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Contents • • • • • • • • • • • • • Measurement methods [ ] Many useful comparisons involve only the of lines of code in a project. Using lines of code to compare a 10,000 line project to a 100,000 line project is far more useful than when comparing a 20,000 line project with a 21,000 line project. While it is debatable exactly how to measure lines of code, discrepancies of an order of magnitude can be clear indicators of software complexity. There are two major types of SLOC measures: physical SLOC (LOC) and logical SLOC (LLOC). Specific definitions of these two measures vary, but the most common definition of physical SLOC is a count of lines in the text of the program's source code excluding comment lines. Logical SLOC attempts to measure the number of executable 'statements', but their specific definitions are tied to specific computer languages (one simple logical SLOC measure for -like is the number of statement-terminating semicolons).

It is much easier to create tools that measure physical SLOC, and physical SLOC definitions are easier to explain. However, physical SLOC measures are sensitive to logically irrelevant formatting and style conventions, while logical SLOC is less sensitive to formatting and style conventions. However, SLOC measures are often stated without giving their definition, and logical SLOC can often be significantly different from physical SLOC.

Consider this snippet of C code as an example of the ambiguity encountered when determining SLOC. This article contains: vague phrasing that often accompanies or information. Such statements should be.

In depth look at DSQI and Software package metrics! Advantage is the that the metric. Aggregating Software Metrics! For example the number of errors per person hours would be a metric. Thus, software measurement gives rise to software metrics. Metrics are related to the four functions of management: Planning; Organising; Controlling; Improving; Metric Classification Software metrics can be divided into two categories; product metrics and process metrics.

(September 2013) SLOC measures are somewhat controversial, particularly in the way that they are sometimes misused. Experiments have repeatedly confirmed that effort is highly correlated with SLOC [ ], that is, programs with larger SLOC values take more time to develop.

Dbz Ultimate Tenkaichi Dlc Characters. Thus, SLOC can be very effective in estimating effort. However, functionality is less well correlated with SLOC: skilled developers may be able to develop the same functionality with far less code, so one program with fewer SLOC may exhibit more functionality than another similar program. In particular, SLOC is a poor productivity measure of individuals, since a developer can develop only a few lines and yet be far more productive in terms of functionality than a developer who ends up creating more lines (and generally spending more effort). Good developers may merge multiple code modules into a single module, improving the system yet appearing to have negative productivity because they remove code. Also, especially skilled developers tend to be assigned the most difficult tasks, and thus may sometimes appear less 'productive' than other developers on a task by this measure. Furthermore, inexperienced developers often resort to, which is highly discouraged as it is more bug-prone and costly to maintain, but it results in higher SLOC.