Yesterday I was involved with a workshop around agile development at scale. At one point in the conversation we started talking about the relationship between cost and quality. Some of the people in the workshop were relatively new to agile and still believed the traditional theory that to build in high quality it costs more, sometimes substantially more. This does appear to be true on traditional waterfall projects, but some people were making the mistake that this was an "natural law of IT" which also must apply to agile project teams. I naturally jumped on that idea and described how agile developers have found that writing high quality code leads to lower development costs and shorter time to value, in direct contradiction to traditional theory. A few people struggled with the idea for a bit, and one was pretty adamant that in some cases the need for very high quality does in fact lead to greater cost and time. He talked about his experiences on large-scale Rational Unified Process(RUP) projects and in particular how some URPS (usability, reliability, performance, and supportability) requirements can increase your cost. At this point Per Kroll, co-author of Agility and Discipline Made Easy: Practices from OpenUP and RUP, jumped into the conversation and pointed out although higher quality does lead to lower cost in most cases, using Toyota's lean approach to manufacturing as an example, that the agile community didn't completely have the relationship between quality and cost completely correct. My spidey sense told me that a learning opportunity was coming my way.
Per and I had an offline discussion about this to explore what he'd been observing in practice. In most situation it appears to be the case that higher quality does in fact lead to lower costs and shorter time for delivery, something that Per and I had observed numerous times. This happens because high quality code is much easier to understand and evolve than low quality code -- the agile community has found that it is very inexpensive to write high quality code by following practices such as continuous integration, developer regression testing [or better yet test-driven development(TDD)], static code analysis, following common development conventions, and agile modeling strategies. When you "bake in" quality from the start through applying these techniques, instead of apply traditional techniques such as reviews and end-of-lifecycle testing (which is still valid for agile projects, but should not be your primary approach to testing) which have long feedback cycles and therefore prove costly in practice. But, as we've learned time and again, when you find yourself in more complex situations of Agility@Scale sometimes the mainstream agile strategies fall down. For example, in situations where the regulatory compliance scaling factor is applicable, particularly regulations around protecting human life (i.e. the FDA's CFR 21 Part 11), you find that some of the URPS requirements require a greater investment in quality which can increase overall development cost and time. This is particularly true when you need to start meeting 4-nines requirements (i.e. the system needs to be available 99.99% of the time) let alone 5-nines requirements or more. The cost of thorough testing and inspection can rise substantially in these sorts of situations.
In conclusion, it does seem to be true in the majority of situations, which is what the level 1 rhetoric focuses on, that higher quality leads to lower development costs. But at scale this doesn't always seem to hold true.
PS -- Sorry for the corny title, but a couple of days ago at the Rational Software Conference I had the pleasure of interviewing Jamie Hyneman and Adam Savage from the Discovery Channel's Mythbuster's show as part of the conference keynote. They're great guys, BTW, who have had a really positive impact on motivating children to be interested in science (apparently kids like to see stuff get blown up, go figure).[Read More]
Agility@Scale: Strategies for Scaling Agile Software Development
Matching: quality X
When it comes to testing on agile projects it is common practice for agile teams to adopt a "whole team testing" approach where the team itself does its own testing. To accomplish this agile teams will often embed testers in the development team. Programmers will work closely with the testers, often via non-solo development strategies such as pair programming, to pick up their valuable testing skills. The testers will in turn pick up new skills from the programmers, and in effect both groups will move away from being just specialists (testers or programmers) to being what's called generalizing specialists. Whole team testing can be very different from traditional approaches where programmers may do some testing, often unit testing of their own code, and then throw it over the wall to testers and quality assurance (QA) professionals for verification and validation.
My experience is that whole team testing is a very effective strategy, that agile testing and quality strategies in general appear to be far more effective than traditional testing and quality strategies, but that whole team testing isn't the full agile testing picture. At scale, particularly in complex domains, complex technical situations, or in regulatory compliance situations, Disciplined Agile Delivery (DAD) teams will extend whole team testing with a parallel independent test team. Although the development team still does the majority of the testing, the independent test team which is working in parallel to the development team looks for problems which are harder or more difficult for the development team to find and then reports potential defects back to the development team.
The types of testing that the parallel independent test team performs may include:
I'd like to leave you with several important thoughts: