Now that we’ve established that very few people who work in “IT” have anything to do with technology, except as a tool, and that “computer science” isn’t about computers, we’re back at the original reason I began to write a book. I was once an ‘Information Systems Engineer’ and wasn’t very sure what any of those words meant, particularly “information”.
Software development teams often see their role as solving their customer’s problems. Software package providers say they are “solution providers”. What does the ‘unspeakable profession’ actually do? We got some clues from Hal Abelson in the video I linked to in my last post, that new areas of intellectual endeavour often confuse the ‘essence’ of their subject with their tools; so do we really engineer software?
Hal said that writing software is the process (or function) of formalising our intuitions about process (function.) Our software is a speculative formal abstraction of our intuitive understanding of a process we may not entirely understand. No wonder software projects so often fail. Like the rest of science, software is built on ideas that haven’t been proved wrong yet.
Software developers are presented with, or attempt to discover, experts’ (declarative) knowledge of the business process in the ‘domain’ we are about to change. This is ‘the abstract requirements’. Some of this may have to be implied from imperative knowledge embedded in existing software. It may be presented as imperative solutions. It may be incomplete.
We then follow our own process (function) for: ‘the way we do software’, in order to design a new process, some of which is also likely to be have to be embedded in software. Applying functions to change functions? That’s what functional programming does, isn’t it?
I believe that the ‘stuff’ of ‘computer science’, is state-change of systems of process and data. Who remembers ‘Data Processing’? Functional programming points out that the processes themselves are data and dynamic state-change is unpredictable and therefore dangerous.
Engineering would apply ‘project thinking’ to this unstable, poorly defined change. I may once have tried to be an information systems engineer but I saw that it didn’t work and took a 20 year break from software development.
Agile frameworks recognise such changes as risky experiments and carefully apply the scientific method, incrementally with feedback loops, to check assumptions.
We may need to return another time to see what functional programming has to say about 2 projects making concurrent changes from the same initial state. Until then, good luck with those.