Why lines of code are a bad measure of developer productivity
Traditional metrics, like lines of code (LOC), have long been a staple of trying to understand developer productivity. However, the reliance on LOC, whether counting total lines, source lines, or differentiating between logical Source Lines of Code (SLOC) and physical SLOC, is increasingly recognized as a flawed approach. This article explores why lines of code, in all their forms—physical line counts, logical SLOC, or even the count lines of code (CLOC)—fall short as a measure of software development productivity and alternatives to understand it better.
Lines of Code (LOC) is a common metric in software engineering. It refers to the number of lines in a software program’s source code. LOC is used to quantify the size of a software project by counting the number of lines it comprises. This measurement includes all the text in the source files, which can be divided into several categories, such as executable statements, declarations, comments, and blank lines, depending on the specific definitions and counting methods employed.
There are two primary types of LOC measurements: physical LOC and logical LOC (also known as Source Lines of Code, SLOC). Physical LOC counts every line in the source code, including blank lines and comments, giving the code base a straightforward, literal size. Logical SLOC, however, attempts to measure only the lines contributing to the software’s functionality, excluding comments, blank lines, and possibly other non-executable statements, depending on the specific methodology used.
