University of Southern California Center for Systems and Software Engineering © 2010, USC-CSSE 1 Trends in Productivity and COCOMO Cost Drivers over the Years Vu Nguyen Center for Systems and Software Engineering (CSSE) CSSE Annual Research Review 2010 Mar 9 th, 2010

University of Southern California Center for Systems and Software Engineering © 2010, USC-CSSE 2 Outline Objectives and Background Productivity Trend Discussions and Conclusions Cost Driver Trends

University of Southern California Center for Systems and Software Engineering © 2010, USC-CSSE 3 Objectives Analysis of Productivity –How the productivity of the COCOMO data projects has changed over the years –What caused the changes in productivity Analysis of COCOMO cost drivers –How cost driver ratings have changed over the years –Are there any implications from these changes

University of Southern California Center for Systems and Software Engineering © 2010, USC-CSSE 4 Estimation models need upgrading It has been 10 years since the release of COCOMO II.2000 –Data collected during 1970 – 1999 Software engineering practices and technologies are changing –Process: CMM  CMMI, ICM, agile methods –Tools are more sophisticated –Advanced communication facility Improved storage and processing capability

University of Southern California Center for Systems and Software Engineering © 2010, USC-CSSE 5 COCOMO II Formula Effort estimate (PM) –COCOMO II 2000: A and B constants were calibrated using 161 data points with A = 2.94 and B = 0.91 Productivity = Constant A is considered as the inverse of adjusted productivity

University of Southern California Center for Systems and Software Engineering © 2010, USC-CSSE 6 COCOMO Data Projects Over the Five-year Periods Dataset has 341 projects completed between 1970 and 2009 –161 used for calibrating COCOMO II 2000 –149 completed since 2000

University of Southern California Center for Systems and Software Engineering © 2010, USC-CSSE 7 Outline Objectives and Background Productivity Trend Discussions and Conclusions Cost Driver Trends

University of Southern California Center for Systems and Software Engineering © 2010, USC-CSSE 8 Average productivity is increasing over the periods Two productivity increasing trends exist: 1970 – 1994 and 1995 – Five-year Periods KSLOC per PM productivity trends largely explained by cost drivers and scale factors Post-2000 productivity trends not explained by cost drivers and scale factors

University of Southern California Center for Systems and Software Engineering © 2010, USC-CSSE 9 Effort Multipliers and Scale Factors EM’s and SF’s don’t change sharply as does the productivity over the periods EAF Sum of Scale Factors Effort Adjustment Factor (EAF) or ∏EM Sum of Scale Factors (  SF)

University of Southern California Center for Systems and Software Engineering © 2010, USC-CSSE 10 Constant A generally decreases over the periods Calibrate the constant A while stationing B = 0.91 Constant A is the inverse of adjusted productivity –adjusts the productivity with SF’s and EM’s Constant A decreases over the periods 50% decrease over the post period

University of Southern California Center for Systems and Software Engineering © 2010, USC-CSSE 11 Outline Objectives and Background Productivity Trend Discussions and Conclusions Cost Driver Trends

University of Southern California Center for Systems and Software Engineering © 2010, USC-CSSE 12 Correlation between cost drivers and completion years Trends in cost drivers –Cost drivers unchanged TEAM, FLEX, RESL, RELY, CPLX, ACAP, PCAP, RUSE, DOCU, PCON, SITE, SCED –Increasing trends: increasing effort DATA, APEX –Decreasing trends: decreasing effort PMAT, TOOL, PREC,TIME, STOR, PLEX, LTEX, PVOL

University of Southern California Center for Systems and Software Engineering © 2010, USC-CSSE 13 Application and Platform Experience Platform and language experience has increased while application experience decreased –Programmers might have moved projects more often in more recent years

University of Southern California Center for Systems and Software Engineering © 2010, USC-CSSE 14 Use of Tools and Process Maturity Use of Tools and Process Maturity have increased significantly

University of Southern California Center for Systems and Software Engineering © 2010, USC-CSSE 15 Storage and Time Constraints Storage and Time are less constrained than they were

University of Southern California Center for Systems and Software Engineering © 2010, USC-CSSE 16 Outline Objectives and Background Productivity Trend Discussions and Conclusions Cost Driver Trends

University of Southern California Center for Systems and Software Engineering © 2010, USC-CSSE 17 Discussions Productivity has doubled over the last 40 years –But scale factors and effort multipliers did not fully characterize this increase Hypotheses/questions for explanation –Is standard for rating personnel factors different among the organizations? –Were automatically translated code reported as new code? –Were reused code reported as new code? –Are the ranges of some cost drivers not large enough? Improvement in tools (TOOL) only contributes to 20% reduction in effort –Are more lightweight projects being reported? Documentation relative to life-cycle needs

University of Southern California Center for Systems and Software Engineering © 2010, USC-CSSE 18 Conclusions Productivity is generally increasing over the 40- year period –SF’s and EM’s only partially explain this improvement Advancements in processes and technologies affect some cost drivers –But majority of the cost driver ratings are unchanged Changes in productivity and cost drivers indicate that estimation models should recalibrate regularly

University of Southern California Center for Systems and Software Engineering © 2010, USC-CSSE 19 Thank You