Skip to main content

Posts

In Praise of Crappy Code

Not all code needs to be perfect! This is pretty heretical thinking for a software engineer. The issue is simple: how do you go about developing software for a small fixed budget. Imagine that you have $500 to implement a solution to a problem. If you spend more than that you will never recoup the extra that you spent. This comes up a lot in systems integration scenarios and also in customization efforts. Someone wants you to 'tweak' an application that they are using; you know that no-one else would want that feature and that if you spend more than what the customer will pay you will end up losing money. From the customer's perspective, the common 'time and materials' approach to quoting for software development is a nightmare. Being able to offer a fixed price contract for a task is a big benefit for the customer. But, how much do you quote for? Too much and you scare the customer away. Too little and you lose money. This is where 'crappy code' com
Recent posts

Minimum Viable Product

When was the last time you complained about the food in a restaurant? I thought so. Most people will complain if they are offended by the quality or service; but if the food and/or service is just underwhelming then they won't complain, they will simply not return to the restaurant. The same applies to software products, or to products of any kind. You will only get negative feedback from customers if they care enough to make the effort. In the meantime you are both losing out on opportunities and failing your core professional obligation. Minimum Viable Product speaks to a desire to make your customers design your product for you. But, to me, it represents a combination of an implicit insult and negligence. The insult is implicit in the term minimum. The image is one of laziness and contempt: just throw some mud on the wall and see if it sticks. Who cares about whether it meets a real need, or whether the customer is actually served. The negligence is more subtle but, in the end,

Hook, Line and Sinker

It is well documented that people’s #1 fear is speaking in public ! Effective and efficient public speaking is a whole topic in its own right; but a few simple tips might help to both improve your effectiveness and help to reduce the anxiety. You may be called on to talk about your work at very short notice; or you may have a week’s notice; and you may be required to give a formal slide show or just a brief verbal update. Many, if not most of the issues, are the same. The Hook Newspaper editors call the first paragraph of an article ‘the hook’. Its meant to hook you into reading the rest of the piece. On the other hand, the classical ‘say what you are going to say, say it, and say what you said’ approach gives people plenty of time to switch off. The hook may be playful, it may be controversial, but it must communicate why the listener should pay attention. The Line Its a conversation! Even if no one says anything they are listening and thinking; and maybe replying to you in their head

Existential Types are the flip side of generics

Generic types, as can now be seen in all the major programming languages have a flip side that has yet to be widely appreciated: existential types. Variables whose types are generic may not be modified within a generic function (or class): they can be kept in variables, they can be passed to other functions (provided they too have been supplied to the generic function), but other than that they are opaque. Again, when a generic function (or class) is used, then the actual type binding for the generic must be provided – although that type may also be generic, in which case the enclosing entity must also be generic. Existential types are often motivated by modules. A module can be seen to be equivalent to a record with its included functions: except that modules also typically encapsulate types too. Abstract data types are a closely related topic that also naturally connect to existential types (there is an old but still very relevant and readable article on the topic Abstract types have

Concept Oriented Markup

I have long been frustrated with all the different text mark up languages and word processors that I have used. There are many reasons for this; but the biggest issue is that markups (including very powerful ones like TeX) are not targeted at the kind of stuff I write. Nowadays, it seems archaic to still be thinking in terms of sections and chapters. The world is linked and that applies to the kind of technical writing that I do. I believe that the issue is fundamental. A concept like "section" is inherently about the structure of a document. But, what I want to focus on are concepts like "example", "definition", and "function type". A second problem is that, in a complex environment, the range of documentation that is available to an individual reader is actually composed of multiple sources. Javadoc exemplifies this: an individual library may be documented using Javadoc into a single HTML tree. However, most programmers require access to multip

Comments Should be Meaningless

This is something of a counterintuitive idea: Comments should be meaningless What, I hear you ask, are you talking about? Comments should communicate to the reader! At least that is the received conventional wisdom handed does over the last few centuries (decades at least). Well, certainly, if you are programming in Assembler, or C, then yes, comments should convey meaning because the programming language cannot So, conversely, as a comment on the programming language itself, anytime the programmer feels the imperative to write a meaningful comment it is because the language is not able to convey the intent of the programmer. I have already noticed that I write far fewer comments in my Java programs than in my C programs.  That is because Java is able to capture more of my meaning and comments would be superfluous. So, if a language were able to capture all of my intentions, I would never need to write a comment. Hence the title of this blog.

Robotic Wisdom

It seems to me that one of the basic questions that haunt AI researchers is 'what have we missed?' Assuming that the goal of AI is to create intelligence with similar performance to natural intelligence; what are the key ingredients to such a capability? There is an old saw It takes 10,000 hours to master a skill There is a lot of truth to that; it effectively amounts to 10 years of more-or-less full-time focus. This has been demonstrated for many fields of activity from learning an instrument, learning a language or learning to program. But it does not take 10,000 hours to figure out if it is raining outside, and to decide to carry an umbrella. What is the difference? One informal way of distinguishing the two forms of learning is to categorize one as `muscle memory' and the other as 'declarative memory'. Typically, skills take a lot of practice to acquire, whereas declarative learning is instant. Skills are more permanent too: you tend not to forget a skill; but i