Category Archives: Software Development

Women’s Day Intuition

The first thing I did yesterday, on International Women’s Day 2017, was retweet a picture of Margaret Hamilton, allegedly the first person in the world to have the job title ‘Software Engineer’. The tweet claimed the pile of printout she was standing beside, as tall as her, was all the tweets asking “Why isn’t there an International Men’s Day?” (There is. It’s November 19th, the first day of snowflake season.) The listings were actually the source code which her team wrote to make the Apollo moon mission possible. She was the first virtual woman on the Moon.

I followed up with a link to a graph showing the disastrous decline of women working in software development since 1985, by way of an explanation of why equal opportunities aren’t yet a done deal. I immediately received a reply from a man, saying there had been plenty of advances in computer hardware and software since 1985, so perhaps that wasn’t a coincidence. This post is dedicated to him.

I believe that the decade 1975 – 1985, when the number of women in computing was still growing fast, was the most productive since the first, starting in the late 1830s, when Dame Ada Lovelace made up precisely 50% of the computer software workforce worldwide. It also happens to approximately coincide with the first time I encountered computing, in about 1974 and stopped writing software in about 1986.

1975 – 1985:
As I entered: Punched cards then a teletype, connected to a 24-bit ICL 1900-series mainframe via 300 Baud accoustic coupler and phone line. A trendy new teaching language called BASIC, complete with GOTOs.

As I left: Terminals containing a ‘microprocessor’, screen addressable via ANSI escape sequences or bit-mapped graphics terminals, connected to 32-bit super-minis, enabling ‘design’. I used a programming language-agnostic environment with a standard run-time library and a symbolic debugger. BBC Micros were in schools. The X windowing system was about to standardise graphics. Unix and ‘C’ were breaking out of the universities along with Free and Open culture, functional and declarative programming and AI. The danger of the limits of physics and the need for parallelism loomed out of the mist.

So, what was this remarkable progress in the 30 years from 1986 to 2016?

Good:

Parallel processing research provided Communicating Sequential Processes and the Inmos Transputer.
Declarative, non-functional languages that led to ‘expert systems’. Lower expectations got AI moving.
Functional languages got immutable data.
Scripting languages like Python & Ruby for Rails, leading to the death of BASIC in schools.
Wider access to the Internet.
The read-only Web.
The idea of social media.
Lean and agile thinking. The decline of the software project religion.
The GNU GPL and Linux.
Open, distributed platforms like git, free from service monopolies.
The Raspberry Pi and computer science in schools

Only looked good:

The rise of PCs to under-cut Unix workstations and break the Data Processing department control. Microsoft took control instead.
Reduced Instruction Set Computers were invented, providing us with a free 30 year window to work out the problem of parallelism but meaning we didn’t bother.
In 1980, Alan Kay had invented Smalltalk and the Object Oriented paradigm of computing, allowing complex real-world objects to be simulated and everything else to be modelled as though it was a simulation of objects, even if you had to invent them. Smalltalk did no great harm but in 1983 Bjarne Stroustrup left the lab door open and C++ escaped into the wild. By 1985, objects had become uncontrollable. They were EVERYWHERE.
Software Engineering. Because writing software is exactly like building a house, despite the lack of gravity.
Java, a mutant C++, forms the largely unrelated brand-hybrid JavaScript.
Microsoft re-invents DEC’s VMS and Sun’s Java, as 32-bit Windows NT, .NET and C# then destroys all the evidence.
The reality of social media.
The writeable Web.
Multi-core processors for speed (don’t panic, functions can save us.)

Why did women stop seeing computing as a sensible career choice in 1985 when “mine is bigger than yours” PCs arrived and reconsider when everyone at school uses the same Raspberry Pi and multi-tasking is becoming important again? Probably that famous ‘female intuition’. They can see the world of computing needs real functioning humans again.

Change Time

After some time trying to think about almost nothing, the last 24 hours have been an alarm call. As others come out of hibernation too, they post interesting stuff and Radio 4 provoked me with a discussion on facts and truth. Now Marc Cooper is at it, with difficult  links about computation and I’m all on Edge https://www.edge.org/response-detail/26733
Before I read about “discrete tensor networks”, I need to write down my own ideas about time, so I will know in the future what I thought, before my mind was changed.

I am ill-equipped for this task, having only 1 term of university maths to my name so I intend to talk in vague, abstract terms that are hard to argue with.

Much of physics is very dependent on Time, like almost all of computer science and business management theory. You can’t have change without time, it seems. Einstein talked about space-time, mostly in the language of mathematics. I can just about order a beer in math(s) but I can’t hold a whole conversation. I know what the first 3 dimensions are: left-right, up-down and back-forward. My personal model of the 4th dimension is that same space in continuous state-change through time. There are a few things I’m not happy about:

  • There is no evidence that time is either continuous or constant.
  • We only have evidence of time being a one-way dimension.
  • What the heck does ‘continous state-change’ mean? Is state a particle or a wave? Make your mind up, physics!
  • There’s that troubling many-worlds interpretation of the universal ‘WAVE’function (which I don’t understand either) which says that everything that might have happened did, in other universes. I don’t like this. Yes, that’s my entire justification – I don’t like the conclusion of a thought process I don’t even understand. It doesn’t feel right.

I’ve been learning about the functional programming language Clojure which does not ‘mutate (change) state’. It doesn’t have ‘variables’ like the more common imperative languages such as FORTRAN, BASIC, C, Java or Python. In Clojure, data flows through functions and is transformed from one form to another on the way. It is basically magic. In a pure functional program, no state is changed. State-change is called a “side-effect”. Sadly, side-effects are required to make a program do anything useful in the real world. Arguably, the purest magic is encapsulated in the world of mathematics and the physical world is a messy place that breaks things.

Clojure models time. It does not model the real world by replacing the current value in a variable and throwing the old value away but by chaining a new value onto the end of a list of all previous values.

Now let us extend this idea ‘slightly’ in a small thought-experiment, to a 3-D network of every particle state in the universe.

Space-time now has 2 regions:

  1. The past – all historic states of those particles as a theoretical chain of events
  2. The future – all possible future states of the universe; effectively an infinity of all possible future universes that could exist, starting from now.

Which brings us to what I mean by ‘now’ – a moving wave at the interface between the past and the future, annihilating possible future universes. Time becomes a consequence of the computation of the next set of states and the reason for it being a one-way street becomes obvious: the universe burned its bridges. Unless the universe kept a list, or we do, the past has gone. Time doesn’t need to be constant in different parts of the universe, unless the universe state ticks are synchronous but it seems likely to be resistant to discontinuities in the moving surface. I imagine a fishing net, pulled by current events.

It’s just an idea. Maybe you can’t have Time without change.

[ Please tell me if this isn’t an original idea, as I’m not very well read.
I made it up myself but I’m probably not the first. ]

A Functional Mindset

When I started learning Clojure, I thought I knew what functional programming was but I’ve learned that the functional paradigm is now more than I expected.

Everyone agrees that it’s a computational model based on evaluation of mathematical functions, which return values. This is generally contrasted with imperative programming languages such as FORTRAN, C, JavaScript or Python, which are also procedural and some of which are object-oriented but may make functional coding possible, in a hybrid style. I wouldn’t recommend learning functional concepts in a language that gives you short-cuts to stray back  to more familiar territory.

Clojure is a member of the Lisp family, first specified in 1958. The unusual feature of Lisps is their homoiconicity – code and data are the same thing. Learning Clojure has informed my thinking about business process change.

Some modern, functional languages such as Clojure use immutable data whenever possible, to eliminate side-effects. This allows better use of multi-core processors but requires a complete change in thinking, as well as programming style. ‘Variables’ are replaced by fixed ‘values’, so loops have to be replaced by recursive functions. New data can be created but it doesn’t replace old data. Yesterday’s “today’s date” isn’t automatically wiped when we decide today has happened.

Objects with their methods and local data were designed for simulating the current state of real-world objects by changing (mutating) object data state. The object model, like relational databases, has no inbuilt representation of time. Functional programming splits these objects back into separate functions and data structures and because values can’t change, they may be transformed by flowing through networks of functions, some recursive, to keep doing something until a condition is satisfied. Eventually, code must have a side effect, to tell us the answer.

Rather than computation being a conditional to-do list with data being moved between boxes, it becomes a flow of data through a network of ‘computing machines’; and the data and machines can be transformed into each other.

I hear that map, reduce & filter data transformation functions will change my world again.

Becoming Functional

I’ve been playing with the idea of doing some functional programming for a while now. I’ve been trying to learn and paddling around in the shallows but this week I dived right in the emacs/CIDER pool. I was aware of some dangers lurking beneath the surface: recursion, immutable data structures and the functional holy trinity of map, reduce & filter, so I came up with some ideas to face my fears. I’ve also realised my maths has got rusty so: Some of That Too.

  1. I’ve ‘done recursion’ before but I thought I’d read that my chosen weapon Clojure didn’t do tail-end recursion. This isn’t true. What it can’t do is automatic optimisation of tail-end  recursion, to stop it blowing the stack after a few thousand iterations but Clojure has a ‘recur’ expression to manually signal tail recursion and fix that. I knocked off the programme in a couple of hours and went to bed happy. My code was happily printing the first n numbers of the Fibonacci sequence but a day later I still couldn’t get it the return the numbers as a sequence.
  2. I was finding out about immutable data the hard way. You can’t build up an immutable vector, 1 element at a time. You get to keep the empty vector you created first. It’s a big mind-set change to not have variables that can vary. In my next post, I’ll try to say what I’ve learned. On this occasion it was lazy sequences.
  3. I mentioned the Algorave in my last post. I only found out about that because of an idea I had for improving my theoretical understanding of music. I realised that I could write, for example, a function that would return the 1st, 3rd and 5th notes in a major scale, using a map function.While working the theory out, I found out that Lisps are already popular in the live-coding world.
  4. At Algorave, I was inspired by the live-coded graphics to try automatically generating some graphics too, to work out the maths of mapping triangular grids onto Cartesian co-ordinates. I need that for another idea.

Three basic working programmes in about a week. They aren’t ‘finished’ but is software ever? They have delivered value via increased Clue.

Lispbian Pi. A Lambda Delta.

I’m conflicted. Part of me says that ‘us old timers’ shouldn’t assume ‘the way things were when we were kids’ were better but we know the Raspberry Pi was an attempt to recapture the spirit of the BBC Micro Model B and that seems to have gone quite well. I got a Pi 2 and I’ve worked out that it is more powerful than the first computer I worked on, a DEC VAX-11/780 which supported about 16 terminals, most used for teaching college level computing. Having that machine to myself would have been an unimaginable amount of processing power for one developer. Banks ran their financial modelling software on boxes like that. So why does the Pi feel so slow? We wasted our gains on GUI fluff.

When I started computing you learned just enough of the command language to get going. So, that’s bash on a pi. Then an editor. For reasons that should become obvious, let us choose emacs. When I first used the VAX/VMS operating system, it didn’t have command line editing. If you made an error, you typed it all again. Getting the facility to press up-arrow, edit the command and re-execute it was a big advance. We should keep it. Bash has that, using a sub-set of the emacs keys, so that’s a way into emacs.

The next big improvements I remember were X windowing and symbolic debugging. We got debugging first but it became far more powerful with multiple terminal windows. The GUI was OK, I guess but DEC didn’t give us many free toys so the main advantage to a developer was having lots of terminal windows. emacs can do that, without the overhead of X.

When I decided to re-learn coding a while back, I got my shortlist of languages down to Python, Java and JavaScript but picked Python because I was already learning a new language and the Object paradigm, so I didn’t want to have to learn web at the same time. I heard about the modern Lisp dialect Clojure and changed horses mid-stream. I’m convinced by the argument that functions and immutability can save the universe from the parallel dimension.

Last night I deep-dived into emacs and found myself in an editor session with 4 windows. Why do I need more than that to learn about computation and data transformation? This guy seems to have come to a similar conclusion http://hackaday.com/2015/09/23/old-lisp-languaged-used-for-new-raspberry-pi-os/ I’ve also wondered whether a purely functional OS might make Sun’s ‘the network is the computer’ dream a little easier. emacs is written in Lisp.

I think a dedicated Lisp machine may be a step too far back. How would you browse in the world-wide hypertext library when you got stuck? But a Linux with bash, emacs, the Java Virtual Machine and libraries, Clojure via Leiningen and Cider to plug everything together might make a fine Lispbian Pi! Is all this chrome and leather trim completely necessary in the engine compartment?

It is unfortunate that the Raspbian upgrade left Leiningen broken.

The Unvexing

This post comes to you courtesy of Graham Lee at: http://www.sicpers.info/2016/11/the-vexing-problems-in-programming/ who reminded me about Value. We agilists (people who believe in agile software development) talk about value a lot but haven’t  agreed on a consistent definition of the word. As an illustration of two of the options:

“The value of this car is £9,500.” Is that to a seller or a buyer? Unless there is a difference, no trade will take place. Or is it a market rate? The long acquisition dance between Yahoo! and Google makes an interesting case study. This is: a value. A ‘fact’, right or wrong. It is the kind of thing developers in imperative programming languages put into variables and mutate but pure functional programmers squirrel away for ever, to embarrass themselves at their past Wrongness.

In contrast, “This car cost £9,500 pounds. I think that was quite good value but the model that costs £1,000 more is even better value.”, is a relative benefit:cost calculation, yet the manufacturer may market a ‘value’ model, which is just cheap. This is: a value judgement. An explicit or implicit comparison relative to something else, followed by a decision. It is a computation.

When Graham says, the most vexing problem of software product  developers is their inability to “compare the expected value of their work to the expected cost of the work.”, I think he means  ‘business benefit of their work’, and cost normally equates closely to development time. All the customer really wants to know is: “Is this the best investment I could make now?”

Graham goes on to say that we are very bad at estimating how long something will take. This is true but we are much better at estimating small jobs accurately than large ones.  Uncertainty increases exponentially with length of sequence of actions, to slightly corrupt Shannon’s Information Theory. This is why the Fibonacci sequence is often used as a sizing tool.

Agility accepts this reality. It addresses the list of things the customer currently wants, in highest benefit:cost ratio order (guessed by a business domain expert, based on guesses by an agile develooment team.) It doesn’t yet know whether the ‘whole job’ is worth doing. It decides only whether to risk the next small, cheap step and keeps doing that, as long as the ‘value’ is Good Enough. While value is high and risk is low enough, keep going.

A journey of any length starts with the first step, so why worry about whether or not it is going to be 1000 Miles? The hard part is to make it a journey, rather than simply wandering about, lost.

Then there are: our values. Our personal decisions about what matters most to us. Do we go home to read our children a bedtime story or work late and win that promotion so they have greater financial security in the future? What do we really care about and what are we willing to pay for it? This too is relative. Politics is the art of persuading you to modify your personal values. Currently, cheating is allowed.

Moderately Grouped

One of the rules I try to live my life by is: “Small pieces, loosely joined”

Then this happened.

http://phys.org/news/2015-06-social-networks-group-boundaries-ideas.html

I don’t know who I am any more. I already feared de-selection from the cult of Unix and now this.

Then I realised that although I favour hi-fi separates, I don’t  design my own amplifiers and hand-wire the components. I don’t compile Linux from source every time. I’m not a fanatic.