Estimating Lines of Code

I’ve always been a bit puzzled on why people would use lines of code to estimate projects. It seems that estimating (more realistically guessing) lines of code (LOC) to estimate effort and schedule is way harder that splitting the project into jobs and undertaking an estimate for each job. However reading Steve McConnell’s Rapid Development book has changed my mind.

In it he has charts linking lines of code to effort over a range of criteria. So if you know the LOC for your projects you can plug them into the tables and see how you projects measure up. Moreover you could get lines of code for a project to build a historic set of data tailored to your team to take some of the guess work out of that blackest of all arts – software estimation.

Which got me thinking of how you would quickly get non-commented, non-whitespace lines of code for a Web Application written it ASP.Net

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C#
Count the semicolons C#.

CSS
I would count the number of {

HTML
LOC are more difficult here. Possibility to count open angled brackets (<) and maybe divide by 5 – making the assumption that there is 5 tags per line JavaScript and VB.Net
Semicolons doesn’t work so well here as they are optional in the code. You’d need to be a bit cleverer and count the number of carriage returns without comments and with a length of more then one when been trimmed

OR

Quick and dirty: arbitrarily estimate the number of characters per line then whip through all the files and could the characters and divide by the per line estimate.

SQL stored procedures and functions
Like JavaScript you’d be looking at using carriage returns or using the quick and dirty method

Other elements.
For example SQL reports, Data extract components etc…
Can’t do anything with these so get the back of the envelope out and estimate what fraction of the project was spend on these activities. Multiple the LOC by this ratio.

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In the best of all worlds we would all use function points or some kind of automated formula based approach but I moved out of the best of all worlds sometime ago and sadly my software development occurs in the dirty old real world. In this world one frequently doesn’t have time to spend half a day calculating historical effort but you’ll always have the opportunity to spend a sneaky 15 minutes seeing how many LOC were wrote and how long it took. It’s always good to marvel at how much work you’ve done and it may even make software estimation a slightly less black art in the future.