Skip to main content

Top Down vs Bottom Up

Top down development has you starting at the highest point in the application that you can. From here you code down until there is nothing else left to develop. Once you reach this point you should be code complete. Along the way you may need to stub out areas that have not yet been created, or designed.

Bottom up development has you starting at the lowest point in the application. The idea being that this part of the application has the most complexity or will be the most important. You will build the system up from a series of smaller components.

Top down development and bottom up development was introduced to myself in my early days of university. At the time the distinction didn't really mean much - I was very much a developer who would work from the bottom up.

Over time I have completely switched my stance on this. I believe agile practices and TDD are the reason for this change. I feel so strongly about this that I would go as far as to claim that within an agile team - bottom up development is an anti pattern.

Consider the following tasks to be completed on a team of four developers.

  • Create controller - main entry point, request mapping.
  • Create service - service layer, simple business logic.
  • Database query - thin wrapper around complex DB query.

With a bottom up approach a pair of developers could work on the complex database query. After some time they would have this working. The other two developers could start with the controller or service.

The problem with this approach comes from the painful integration process. The developers working on the service might be coding against the interface the team discussed during a planning session, while the developers on the query may have had to change their approach.

This example is trivial, but imagine a story with thirty tasks, more developers and more complexity and this bottom up approach is difficult. Over the past few years my top down approach has evolved.

My first step would be to stub out the workflow with the above implementation. There is no real logic here - only the objects collaboration is implemented. At this stage there are no tests, TDD would not be used. After all there is no logic here. The code is so simple it can be reasoned about with peer review, planning sessions and so on.

At this stage all of the tasks are open for any developer to pick up. If a breaking change was required, there would be no way for one pair to commit these changes without the other pair knowing. Another benefit of this approach is that an end to end acceptance test could be wrapped around the functionality from the get go.

As part of these tasks each developer would use TDD. Remember no tests exist at this point. Building up the tests in stages would ensure the logic of how the objects collaborate is preserved, and ensures that the actual domain logic that is implemented is correct. Does this mean we aren't doing TDD? No, of course not. The tests will drive the implementation. If we need to introduce new objects that is fine - these simply become implementation details that the other devs need not worry about as long as the workflow is not broken.

This approach to top down development isn't new, though many don't appreciate its benefits. I plan on expanding on this style of pragmatic TDD in the coming months.


Popular posts from this blog

Three Steps to Code Quality via TDD

Common complaints and problems that I've both encountered and hear other developers raise when it comes to the practice of Test Driven Development are: Impossible to refactor without all the tests breakingMinor changes require hours of changes to test codeTest setup is huge, slow to write and difficult to understandThe use of test doubles (mocks, stubs and fakes is confusing)Over the next three posts I will demonstrate three easy steps that can resolve the problems above. In turn this will allow developers to gain one of the benefits that TDD promises - the ability to refactor your code mercifully in order to improve code quality.StepsStop Making Everything PublicLimit the Amount of Dependencies you Use A Unit is Not Always a Method or ClassCode quality is a tricky subject and highly subjective, however if you follow the three guidelines above you should have the ability to radically change implementation details and therefore improve code quality when needed.

DRY vs DAMP in Tests

In the previous post I mentioned that duplication in tests is not always bad. Sometimes duplication becomes a problem. Tests can become large or virtually identically excluding a few lines. Changes to these tests can take a while and increase the maintenance overhead. At this point, DRY violations need to be resolved.SolutionsTest HelpersA common solution is to extract common functionality into setup methods or other helper utilities. While this will remove and reduce duplication this can make tests a bit harder to read as the test is now split amongst unrelated components. There is a limit to how useful such extractions can help as each test may need to do something slightly differently.DAMP - Descriptive and Meaningful PhrasesDescriptive and Meaningful Phrases is the alter ego of DRY. DAMP tests often use the builder pattern to construct the System Under Test. This allows calls to be chained in a fluent API style, similar to the Page Object Pattern. Internally the implementation wil…

Coding In the Real World

As a student when confronted with a problem, I would end up coding it and thinking - how do the professionals do this?For some reason I had the impression that once I entered the industry I would find enlightenment. Discovering the one true way to write high quality, professional code.It turns out that code in industry is not too far removed from the code I was writing back when I knew very little.Code in the real world can be:messy or cleanhard or easy to understandsimple or complexeasy or hard to changeor any combination of the aboveVery rarely will you be confronted with a problem that is difficult. Most challenges typically are formed around individuals and processes, rather than day to day coding. Years later I finally have the answer. Code in the real world is not that much different to code we were all writing when we first started out.If I could offer myself some advice back in those early days it would be to follow KISS, YAGNI and DRY religiously. The rest will fall into plac…

Feature Toggles

I'm a fan of regular releasing. My background and experience leads me to release as regularly as possible. There are numerous benefits to regular releases; limited risk, slicker release processes and the ability to change as requirements evolve.The problem with this concept is how can you release when features are not functionally complete?SolutionIf there is still work in progress, one solution to allow frequent releases is to use feature toggles. Feature toggles are simple conditional statements that are either enabled or disabled based on some condition.This simple example shows a feature toggle for an "Edit User" feature. If the boolean condition is false, then we only show the "New User" feature and the "Admin" feature. This boolean value will be provided by various means, usually a configuration file. This means at certain points we can change this value in order to demonstrate the "Edit User" functionality. Our demo environment could …

Reused Abstraction Principle

This is the second part of my series on abstractions.Part 1 - AbstractionsPart 3 - Dependency Elimination PrincipleThe Reused Abstraction Principle is a simple in concept in practice, but oddly rarely followed in typical enterprise development. I myself have been incredibly guilty of this in the past.Most code bases have a 1:1 mapping of interfaces to implementations. Usually this is the sign of TDD or automated testing being applied badly. The majority of these interfaces are wrong. 1:1 mappings between interfaces and implementations is a code smell.Such situations are usually the result of extracting an interface from an implementation, rather than having the client drive behaviour.These interfaces are also often bad abstractions, known as "leaky abstractions". As I've discussed previously, these abstractions tend to offer nothing more than simple indirection.ExampleApply the "rule of three". If there is only ever one implementation, then you don't need …