I’m writing a short series of posts for MS Israel MCS blog (in Hebrew) and I’d thought I’d translate them to English, as it seems to me they are interesting enough.
In this series I am going to talk about Evolutionary Architecture or , some of the aspect of dealing with software architecture in agile projects. The topic is interesting since architecture and agile seems to have some conflicting forces at work to better understand that let’s start by defining software architecture
There are many definitions for software architecture, with the simplest one (attributed, I think, to Kent Beck) that software architecture is what software architects does. Leaving the fact that (unfortunately) sometimes software architects are very far from building software architectures, the definition doesn’t tell us much. There are many definitions around some are good and some are bad. My current definition is
“Software architecture is the collection of decisions affecting the system’s quality attributes; which have global effects and are hardest to change. Software architecture provides the frame within which the design (code) is built.”
Let’s review the components of this definition
- “affecting the system’s quality attributes” – I’ve written a lot about quality attributes in the past. In a nut shell, quality attributes (often going by the name “non-functional reqs.”) includes aspects of the system like scalability, security, availability etc. Architectural decisions have a direct effect on the system’s ability to meet these types of goal;
- “Global effects” – Design decisions effect the module or the class where they happen. Decisions with macro effect (e.g. choosing a technology, scaling approach) can completely alter a solution
- “Hardest to change” – The most interesting part of the definition, at least in regard to evolutionary architecture.The definition mentions that the code is built within the frame and rules set by the architectural decisions. Change in these decisions can have significant consequences. As a (over simplified) example – You can’t take a standalone system developed in Access and move it to a service oriented, Hadoop based solution with out major changes in the code, data flows and what not.
The definition of Software Architecture above, seems to prescribe that for best results we need to do a lot of up front design to get the architecture right. If that’s true than we have a severe mismatch with agile and/or lean where handling requirement and design up-front is a big no-no (YAGNI- you ain’t gonna need it, comes to mind) – Is there any way to make them work together.
I think yes, and as you’ve probably guessed, the answer is evolving the architecture over time. While this may sound simple it isn’t – I’ll try to give a few strategies to make that work later in the series. Before that, the next part, we’ll examine why design can be emergent which architectures need to evolve