Estimation techniques - Problem based Estimation

In software estimation, lines of code and function point metrics can be used in two ways:
- it can be used as an estimation variable that could size each element of the software.
- it can be used as baseline metrics that are collected from past projects and are used with the estimation variables to develop cost and effort.

Lines of code and function point are different techniques but there are some characteristics that are common. Project planning begins with scope of the software and software is decomposed into problem functions and are estimated individually and then lines of code and function point are estimated for each function.

Baseline metrics are applied to estimation variable and cost and effort is derived. It should be kept in mind when collecting productivity metrics for projects, one should be sure to establish a taxonomy of project types. This will enable to compute domain specific averages making estimation more accurate.

LOC and FP techniques differ in how decomposition is used. Consider a case when LOC is used, it is essential to use decomposition and that too to a fairly detailed level. In order to get a higher level of accuracy, it is necessary to have a high degree of partitioning.

Now considering the case of FP, the usage of decomposition is different. It is required to get the five information domain characteristics, and the complexity adjacent values. Once these are available, and using past data, an estimate can be generated.

Alongside, a project planner estimates a range of values using historical data; these are the optimistic, most likely, and pessimistic sizes for each function. Based on these, an expected value for the estimation variable can be calculated.

What are different metrics used for software measurement?

Software measurement can be categorized in two ways:
- direct measures of software process.
- indirect measures of product.
There are many factors that can affect the software work so metrics should not be used to compare individuals or teams.

Size oriented software metrics are derived by normalizing quality measures by considering size of the software that is produced. Lines of code is chosen as the normalization value to develop metrics that can get absorbed with similar metrics from other projects. Size oriented metrics are widely used but there is always a debate about their validity and applicability continues.

Function oriented metrics uses measure of functionality that is delivered by an application as a normalization value. Function point metric is based on characteristics of software's information domain and complexity. Function point is language independent and it is based on data that is likely to be known early in evolution.

The quality of the design and the language used to implement the software defines the relationship between lines of code and function points. Function points and LOC based metrics are exact predictor of software development effort and cost.