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Some practical Software Size approximation techniques
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n the startup phase of a software development project, the project sponsor (that is, the customer) wants to know how much the software will cost and how long it will take to develop The developer (in-house or external) needs to establish the approximate size of the software to be developed in order to estimate the effort, cost, and time for planning purposes To satisfy these needs, the size of the software needs to be established, but as it is early in the life cycle of the proposed project, a full function point count is not practical or economically sensible In this chapter we will provide examples of quick sizing techniques for each of the three functional size measurement (FSM) methods most represented in the ISBSG Repository, namely: IFPUG, FiSMA, and COSMIC These are simple but effective ways of roughly determining the functional size of a project
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Note In this chapter you will find some simple but effective ways of
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roughly determining the functional size of a project even when a function point count has not been completed
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Many software size approximation techniques are available in the literature and industry practice The following are just a few examples A number of commercial software metrics consulting companies also provide products and services to assist in size approximation, and some useful sizing tools are now available
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ID DEVXS DEVS DEVM DEVL DEVXL
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Size Class Very Small Small Medium Large Very Large Extremely Large Range (FP) 0 150 150 300 300 600 600 1,200 1,200 5,000 >5,000 ID ENHXS ENHS ENHM ENHL ENHXL ENHXXL Size Class Very Small Small Medium Large Very Large Extremely Large Range (FP) 0 60 60 120 120 240 240 480 480 2,000 >2,000
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DEVXXL
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Table 5-1
Direct Size Approximation
Direct Size Approximation
This method uses statistical distribution of total functional size, both for new development and for enhancement projects An analysis of size distribution of the ISBSG database leads to the size classes reported in Table 5-1 for development ( DEV ) and for enhancement ( ENH ) projects
Example: Direct Size Approximation
Consider the analogy between your team s last five development projects and the planned development project: Projects 1 and 2 fell into size class DEVS (Small), that is, between 150 and 300 FP Projects 3 and 4 fell into size class DEVM (Medium), that is, 300 to 600 FP Project 5 fell into size class DEVL (Large), or 600 to 1,200 FP Interview the project sponsor and analysts from the planned and past projects, and then compare the projects for relative functionality delivered If it is decided that the planned project will have about the same amount of required functionality of projects 3 and 4 (that is, much more than projects 1 and 2 and no more than half of project 5 ), then the most likely size range of the new project will be in the range of projects 3 and 4 (Medium), that is, 300 to 600 FP This analogy-based approach provides only a ballpark project size
Derived Size Approximation
There are a number of ways of deriving an approximate size for a proposed piece of software Here we provide details on three techniques to derive IFPUG, COSMIC and FiSMA sizes We also provide some examples of extrapolative approaches
5:
p r a c t i c a l S o f t w a r e S i z e a p p r o x i m a t i o n te c h n i q u e s
Early Approximation of Functional Size Using ISBSG Data
In the example that follows, we use the known ratios of the IFPUG functional size components from the ISBSG repository data1 It is possible to derive similar functional type relationship patterns for all five FSM methods
Note Function point internal logical files closely resemble a count of
logical entities Often the functional component that you will have the most knowledge of is the internal logical files (ILFs) These closely resemble a count of the entities in a logical data model, modeled to second normal form If a high-level data model has been developed as part of the requirements analysis, this can be used to approximate the number of internal logical files An IFPUG function point count identifies all occurrences of the following five base functional component types, (BFC types): Internal logical files (ILF) within the software Data maintained by processes
External interface files (EIF) Data referenced by processes within the software External inputs (EI) within the software Processes that enter data to be stored
External outputs (EO) Processes that extract derived data to be provided to the user External queries (EQ) Processes that retrieve stored data to be provided to the user From the ISBSG analysis of its history data, it has been observed that the relationships between these five component types remains relatively constant for new development projects and for complete applications; that is, each component type contributes a consistent percentage of function points to the overall total size of the application Investigation into the rationale for the relationships shows good reasons why this consistency exists For any complete application that operates as a software system, the data entered would be expected to be processed and stored for later retrieval It therefore follows that we would expect a strong relationship between input functions (data
Note that this method relies on a single algorithm (most of the commercial products that approximate size rely on between 10 and 40 algorithms) The more relationships that can be analyzed and that can contribute to an approximated size, the more accurate the size estimate will be
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