Symposium PresentationApproved for public release; distribution is unlimited

Biancalana, Nickolas A.

Drylie, Scott T.

Fass, David

Ritschel, Jonathan D.

White, Edward D.

English

Calhoun, Institutional Archive of the Naval Postgraduate School

Calhoun: The NPS Institutional ArchiveDSpace RepositoryAcquisition Research Program Acquisition Research Symposium2022-05-06Improving Software Cost EstimatingTechniques in Defense ProgramsBiancalana, Nickolas A.; Ritschel, Jonathan D.; Drylie,Scott T.; Fass, David; White, Edward D.Monterey, California. Naval Postgraduate Schoolhttp://hdl.handle.net/10945/70250Copyright is reserved by the copyright ownerDownloaded from NPS Archive: CalhounImproving Software Cost Estimating Methods in Defense Programs1Lt Nick BiancalanaSAF/FMCSOverview Main Topic Using historical cost and ESLOC data to create distributions to estimate and simulate future values Formulate specific distributions for combinations of characteristics Assumption Information known at the beginning of the program Commodity, system type, service, contractor, contract type Research Questions Shapes and parameters of distributions that map each data subset How does software size and cost change within characteristics? Methods Incremental analysis Compare median values Statistical tests for differencesData 42 projects 314 data points (Cost/ESLOC) 351 data points (ESLOC)  Similar proportions for data pointsResults (Cost/ESLOC) Analysis performed for nearly all combinations of characteristics for both Cost/ESLOC and ESLOCCommodity/Contractor Contractor 1 Contractor 2 Contractor 3 Contractor 4 Contractor 5Aircraft 0.183 0.185 0.174 0.088b 0.043bEAS 0.278 0.177a 0.056 0.134a 0.071aMissile 0.708 0.511a,b,cRotary Wing 0.202 0.467 0.218 0.327Space 0.798 1.331a 0.131 1.051a,b 0.078UAV 0.173 0.141cN 96 46 89 52 68Median 0.205 0.377 0.119 0.28 0.122KW 0.303 0.004 0.05 0.001 0.008Note: Commodities that share a letter within the same contractor are members of a Steel-Dwass PairResults Distributions for each division of dataset Space and Missile most expensive commodities, Aircraft largest Cost and ESLOC vary within the same program characteristics Some commodities are more expensive depending on contractor Fewer effects for ESLOC EAS is cheapest yet also largest for the Army Specific Contract Type can impact size/cost Impacts mostly lost when contract type is generalized EAS, Missile, and UAV experienced different ESLOC depending on service Arsenal of distributions for all situations Decision toolSpecific Distributions –Cost/ESLOC Aircraft EAS Missile Rotary Wing Space UAV Commodity Service Contractor Contract Type Distribution C1 C3 C4 C5 C6 C2 Army SP8 Air Force SP7 Contractor 5 SP3 MC SP12 Contractor 2 SP1 Contractor 4 SP2 MC SP13 Questions

Improving Software Cost Estimating Techniques in Defense Programs

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Improving Software Cost Estimating Techniques in Defense Programs

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