source lines of code

The patron is looking for, size estimates of logical source lines of code ratios for different languages.

It is common practice to count the software size (Source lines of code) to track current project progress or establish a baseline for future project estimates.

The size of the system, measured in source lines of code as established by the system design, may change as the system is coded.

Amount of code that can be created or maintained per programmer (often measured in source lines of code per day)

Program size is expressed in estimated thousands of source lines of code (SLOC)

It relates software development effort for a program, in man-years T, to source lines of code (SLOC).

In 2001, Wheeler published a webpage where he measured the source lines of code of the Red Hat Linux distribution version 7.1.

Putnam uses ESLOC (Effective Source Lines of Code) throughout his books.

SLOC refers to Source Lines of Code and is a unit used to measure the size of software program based on a set of rules.

Examples could include DOS to Win95 or Unix to GNU, using a simple metric like source lines of code to mark the difference.

The current version has grown to more than 200,000 source lines of code and is capable of outputting to many third party clients including Microsoft Project and IBM Rational.

Supported sizing metrics include source lines of code (SLOC), function points, function-based sizing (FBS) and a range of other measures.

Source lines of code (SLOC) is a software metric used to measure the size of a computer program by counting the number of lines in the text of the program's source code.

Although source lines of code or SLOC is a widely accepted sizing metric, in general there is a lack of standards that enforce consistency of what and how to count SLOC.

For example, measuring the productivity of a software development team in terms of source lines of code encourages copy and paste code and over-engineered design, leading to bloated code bases that are particularly difficult to maintain, understand and modify.

The size of the software has grown to over 200,000 source lines of code and shifted from simply a means to generate work estimates through parametric modeling to a system that buttresses those results with simulation-based probability and over 20,000 historical cases to draw conclusions from.

By retrieving data from revision control repositories (such as CVS, SVN, Git, Bazaar, and Mercurial), Ohloh provides statistics about the longevity of projects, their licenses (including license conflict information) and software metrics such as source lines of code and commit statistics.

As many ancestor measurement methods use source lines of code (SLOC) to measure software size, WMFP uses a parser to understand the source code breaking it down into micro functions and derive several code complexity and volume metrics, which are then dynamically interpolated into a final effort score.