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CS, NcState
CS, NcState

How to avoid local tuning. Tim Menzies (WVU) Jairus Hihn (JPL) Oussama Elrawas (WVU) Karen Lum (JPL) Dan Baker

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STAR Seeking New Frontiers in Cost Modeling Tim Menzies (WVU) Jairus Hihn (JPL) Oussama Elrawas (WVU) Karen Lum (JPL) Dan Baker (WVU) 22nd International Forum on COCOMO and Systems/Software Cost Modeling (2007)
STAR ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Note ,[object Object],[object Object],[object Object],http://menzies.us/pdf/ 07casease.pdf
Method ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],normalization 0 <= x <= 1
How to Stagger ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Sample runs from STAR (after 500 runs, little improvement) Bad Good Best 10%
Staggering the Tunings Range of effort multipliers (COCOMO) ,[object Object],[object Object],[object Object],[object Object],[object Object],cplx, data, docu pvol, rely, ruse, stor, time Increase effort acap, apex, ltex, pcap, pcon, plex,sced, site,toool decrease effort
After staggering, select best things ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Bad Good 22 good ideas 38 not-so- good ideas
Staggering the inputs : 5 different ways ,[object Object],“ Values” = fixed “ Ranges”= Loose (select within these ranges) 1 2 4 5 3
Making Strategic Decisions Full range of model Constrained by Jairus’ guess at JPL environment
Results : OSP ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Results: OSP2 ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Results: all experiments ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Calibrating/Tuning Models ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Comparisons ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],diff same diff diff same same diff diff same same 63% 66% ground 111%  112%  OSP 125%  99% OSP2 121%  101%  flight 75% 91% all tactical strategic ∑ mre(lc) / ∑ mre(star)

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Star Master Cocomo07

  • 1. STAR Seeking New Frontiers in Cost Modeling Tim Menzies (WVU) Jairus Hihn (JPL) Oussama Elrawas (WVU) Karen Lum (JPL) Dan Baker (WVU) 22nd International Forum on COCOMO and Systems/Software Cost Modeling (2007)
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  • 9. Making Strategic Decisions Full range of model Constrained by Jairus’ guess at JPL environment
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