Fundamentals of Function Point Analysis Part I


Abstract

Systems continue to grow in size and complexity. They are becoming more and more difficult to understand. Improvement of coding tools allows software developers to produce large amounts of software to meet an ever expanding need from users. As systems grow a method to understand and communicate size needs to be used. Function Point Analysis is a structured technique of problem solving. It is a method to break systems into smaller components, so they can be better understood and analyzed.

Function points are a unit measure for software much like an hour is to measuring time, miles are to measuring distance or Celsius is to measuring temperature. Function Points are an ordinal measure much like other measures such as kilometers, Fahrenheit, hours, so on and so forth. Count calculation I will cover in Part II.

Introduction

Human beings solve problems by breaking them into smaller understandable pieces. Problems that may appear to be difficult are simple once they are broken into smaller parts -- dissected into classes. Classifying things, placing them in this or that category is a familiar process. Everyone does it at one time or another -- shopkeepers when they take stock of what is on their shelves, librarians when they catalog books, secretaries when they file letters or documents. When objects to be classified are the contents of systems, a set of definitions and rules must be used to place these objects into the appropriate category, a scheme of classification. Function Point Analysis is a structured technique of classifying components of a system. It is a method to break systems into smaller components, so they can be better understood and analyzed. It provides a structured technique for problem solving.

In the world of Function Point Analysis, systems are divided into five large classes and general system characteristics. The first three classes or components are External Inputs, External Outputs and External Inquires each of these components transacts against files therefore they are called transactions. The next two Internal Logical Files and External Interface Files are where data is stored that is combined to form logical information. The general system characteristics assess the general functionality of the system.

Objectives of Function Point Analysis

Frequently the term end user or user is used without specifying what is meant. In this case, the user is a sophisticated user. Someone that would understand the system from a functional perspective -- more than likely someone that would provide requirements or does acceptance testing.

Since Function Points measures systems from a functional perspective they are independent of technology. Regardless of language, development method, or hardware platform used, the number of function points for a system will remain constant. The only variable is the amount of effort needed to deliver a given set of function points; therefore, Function Point Analysis can be used to determine whether a tool, an environment, a language is more productive compared with others within an organization or among organizations. This is a critical point and one of the greatest values of Function Point Analysis.

Function Point Analysis can provide a mechanism to track and monitor scope creep. Function Point Counts at the end of requirements, analysis, design, code; testing and implementation can be compared. The function point count at the end of requirements and/or designs can be compared to function points actually delivered. If the project has grown, there has been scope creep. The amount of growth is an indication of how well requirements were gathered by and/or communicated to the project team. If the amount of growth of projects declines over time it is a natural assumption that communication with the user has improved.

The Five Major Components

Since it is common for computer systems to interact with other computer systems, a boundary must be drawn around each system to be measured prior to classifying components. This boundary must be drawn according to the user's point of view. In short, the boundary indicates the border between the project or application being measured and the external applications or user domain. Once the border has been established, components can be classified, ranked and tallied.

  1. External Inputs (EI) - is an elementary process in which data crosses the boundary from outside to inside. This data may come from a data input screen or another application. The data may be used to maintain one or more internal logical files. The data can be either control information or business information. If the data is control information it does not have to update an internal logical file.
  2. External Outputs (EO) - an elementary process in which derived data passes across the boundary from inside to outside. Additionally, an EO may update an ILF. The data creates reports or output files sent to other applications. These reports and files are created from one or more internal logical files and external interface file.
  3. External Inquiry (EQ) - an elementary process with both input and output components that result in data retrieval from one or more internal logical files and external interface files. The input process does not update any Internal Logical Files, and the output side does not contain derived data.
  4. Internal Logical Files (ILF's) - a user identifiable group of logically related data that resides entirely within the applications boundary and is maintained through external inputs.
  5. External Interface Files (EIF's) - a user identifiable group of logically related data that is used for reference purposes only. The data resides entirely outside the application and is maintained by another application. The external interface file is an internal logical file for another application.

All components are rated as Low, Average or High

After the components have been classified as one of the five major components (EI's, EO's, EQ's, ILF's or EIF's), a ranking of low, average or high is assigned. For transactions (EI's, EO's, EQ's) the ranking is based upon the number of files updated or referenced (FTR's) and the number of data element types (DET's). For both ILF's and EIF's files the ranking is based upon record element types (RET's) and data element types (DET's). A record element type is a user recognizable subgroup of data elements within an ILF or EIF. A data element type is a unique user recognizable, non recursive, field.

Summary of benefits of Function Point Analysis

  • Function Points can be used to size software applications accurately. Sizing is an important component in determining productivity (outputs/inputs).
  • They can be counted by different people, at different times, to obtain the same measure within a reasonable margin of error.
  • Function Points are easily understood by the non technical user. This helps communicate sizing information to a user or customer. Function Points can be used to determine whether a tool, a language, an environment, is more productive when compared with others.

Conclusions

Function Points are becoming widely accepted as the standard metric for measuring software size. Now that Function Points have made adequate sizing possible, it can now be anticipated that the overall rate of progress in software productivity and software quality will improve. Understanding software size is the key to understanding both productivity and quality. Without a reliable sizing metric relative changes in productivity (Function Points per Work Month) or relative changes in quality (Defects per Function Point) can not be calculated. If relative changes in productivity and quality can be calculated and plotted over time, then focus can be put upon an organizations strengths and weaknesses. Most important, any attempt to correct weaknesses can be measured for effectiveness.

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