the right answer the system as a whole will do the right thing. That’s the theory anyway. Unfortunately in practice it doesn’t always work. Nancy Leveson, an expert in software safety from MIT, ran an experiment where different programmers were given programs to write. She found they wrote code that gave the same wrong answers. Even if it had used independently written redundant code it’s still possible Ariane 5 would have exploded.

Redundancy is a big help but it can’t guarantee software works correctly. When designing systems to be highly reliable you have to assume things will still go wrong. You must still have ways to check for problems and to deal with them so that a mistake (whether by human or machine) won’t turn into a disaster.

Paul Curzon, Queen Mary University of London

Related Magazine …

CS4FN Issue 17 – Machines making medicine safer

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