When done is not done

Posted by Tony Davis on Simple Talk See other posts from Simple Talk or by Tony Davis
Published on Thu, 05 Jul 2012 13:45:00 +0000 Indexed on 2012/07/05 15:21 UTC
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Most developers and DBAs will know what it’s like to be asked to do "a quick tidy up" on a project that, on closer inspection, turns out to be a barely working prototype: as the cynical programmer says, "when you’re told that a project is 90% done, prepare for the next 90%".

It is easy to convince a layperson that an application is complete just by using test data, and sticking to the workflow that the development team has implemented and tested. The application is ‘done’ only in the sense that the anticipated paths through the software features, using known data, are fully supported.

Reality often strikes only when testers reveal its strange and erratic behavior in response to behavior from the end user that strays from the "ideal". The problem is this: how do we measure progress, accurately and objectively? Development methods such as Scrum or Kanban, when implemented rigorously, can mitigate these problems for developers, to some extent. They force a team to progress one small, but complete feature at a time, to find out how long it really takes for this feature to be "done done"; in other words done to the point where its performance and scalability is understood, it is tested for all conceivable edge cases and doesn’t break…it is ready for prime time. At that point, the team has a much more realistic idea of how long it will take them to really complete all the remaining features, and so how far away the end is.

However, it is when software crosses team boundaries that we feel the limitations of such techniques. No matter how well drilled the development team is, problems will still arise if they don’t deploy frequently to a production environment. If they work feverishly for months on end before finally tossing the finished piece of software over the fence for the DBA to deploy to the "real world" then once again will dawn the realization that "done done" is still out of reach, as the DBA uncovers poorly code transactions, un-scalable queries, inefficient caching, and so on. By deploying regularly, end users will also have a much earlier opportunity to tell you how far what you implemented strayed from what they wanted.

If you have a tale to tell, anonymized of course, of a "quick polish" project that turned out to be anything but, and what the major problems were, please do share it.

Cheers,

Tony.

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