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The ISBSG s analysis revealed that mainframe projects make more frequent use of methodologies The methodologies used on mainframe
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Factors that Influence productivity
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projects are likely to be purchased but then applied with some customization In contrast, PC projects make infrequent use of methodologies, and the methodologies that are used on PC projects are likely to be written in-house Purchased methodologies are almost always comprehensive and detailed Projects that follow them tend to produce a wide range of documents, such as specifications, designs, plans, change and issue lists, and test cases In contrast, in-house methodologies tend to focus only on key parts of a software project s life cycle Projects that follow in-house methodologies, or no methodology at all, tend to produce fewer documents A software project that produces fewer documents is likely to have a better (lower) hours per function point value than a project that produces many documents Of course, software projects produce documents in order to communicate with multiple business units and to avoid the cost of rework resulting from poor specification, design, and planning So there is likely to be a trade-off between project delivery rate and defects delivered2
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The PC environment shows the best (that is, lowest) project delivery rates of the three platforms Mainframe environments have the highest project delivery rates Multiplatform environments have similar project delivery rates to PCs If you use the regression equations provided in the appendixes, ensure that you choose the equations appropriate for the platform/environment that you are developing on
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Project delivery rates for new developments are significantly different from those for enhancements New developments average 8 to 12 hours per function point, and enhancements average 12 to 16 hours per function point The difference is probably due to factors other than the development type; for example, a much greater proportion of enhancements were mainframe projects, whereas new developments include more PC projects
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4GLs as a whole have significantly better (lower) project delivery rates than 3GLs
Application Type
Management information systems (MISs) show better (that is, lower) project development rates than do transaction/production systems
Refer to the ISBSG Special Report: Techniques and Tools Special Report II
practical Software project estimation
Application Architecture
PDR tends to be best for multitier systems and worst for client-server systems, with stand-alone systems falling somewhere in between The difference is probably due to factors other than the architecture; in particular, in the projects studied here the maximum team size happens to be greatest for client-server projects and smallest for multitier systems
Other Project-Specific Characteristics Known to Influence PDR
The list of project-specific characteristics known to influence software development productivity (and hence total effort) that have not been the subject of the ISBSG statistical analysis includes Intrinsic team skills Staff experience levels with the technology Level of technical innovation Use of contractors/part-time resources Product performance Quality attributes required Budget constraints Developers environment Stability of requirements These are some of the project-specific characteristics not included directly in the common estimation techniques, but which you must take into account when calculating the final total project effort or cost estimate Several different estimation methods are available that include these project-specific characteristics: COCOMO II: 23 productivity factors IFPUG value adjusted factor (VAF): 14 factors3 FiSMA ND21 situation analysis for new development: 21 factors All these methods ask the user to select from a list of the projectspecific characteristics applicable to their project Based on the selected values, the method gives a coefficient figure, which is a multiplier for the preliminary effort estimate counted from the software size and delivery rate Table 2-5 shows the lists of productivity
Note that the VAF is likely to be phased out in the future
COCOMO II Project scale factor attributes: 1 Precedentedness 2 Development flexibility 3 Architecture/risk resolution 4 Team cohesion 5 Process maturity 6 Required software reliability 7 Database size 8 Product complexity 9 Develop for reuse 10 Documentation match to life-cycle needs 11 Execution time constraint 12 Main storage constraint 13 Platform volatility 14 Analysis personnel capability 15 Programmer personnel capability 16 Personnel continuity 17 Applications experience 18 Personnel platform experience 19 Language and tool experience 20 Use of software tools 21 Multisite development 22 Required development schedule 23 Other
VAF General system characteristics: 1 Data communications 2 Distributed data processing 3 Performance 4 Heavily used configuration 5 Transaction rate 6 Online data entry 7 End-user efficiency 8 Online update 9 Complex processing 10 Reusability 11 Installation ease 12 Operational ease 13 Multiple sites 14 Facilitate change
FiSMA ND21 Project organizational factors: 1 Involvement of the customer representatives 2 Performance and availability of the development environment 3 Availability of IT staff 4 Number of stakeholders 5 Pressure on schedule Process factors: 6 Impact of standards 7 Impact of methods 8 Impact of tools 9 Level of change management 10 Maturity of software development process Product quality factors: 11 Functionality requirements 12 Reliability requirements 13 Usability requirements 14 Efficiency requirements 15 Maintainability requirements 16 Portability requirements People factors: 17 Analysis skills of staff 18 Application knowledge of staff 19 Tool skills of staff 20 Experience of project management 21 Team skills of the project team
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