University of Southern California Center for Software Engineering C S E USC Using COCOMO for Software Decisions - from COCOMO II Book, Section 2.6, 6.5 Marilee Wheaton Csci 510

University of Southern California Center for Software Engineering C S E USC 2 Outline COCOMO II Objective: Decision Support Example Company: UST, Inc. Auto Parts Frequent Software Decisions –Investment; Business Case Analysis –Setting Project Budgets and Schedules –Performing Tradeoff Analysis –Cost Risk Management –Development vs. Reuse –Legacy Software Phaseout –Software Process Improvement Software Organizational Decisions Conclusions

University of Southern California Center for Software Engineering C S E USC 3 UST, Inc. Auto Parts Company Large manufacturing company –200-person software organization Considering development of manufacturing control system (MCS) –100 KSLOC; nominal drivers ratings; $8K/PM Scaling exponent E= ( )=1.10 Estimated effort and cost Effort=2.94*100^1.10 = 466 PM Cost = 466 PM * $8K/PM = $3.728M

University of Southern California Center for Software Engineering C S E USC 4 UST, Inc. Auto Parts Company (Cont.) Plus Inception (6%) and Transition (12%) costs –Acquisition Cost = $3.728*1.18 = $4.4M Annual Maintenance Cost Annual Software Change = 100*(0.20) = 20KSLOC Cost = 2.94*(20)^1.10*$8K=$635K

University of Southern California Center for Software Engineering C S E USC 5 MCS Business Case Analysis MCS estimate to reduce manufacturing inventory 20% –Enables more just-in-time arrival of suppliers components Current Manufacturing inventory valued at $80M Inventory carrying costs average around 25% –Inventory control, property taxes, capital costs, etc. MCS savings in reduced inventory carrying costs = ($80)*(0.25)*(0.2)=$4M/Year MCS savings subtracts software maintenance cost =$4M-0.635M=$3.365M 5-year-ROI=5* =$3.365M/$4.4M = 3.8 –Well worth the investment

University of Southern California Center for Software Engineering C S E USC 6 Setting Project Budget and Schedules Schedule TDEV=3.67*(PM)^[ *(E-0.91)] = 3.67*(466)^0.318 = 26 month Constructive phase schedule and effort (Table A.5) –Effort=0.76*(466)=354 PM; Schedule=0.625*26=16.25 Month; –Staff Level = 354/16.25=28.8 people Staff needed for construction activities (Table A, 11) –Requirements = 21.8*0.08=1.7 people –Product Design =21.8*0.16=3.5 people

University of Southern California Center for Software Engineering C S E USC 7 Performing Tradeoff Analysis MCS Life-cycle Costs vs. Reliability Level RELY RatingVery Low LowNominalHighVery High Dev. Effort Mult Dev. Cost ($K) Maint. Effort Mult Maint. Cost (*2 for Nominal) 11,88010,1208,8008,6249,680 Life-cycle Cost15,48814,16813,20013,46415,224

University of Southern California Center for Software Engineering C S E USC 8 Value-Based Tradeoff Analysis Cost of Downtime = $38*(Downtime) RELY RatingVery Low LowNominalHighVery High Mean Time to Failure (hr) ,000300,000 Mean Time to Repair (hr) Avail= MTBF/(MTBF+MTTR) Downtime Cost=$38*Downtime $1500M$300M$10M$0.3M$0.01M SW Life-cycle Cost $15.5M$14.2M$13.2M$13.5M$15.2M Ownership Cost $1515M$314M$23.2M$13.8M$15.2M

University of Southern California Center for Software Engineering C S E USC 9 Outline COCOMO II Objective: Decision Support Example Company: UST, Inc. Auto Parts Frequent Software Decisions –Investment; Business Case Analysis –Setting Project Budgets and Schedules –Performing Tradeoff Analysis –Cost Risk Management –Development vs. Reuse –Legacy Software Phaseout –Software Process Improvement Software Organizational Decisions Conclusions

University of Southern California Center for Software Engineering C S E USC 10 Cost Risk Management Risk reserve for requirement volatility –Estimate as high as 15% –Resulting cost = 2.94*(100+15)^1.10*($8k)=$5130k –Risk reserve = $5130k – 4400k = $730k Risk reserve for less experienced personal –Average applications, Platform experience ½-level lower –Resulting cost = $4400k*(1.05)*(1.045)=$4828k –Risk reserve = $428k

University of Southern California Center for Software Engineering C S E USC 11 Development vs. Reuse Possibility of reusing a 40 KSLOC component Reuse parameters not a strong match –% design modified DM=40 –% code modified CM=50 –% integration redone IM=100 –Understanding penalty SU=50 –SW unfamiliarity UMFM=1.0 –Adaptation of assessment AA =5% Equivalent new lines of code = 40k*[(0.4*40+0.3*50+0.3*100)/100+(5+50*1.0)/100] = 40k * ( ) = 46.4KSLOC Not a good decision to reuse

University of Southern California Center for Software Engineering C S E USC 12 Legacy Software Phaseout Candidate: Corporate property accounting system –50K COBOL program; 20% annual charge (10K) –SU = 50: poorly structured, documented –UNFM = 0.7: few people familiar with code Equivalent annual maintenance size = 10KSLOC * [1 + (50*0.7)/100] = 13.5 KSLOC/year 3 years: 40.5K SLOC Replacement could use MCS GUI, DBMS –Only 20 KSLOC of new software needed –SU = 25: better structured, documented –UNFM = 0.4: New developers familiar with the code Equivalent annual maintenance size = 20KSLOC * [1+ (25*0.4)/100] = 4.4 KSLOC/year 3 years + development = 3* = 33.2 KSLOC –Better to phase out and replace legacy SW

University of Southern California Center for Software Engineering C S E USC 13 Software Process Improvement UST currently at Process maturity Level 2 –Planning & control, config. Management, guality assurance Cost to achieve level 3 (process group, training, product engr.) –Process group: (2yr)*(4 persons)*($96K/yr) = $768K –Training: (200 persons)*(3weeks)*($96K/Ω) = $1108K –Contingency = $124K; Total = = $2000K Benefit: scale exponent reduced by =.0156, to 1.10 – = –From 100^1.10 = to 100^ = 147.5, or 7% less effort –Annual savings = (200 persons)*(96K/yr)(.07)=$1344K 5 year ROI = [5*$1344K-$2000K]/$2000K = 2.36 –Again, well worth the investment

University of Southern California Center for Software Engineering C S E USC 14 Conclusions COCOMO II is useful in many decision situations –Support objective discussion and negotiation Most analysis can be done with hand calculator –Simpler, easier to explain Usage builds shared understanding and trust