Pm Scheduling Cost Pricing
- 2. Software Contracting LS 15% $ Value created company development Cost Profit bids
- 3. Software Contracting HS $ Value created Cost Profit company development bids
- 4. New Software Product Off-the-shelf product value created (product) -> pricing competition/substitutes comparable features development budget < price * estimated sales - overhead ASP software provided as service (online) Shareware wider distribution ability to test/enter a new market, with low risk slash the distribution costs of the conventional retail software channel quick releases Open Source/Freeware Software Consulting
- 5. Types of Revenues Software Development software contracting, product development Install/Setup Training Call Center Maintenance (upgrades) Software Service (ASP)
- 7. Gantt Chart/Critical Path PBS WBS
- 8. Software Project Management Plan - IEEE 1058 Title Page Signature Page Change History Preface Table of contents List of figures List of tables Overview Project summary Evolution of the plan
- 9. Software Project Management Plan - IEEE 1058 References Definitions Project organization External Interfaces Internal structure Roles and responsabilities Managerial process plan Start-up plan Estimation plan Schedule allocation Resource acquisition plan Project staff training plan
- 10. Software Project Management Plan - IEEE 1058 2. Work plan - (WBS structure) Work activities Schedule allocation Resource allocation Budget allocation 3. Control plan Requirements control plan Schedule control plan Budget control plan Quality control plan Reporting plan Metrics collection plan 4. Risk management plan 5. Closeout plan
- 11. Software Project Management Plan - IEEE 1058 6. Technical process plans Process model Methods, tools, and techniques Infrastructure plan Product acceptance plan 7. Supporting process plans Configuration management plan Verification and validation plan Documentation plan Quality assurance plan Reviews and audits Problem resolution plan Subcontractor management team Process improvement plan 8. Additional plans Annexes Index
- 12. Estimation Methods If history of projects: Estimation (time, cost, resources) Analogy Otherwise: Expert/Team Guessing Algorithmic Code size based Regression based: COCOMO Functionality based Function-point count Object points
- 13. Algorithmic Cost Modelling Effort = A x Size B x M A is a constant factor which depends on the software organization and the software application Size is either code size or function or object point estimate. B is between 1 and 1.5, costs are non linear with the project size M is a multiplier made up by combining diferent process, product and development attributes. 4x 2x 0.5x 0.25x x Fesability Requirements Design Code Software project cost estimation accuracy
- 14. COCOMO Estimation (basic) Organic mode -small teams -familiar environment -familiar applications Semi-detached mode -experienced and inexperienced staff Embedded mode -tight constraints -complex projects PM = 2.4(KDSI) 1.05 TDEV = 2.5(PM) 0.38 PM = 3.4(KDSI) 1.12 TDEV = 2.5(PM) 0.35 PM = 3.6(KDSI) 1.20 TDEV = 2.5(PM) 0.32 KDSI = number of thousands delivered instructions PM = number of persons month TDEV = development time (months) N = (PM/TDEV) number of personnel
- 15. Example For a 50.000 DSI project, organic mode (small team, familiar environment and applications): PM = 2.4(50) 1.05 = 146 p.m. TDEV = 2.5(146) 0.38 = 17 months N = (PM/TDEV) = (146/17) = 9 people
- 16. Attribute description Attributes Cost Description Driver Product attribute RELY Required software reliability. DATA Database size(bytes, 10DSI L, 10-100DSI N, >1000DSI VH) CPLX Product complexity (simple I/O, multi-file I/O, library) Computer attribute TIME Execution time constraints (N >50%, >95% EH) STOR Storage constraint (less than half available N) VIRT Virtual machine volatility. (once year L, 6 months N) TURN Computer turnaround time (>12h VH) Personnel attribute ACAP Annalist capability (one year N, >3 year VH) AEXP Application experience (one year N, >3 year VH) PCAP Programmer capability (one year N, >3 year VH) VEXP Virtual machine experience (one year N, >3 year VH) LEXP Programming language experience (one year N, >3 year VH) Project attribute MODP Modern programming practices (no use L) TOOL Software tools (implementation, testing, debugging N) SCED Required development schedule (acceleratedL, extendedVH)
- 17. Attribute Table Attributes Cost Ratings Driver VL L N H VH EH Product attribute RELY 0.75 0.88 1.00 1.15 1.40 - DATA - 0.94 1.00 1.08 1.16 - CPLX 0.70 0.85 1.00 1.15 1.30 1.65 Computer attribute TIME - - 1.00 1.11 1.30 1.66 STOR - - 1.00 1.06 1.21 1.56 VIRT - 0.87 1.00 1.15 1.30 - TURN - 0.87 1.00 1.07 1.15 - Personnel attribute ACAP 1.46 1.19 1.00 0.91 0.82 - AEXP 1.29 1.13 1.00 0.91 0.82 - PCAP 1.42 1.17 1.00 0.86 0.70 - VEXP 1.21 1.10 1.00 0.90 - - LEXP 1.14 1.07 1.00 0.95 - - Project attribute MODP 1.24 1.10 1.00 0.91 0.82 - TOOL 1.24 1.10 1.00 0.91 0.83 - SCED 1.23 1.08 1.00 1.04 1.10 -
- 18. Investment tradeoff Attributes RELY 1.15, STOR 1.21, TIME 1.10 TOOL 1.10 PM = 146 * 1.15 * 1.21 * 1.10 * 1.10 = 246 p.m. with $4000/month, C = 246 * $4000 = $984.000 with $50.000 investment in a software tool, RELY 1.15, STOR 1.0, TIME 1.00 TOOL 1.00 PM = 146 * 1.15 * 1.00 * 1.00 * 1.00 = 168 p.m. C = $4000 * 168 = $672.000
- 19. Function-point count Language-independent Productivity expressed as function points produced per person-month Biased towards data-processing systems Number of function points in a program: External inputs and outputs User interactions External interfaces Files used by the system UFC = SUM(number of elements of given type) x (weight) The function-point count = UFC x project complexity factors
- 20. Object points For 4GL or compatible languages Number of object points: simple moderate complex Easyer to estimate from a high-level software specification Code size = AVC x Number of function points AVC (200-300 LOC/FT in assmebly to 2-40 LOC/FP in a forth generation language) 10 10 10 Number of separate 3GL moduled produced to suplement the 4GL code 8 5 2 Number of reports produced 3 2 1 Number of separate screens are displayed
- 21. Factors affecting software engineering productivity Factor Description Application experience Knowledge of the application domain Process quality The development process has significant effect Project size More overhead for larger projects Technology support CASE tools; supportive SCMS Working environment Quite work environment; private work areas