# Size Estimation ## Basic idea Estimating *how big* the software will be — a prerequisite for any algorithmic cost model. Three popular metrics: SLOC (post-hoc, language-dependent), Function Points (from requirements), Use Case Points (from use cases). ## Key facts * SLOC: easy to count after the fact, useless to predict beforehand without analogous projects. * FP: requires written requirements spec; language-independent. * UCP: needs well-written use cases. Commonly used metric for software size estimation * Source lines of code (SLOC) * Function Points (FP) * Based on Requirement specs * Use case points (UCP) * Based on Use Cases ## Source Lines of Code (SLOC) There are two types of SLOC: * Physicial SLOC: Count excluding comments and blank lines. * Logical SLOC: Measure the number of executable "statements", but their specific definitions are tied to specific computer languages. ### Advantages of SLOC * Scope for Automation of counting: since lines of code is a physical entity it is easy to count and can be automated using a tool. * An intuitive metric: Lines of code serves as an intuitive metric for measuring the size of software because it can be seen and the effect of it can be visualized. ### Disadvantages of SLOC * Variability: depends on programmer experience, language, framework support, reuse etc. * It is difficult to estimate the number of lines of code that will be needed to develop a system from information that is available in analysis and design phases * Lack of universally accepted definition for exactly what a line of code is. --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://isubasinghe.gitbook.io/isithas-wiki/software_engineering/management/cost_estimation/size_estimation.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.