Lesson plan
Weighted Micro Function Points
Weighted Micro Function Points (WMFP) is a modern software sizing algorithm which is a successor to solid ancestor scientific methods as COCOMO, COSYSMO, maintainability index, cyclomatic complexity, function points, and Halstead complexity. It produces more accurate results than traditional software sizing methodologies, while requiring less configuration and knowledge from the end user, as most of the estimation is based on automatic measurements of an existing source code. 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. In addition to compatibility with the waterfall software development life cycle methodology, WMFP is also compatible with newer methodologies, such as Six Sigma, Boehm spiral, and Agile (AUP/Lean/XP/DSDM) methodologies, due to its differential analysis capability made possible by its higher-precision measurement elements.
Article summary
Weighted Micro Function Points (WMFP) is a modern software sizing algorithm which is a successor to solid ancestor scientific methods as COCOMO, COSYSMO, maintainability index, cyclomatic complexity, function points, and Halstead complexity. It produces more accurate results than traditional software sizing methodologies, while requiring less configuration and knowledge from the end user, as most of the estimation is based on automatic measurements of an existing source code. 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. In addition to compatibility with the waterfall software development life cycle methodology, WMFP is also compatible with newer methodologies, such as Six Sigma, Boehm spiral, and Agile (AUP/Lean/XP/DSDM) methodologies, due to its differential analysis capability made possible by its higher-precision measurement elements.
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Discussion questions
- Summarise the article in your own words. Which single claim would you verify first, and why?
- Which claim in this article is most likely to be revised as the sources update? How would you check its current status?
- If two sources disagreed about one of these facts, what would you need in order to trust one over the other?
Bibliography
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Key claims and bibliography are generated from the same tracked claims and sources as the article page.