MTAT Software Economics. Lecture 5: Software Cost Estimation

Transcription

1 MTAT Software Economics Lecture 5: Software Cost Estimation Marlon Dumas marlon.dumas ät ut. ee

2 Outline Estimating Software Size Estimating Effort Estimating Duration 2

3 For Discussion It is hopeless to accurately estimate software costs. Most often than not, such estimates are wrong. So why should we bother? We have 6 months and 10 analysts/developers, so it will take 6 months and 60 person-months. 3

4 There are lies, dammed lies and statistics. What about a method to estimate software costs from a high-level design, that is: within 20% of the actual size 50% of the time within 30% of the actual size 66% of the time Is this good enough? Can we do better? 4

5 Cone of Uncertainty 5

6 Estimating Size From the early design, you can count the function-points. Can we estimate the size (LOC) from there? Answer: yes, through backfiring Caper Jones s database: > 9000 projects with both function-points and actual LOC Cobol, C 120 LOC/FP Cobol, Fortran 100 LOC/FP Pascal, Ada, (PHP) LOC/FP OO Languages 30 LOC/FP 6

7 Estimating Effort Parkinson's Law If we have 600 personmonths, it will take 600 person-months Estimation by analogy This project is about 20% more complex than the previous one Expert judgement (e.g. based on WBS) Wideband Delphi, Planning Poker Parametric cost models SLIM (Putnam) COCOMO 81 and COCOMO II.2000 (Boehm et al.) No approach is perfect consider combinations. 7

8 Example Analogy/expert-based estimation Wide-Band Delphi Ask each team member their estimate Apply personal experience, Look at completed projects, Extrapolate from modules known to date Collect and share in a meeting: discuss why/ how different people made their estimate Repeat When stable, Size = (H + 4 X Ave. + L)/6 8

9 Productivity estimates Real-time embedded systems: LOC/PM Systems programming (e.g. games, graphics): LOC/PM Commercial applications: LOC/PM Web apps with simple business logic > 500 Heavy transactional business logic, high scalability requirements < 500 From I. Sommerville s Software Engineering 9

10 Estimation Models It took me one month to fully develop (end-toend) a small software application of 1000 LOC Can I develop an application of LOC in 10 months? I have four friends with similar experience as mine, can we develop an application of LOC in 2 months? Hints: Brook s law, Farr & Nanus study 10

11 Non-Linear Productivity There is overwhelming evidence that, except for simple projects, development effort goes up exponentially with size, so this is probably wrong: Effort = P x Size This might be closer to the mark: Effort = A x M x Size B where A is a constant derived from historical data, and M is dependent on each project (effort multiplier), and B is dependent on the complexity of the project 11

12 Diseconomy of Scale Nonlinear relationship when exponent > 1 (c) USC CSSE 12

13 COCOMO Stands for Constructive Cost Model Developed at USC (Barry Boehm et al.) based on a database of projects First version of COCOMO (now COCOMO 81) Most recent version COCOMO II.2000 Based on statistical model building (fitting actual data to equation) Can be calibrated based on company-specific historical data 13

14 Basic COCOMO 81 Complexity Formula Description Organic PM = 2.4 (KLOC)1.05 Well-understood applications developed by small teams with strong prior experience in related systems. Semi- Detached PM = 3.0 (KDSI)1.12 More complex projects where team members may have limited experience of related systems. Embedded PM = 3.6 (KDSI)1.20 Complex projects where the software is constrained by hardware limitations (embedded), needs to respond in real-time, or is critical. 14

15 Intermediate COCOMO 81 E = a KLOC b x EAF EAF is the product of 15 factors Check out Cocomo 81 calculator a Organic Semi-detached Embedded b 15

16 Estimating Time The Cocomo model is calibrated under the assumption of nominal time Nominal time in Cocomo 81 model: D = c E d c d Organic Semi-detached Embedded

17 Nominal versus Optimal Time 17

18 Exercise See exercise Cocomo I on course web page Use the Cocomo 81 calculator (see link on Readings page) 18

19 COCOMO 81 limitations Over time, Cocomo 81s database became outdates by new tools, languages and practices Cocomo 81 was designed for the waterfall model, which was largely superseded by incremental, iterative methods Cocomo 81 had only three possible exponents could not explain for various factors affecting non-linearity of productivity Did not take into account different levels of information available throughout the lifecycle 19

20 Cocomo II.2000 Designed for an iterative development method (MBASE) Calibrated with a larger database (161 projects) More refined set of cost drivers (6-17) Multiple exponential scale drivers: PM = a x Size b x Π EM i (i = 1 to 6 or 17) where a = 2.94 b = x Σ SF j (j = 1 to 5) 20

21 COCOMO 2 models COCOMO 2 incorporates a range of sub-models that produce increasingly detailed software estimates. The sub-models in COCOMO 2 are: Application composition model. Used when software is composed from existing parts. Early design model. Used when requirements are available but design has not yet started (6 cost drivers). Reuse model. Used to compute the effort of integrating reusable components. Post-architecture model. Used once the system architecture has been designed and more information about the system is available (17 cost drivers). From I. Sommerville s Software Engineering 21

22 Use of COCOMO 2 models From I. Sommerville s Software Engineering 22

23 Cost Factors Significant factors of development cost: scale drivers are sources of exponential effort variation cost drivers are sources of linear effort variation product, platform, personnel and project attributes effort multipliers associated with cost driver ratings Defined to be as objective as possible Each factor is rated between very low and very high per rating guidelines relevant effort multipliers adjust the cost up or down (c) USC CSSE 23

24 Scale Drivers Precedentedness (PREC) Degree to which system is new/past experience applies Development Flexibility (FLEX) Need to conform with specified requirements Architecture/Risk Resolution (RESL) Degree of design thoroughness and risk elimination Team Cohesion (TEAM) Need to synchronize stakeholders and minimize conflict Process Maturity (PMAT) SEI CMM process maturity rating (c) USC CSSE 24

25 Scale Factors Sum scale factors W i across all of the factors to determine a scale exponent, B, using B = Σ W i (c) USC CSSE 25

26 Precedentedness (PREC) and Development Flexibility (FLEX) (c) USC CSSE 26

27 Architecture / Risk Resolution (RESL) Use a subjective weighted average of: (c) USC CSSE 27

28 Team Cohesion (TEAM) Use a subjective weighted average of the characteristics to account for project turbulence and entropy due to difficulties in synchronizing the project's stakeholders. Stakeholders include users, customers, developers, maintainers, interfacers, and others (c) USC CSSE 28

29 Process Maturity (PMAT) Two methods based on the Software Engineering Institute's Capability Maturity Model (CMM) Method 1: Overall Maturity Level (CMM Level 1 through 5) Method 2: Key Process Areas (see next slide) (c) USC CSSE 29

30 Key Process Areas Decide the percentage of compliance for each of the KPAs as determined by a judgment-based averaging across the goals for all 18 Key Process Areas. (c) USC CSSE 30

31 Example of Scale Factors A company takes on a project in a new domain. The client has not defined the process to be used and has not allowed time for risk analysis. The company has a CMM level 2 rating. Precedenteness - new project 0.4 Development flexibility - no client involvement - Very high 0.1 Architecture/risk resolution - No risk analysis - V. Low 0.5 Team cohesion - new team nominal 0.3 Process maturity - some control nominal 0.3 Scale factor = From I. Sommerville s Software Engineering 31

32 Cost Drivers (Post-Architectural Model) Product Factors Reliability (RELY) Data (DATA) Complexity (CPLX) Reusability (RUSE) Documentation (DOCU) Platform Factors Time constraint (TIME) Storage constraint (STOR) Platform volatility (PVOL) (c) USC CSSE Personnel factors Analyst capability (ACAP) Program capability (PCAP) Applications experience (APEX) Platform experience (PLEX) Language and tool experience (LTEX) Personnel continuity (PCON) Project Factors Software tools (TOOL) Multisite development (SITE) Required schedule (SCED) 32

33 Example Cost Driver - Required Software Reliability (RELY) Measures the extent to which the software must perform its intended function over a period of time. Ask: what is the effect of a software failure? (c) USC CSSE 33

34 Example Effort Multiplier Values for RELY Very Low Low Nominal High Very High Slight Inconvenience Low, Easily Recoverable Losses Moderate, Easily Recoverable Losses High Financial Loss Risk to Human Life 0.75 E.g. a highly reliable system costs 39% more than a nominally reliable system 1.39/1.0=1.39) or a highly reliable system costs 85% more than a very low reliability system (1.39/.75=1.85) 34 (c) USC CSSE

35 COCOMO II Schedule Estimation D = c x E d x SCED%/100 where c = 3.67 d = x [b ] SCED% = percentage of required schedule compression 35

36 Software Costing and Pricing Caution: All of the above is about effort and schedule estimation From effort and schedule, one can estimate cost Estimate technical effort cost based on PM x monthy total salary cost Add licensing costs and overhead cost for administrative support, infrastructure, etc. But cost price Price depends on many other factors: Risk margin, requirements volatility, competitive advantage, market opportunity, need to win the bid 36

37 Final Word of Caution COCOMO and similar models are just MODELS COCOMO comes calibrated by a set of projects that might not reflect a particular project s context Should be combined with analogy, expert assessment, and continuous cost control 37

38 Homework (10 points) In teams of 4-5 (same teams as for homework 1) Take the Function-Point estimate of homework 1 Make a size estimate Compare this estimate with the actual size Explain the difference, if there is one Make an effort and schedule estimation using Cocomo II (post-architectural). Explain your choice of cost and scale drivers me a 2-5 pages report by Monday 12 Oct. Short 5-minutes presentation on 13 Oct. 38