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Software estimates: how accurate are they
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Although the findings summarized below pertain to this particular collection of projects, the ISBSG believes that they provide a good picture of the state of estimates in good software projects Size approximation techniques: When a size approximation is available, it is usually used to help estimate delivery date, effort, and/or cost If a size approximation is not available, work breakdown techniques are used Functional size based techniques generally produce slightly more accurate estimates Accuracy of different types of estimate: Delivery date is often estimated well Over half of the projects were delivered early or on time, and 70 percent were delivered no later than 1 month late Once a project is more than a month late, the median error is about 25 months overrun Projects planned to run for a year or more are delivered on time; the worst errors occur in projects planned to run for about 4 to 6 months Effort is estimated worst Over half of projects underestimate effort by at least 10 percent Some enormous errors occur, with actual effort up to 80 times the estimate On average, effort is underestimated by about 50 percent There are no patterns to explain which types of projects are estimated better or worse than other types Errors in cost estimates are closely related to errors in effort estimates, supporting the intuition that effort largely determines cost But cost estimates are not generally as inaccurate as effort estimates This may be because extra effort recorded against a project is unpaid There is no relationship between project delivery rate and the accuracy of estimates For everything except effort, half or more of the projects are estimated accurately; for effort, that drops to a third of the projects Overestimates and underestimates: A late project averages an overrun of 2 to 3 months If effort is underestimated, the average overrun is 67 to 100 percent The average across all projects is to underestimate effort by 50 percent If cost is underestimated, the average overrun is 25 to 30 percent Overestimates are rare, usually small, and occur in small projects When anything is overestimated, it is probably by about 20 percent
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practical Software project estimation
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Factors influencing accuracy: As a general guide, smaller projects are more likely to be estimated accurately or overestimated Larger and, more particularly, longer projects are more likely to be underestimated Estimates appear to be less accurate for projects involving newer technologies, and for those with a large and varied user base Use the information provided in this chapter to guide both your approach to preparing estimates for a project, and the allowances that you make to your estimate for factors specific to your project Use both macro- and micro-estimating techniques to obtain the most reliable estimate
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his chapter introduces the concept that functional size measurement of software can be performed at different levels of accuracy to suit different purposes It will introduce the concept of approximating size rather than measuring it Approximating size techniques can be used when there is insufficient opportunity, time, or perhaps information to perform a detailed size measurement Functional size measurement (FSM)1 is the most accepted approach to measuring the size of a software project Standard functional size measurement methods2 are often unsuitable to be used early in the life of a project3 because they require some kind of structured analysis before identifying and classifying functions, counting elementary components, and performing numerical transformations, in line with their specific counting rules Although simple in concept, functional size measurement is not a trivial task However, there are several simple but effective ways of roughly determining the functional size of a project without doing a detailed functional size measurement The resulting approximated size is much less accurate than the measured size, but the error range
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ISO/IEC 14143-1:2007 Software Engineering Software measurement Functional size measurement Definition of concepts ISO14143-6 Information technology Software measurement Functional size measurement Part 6: Guide for use of ISO/IEC 14143 series and related international standards This chapter assumes the functional size of the software system being developed as the main cost driver of the project Physical dimensions (for example, LOC) are excluded as estimating factors, due to the higher difficulty in estimating those dimensions in the initial phases of the project when nothing has been produced or even designed
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