Systematic Reuse Mythbuster #1 – Reusable Doesn’t Mean Perfection

December 26, 2011

One common criticism against systematic software reuse is the myth that it implies perfection – creating a reusable asset automatically conjures up visions of a perfect design, something that is done once and done right.  Many developers and managers confuse reusability with design purity. However, reusability is a quality attribute like maintainability, scalability, or availability in a software solution. It isn’t necessary or advisable to pursue a generic design approach or what one believes is highly reusable without the right context.

The key is to go back to the basics of good design: identify what varies and encapsulate it.

The myth that you can somehow create this masterpiece that is infinitely reusable and should never be touched is just that – it is a myth and is divorced from reality. Reusable doesn’t imply:

  • that you invest a lot in big up front design effort
  • you account for everything that will vary in the design – the critical factor is to understand the domain – well enough, deep enough, so you can identify the sub-set of variability that truly matters

In the same vein, reusablility strives for separating concerns that should be kept distinct. Ask repeatedly:

  • Are there multiple integration points accessing the core domain logic?
  • Is there a requirement to support more than one client and if so, how will multiple clients use the same interface?
  • What interfaces do your consumers need? is there a need to support more than one?
  • What are the common input parameters and what are those that vary across the consumer base?

These are the key questions that will lead the designer to anticipate the appropriate places where reuse is likely to happen.  Finally, it is important that we don’t build for unknown needs in the future – so the asset is likely to solve a particular problem, solve it well, solve it for more than one or two consumers, and finally has potential to be used beyond the original intent. At each step there are design decisions made, discarded, continuous refactoring, refinements to the domain model – if not re-definition altogether.

Don’t set out trying to get to the end state or you will run the risk of adding needless complexity and significant schedule risk.


Domain Analysis Key To Systematic Reuse

November 26, 2010

Domain analysis is a foundational capability required for effective systematic reuse. Why? There are a lot of applications your teams are working on and the common theme among them most likely is the fact that they are in the same problem domain. In order to truly bring down cost of new applications and services, it is critical that the domain is understood and modeled appropriately. Here are some specific strategies to make this idea operational:

  1. Account for domain analysis and modeling in your iteration planning. Domain analysis is necessary to understand the nuances and variation points that an application/service/process needs to realize. Discovering the right variations requires time and interactions with business stakeholders and subject matter experts.
  2. Aspire for a core set of business object definitions that can be shared across business processes and service interfaces. Without appropriate data governance, domain knowledge will either be inaccurate/incomplete or worse duplicated in an inconsistent fashion. As the number of customer interfaces increase for your services, the domain inconsistencies will lead to greater point-to-point integrations and complexity.
  3. Align overall architecture with domain variations. Your domain is rich and complex but probably varies in a known set of ways. Additionally, what varies isn’t uniform and the rate of change across these variations aren’t identical. This is significant because the variations in the domain need to be captured in your overall architecture. Products/applications in the domain need to share a common architecture – only then can components integrate and inter-operate and systematic reuse will take hold. Constantly evaluate the need for a new version of a core business entity and associated classes to manage the entity.
  4. Refactor constantly to get to intention revealing design and code. As Eric Evans illustrates in Domain Driven Design, intention revealing code is easier to understand and evolve.  It also makes it easier to address new business requirements – as the design/implementation are closely aligned with the business domain, the quality of communication (referred to as ubiquitous language) and the ability to change it both increase significantly.

This isn’t an exhaustive list – instead, it is meant to highlight the need for placing the domain in the middle of every design, architecture, and implementation decision your teams make.

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