Leftshift’s Weblog

Techniques to improve your code

Wordle Up

I’m off on holiday for the next two weeks so before being largely disconnected I thought I’d point you in the direction of wordle. It’s a tag cloud creator and works based on an RSS or ATOM feed, or any text you paste in. Here is the cloud for this blog

Tag cloud of leftshift.wordpress.com

As you can see it produces very nice images and the fonts, colours and layout are all customizable. I think I might start adding a tag index to all docs I produce to give people a visual clue of the content.

Happy coding and see you in a couple of weeks.

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15 August 2008 Posted by | Misc. | , | Leave a comment

Quality Testing

As part of a continuous integration cycle most people consider running unit and integration tests. Some even consider running automated acceptance tests. Fewer still focus on code quality tests. To ensure code is maintainable requires a certain amount of effort as the code changes. I think this is what the refactor stage of the TDD red, green, refactor cycle alludes to. As well as refactoring code to remove duplication, there are other considerations to be made with regards to maintainability. We use six indicators to give a finger in the air estimate of the maintainability of a code base. The indicators we use are as follows:

Unit Test Coverage High test coverage is a good indicator of whether a TDD approach is being followed, and if not an optimistic percentage of the chance of a bug being caught. Said another way, If a bug is introduced into the code the chance of it being caught is at best the percentage of code covered by tests. This very much depends on the quality of the tests, but if you only have fifty percent coverage and introduce a bug, it’s a coin toss whether it’s detected. If the tests are poor the real figure is much lower than fifty percent.

Percentage of large methods Fairly obvious this one, but large methods are harder to maintain because they contain more code. There is more scope for error, less accuracy for identifying the cause of any error [any unit test covers more code] and a greater chance that the method is breaking the single responsibility principle giving it more than one reason to change. What you consider a large method is up to you, but we have been using ten lines of code as our measure.

Class Cohesion For a class to be cohesive all methods should use all fields. We use the lack of cohesion of methods henderson-sellers formula to measure this one. If a class isn’t cohesive it’s an indicator that unrelated functionality could be split into it’s own class. In other words it has more than one reason to change and is therefore breaking the single responsibility principle.

Package Cohesion For a package or assembly to be cohesive the classes inside the package should be strongly related. This is a measure of the average number of type relationships within a package. Low cohesion suggests that the types can be split into seperate packages.

Class Coupling This is a measure of the number of types that depend on a particular type a.k.a. afferent coupling. If a high number of types depend on the class in question, making changes to it will be hard without breaking lots of client code. There are a number of reasons why this might occur. Responsibility for one aspect may be split among multiple classes, but more likely you don’t have a losely coupled design.

Package Coupling This is a measure of the number of types outside this package or assembly that depend upon types within this package. One possible reason for high coupling is a packaging problem – things that change together should stay together. Another reason is that the packages in question have many responsibilities.

I’d love to hear feedback on the way you measure the maintability of code.

12 August 2008 Posted by | Code Quality, Metrics | , , | Leave a comment