Skip to main content

Log Everything

This post was originally conceived back in mid 2011, starting a new project made me think back to this event, hence the post.

Any developer worth their salt will know what logging is. You could argue there are two types of logging, either developer logging or auditing. Developer logging would be what we log when something goes wrong. Using the results of this logging we can track down what went wrong, and put fixes in place to stop this event from occurring again. If this logging fails, or logs the incorrect thing it is not the end of the world. Due to this, I generally do not care for testing such scenarios. The code should behave the same with our without this logging.

Auditing would come under logging which as part of the application needs to be carried out at all times. Consider visiting a cash machine. When withdrawing fifty pounds, you want to make sure your bank logs this in case anything goes wrong. This sort of logging is crucial, and must work and must log the correct data. This is considered a feature, therefore this should be tested as it is part of the behavior of the application.

When I think back to my first few years of programming my code was littered with logging. In the early days after each statement, variable and function I would print out what happened, along with any errors that happened. In fact I'd say that everyone starts out like this. The strange thing is as we get better, the logging becomes less and less. Rather than the first class citizen we relied on in the early days, logging is seen as boring. The problem with treating logging code as a second class citizen is that when things go wrong, it can be very difficult or near impossible to track down what has happened. When you realise you need logging, its often too late. You will need to redeploy the application and wait for the problem to expose itself again.

Back in 2011 we had a difficult problem to track down. The dreaded "OutOfMemoryException". Being the cocky developers we were, we decided to add the logging last. After all, it was there for when things went wrong. We never planned things would go wrong, after all it "worked on my machine". After redeploying the application with logging we managed to track down roughly what was going wrong, and in turn began to resolve the problem. Had we added this logging initially, we could have resolved this problem in half the time.

The lesson I learned here was simple. Any time you have an error, log it. If the logging is not in place, we add it. Creating a new application? In the first iteration(s) make sure some form of logging is in place. I believe by following this simple rule any future issues can be handled easier. Logging should be a first class citizen regardless of purpose.


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 …