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Tag Archive for code-metrics

Is the number of bugs in a section of code proportional to the # of lines ? The square of the # of lines ?

Are there any studies that aggregate data over a wide population of contributed code, that establish a correlation between amount of code written in a commit and the # of bugs discovered in that code ? It’d be hard to do in github without knowing whether a change was due to new functionality or a bug, but you could determine a relation between lines of code per commit and how much thrashing eventually goes on in that code.

Source code metrics for measuring code stability?

Considering how software is developed during a release cycle (implementation, testing, bug fixing, release) I was thinking that one should be able to see some pattern in the lines of code that are changed in the code base; e.g. towards the end of a project, if the code becomes more stable, one should see that fewer lines of code are modified per unit of time.

Strategies for using a code metric evaluation tool

Should code quality metric evaluation tools like Sonar be integrated with IDE for running local analysis or should they be a part of the build process (like integrated with maven) for continuous inspection or should it be a combination of both? How can we leverage the power of such tools to the maximum extent possible?

What does the “4” in LCOM4 mean?

I know that methods in a class should have high cohesion which roughly translates to having all the methods use all the instance variables directly or indirectly. I know that LCOM4 (Lack of cohesion)metric is useful for having a quantitative figure of how much cohesive the methods in a class are. A class with a LCOM4 value of 1 will be considered pretty good while a class with LCOM4 value of, say, 10 is considered a poorly designed class and this probably tells that we are better off decomposing the original class into 10 separate classes. All this is okay but what does the 4 signify in LCOM4 metrics?

Is there a software quality metric related to side effects?

In large systems there are often code paths that modify state or produce side effects that other code comes to depend on. This makes it hard to safely change code without understanding the whole system, because changing the order of function calls or operations could change the behavior. Is there a software quality metric that measures or correlates with this kind of issue?