ECE 355 Software Engineering Project Cost Estimation Instructor

ECE 355: Software Engineering Project Cost Estimation Instructor: Kostas Kontogiannis 1

Course Outline • Introduction to software engineering • Requirements Engineering • Design Basics • Traditional Design • OO Design • Design Patterns • Software Architecture • Design Documentation • Verification & Validation èSoftware Process & Project Management 2

• These slides are based on: – Lecture slides by Ian Summerville, see http: //www. comp. lancs. ac. uk/computing/resources/ser/ – ECE 355 Lecture slides by Sagar Naik 3

Process/Project Management • Project management involves a whole host of issues and skills – – – Effort estimation Staffing Defining and managing the process Scheduling activities Monitoring quality … • Process management at the level of an organization – A software development organization should define, implement and constantly improve their • Software processes • Organizational structure 4

Overview - Software Process & Project Management èCost estimation & Staffing • Project scheduling • Software Life-Cycle Models • Examples of Software processes • Process improvement and Software metrics 5

Software cost estimation • Predicting the resources required for a software development process 6 ©Ian Sommerville 1995

Topics covered • • Productivity Estimation techniques Algorithmic cost modelling Project duration and staffing 7 ©Ian Sommerville 1995

Software cost components • Effort costs (the dominant factor in most projects) – – salaries of engineers involved in the project costs of building, heating, lighting costs of networking and communications costs of shared facilities (e. g library, staff restaurant, etc. ) – costs of pensions, health insurance, etc. • Other costs – Hardware and software costs – Travel and training costs – … 8 ©Ian Sommerville 1995 [modified]

Costing and pricing • There is not a simple relationship between the development cost and the price charged to the customer • Software pricing factors – Market opportunity – low price to enter the market, e. g. , initially “free software” – Cost estimation uncertainty – Contractual terms – Requirements volatility – Financial health – … 9 ©Ian Sommerville 1995 [modified]

Programmer productivity • A measure of the rate at which individual engineers involved in software development produce software and associated documentation – Not quality-oriented although quality assurance is a factor in productivity assessment • Measure useful functionality produced per time unit & programmer 10 ©Ian Sommerville 1995 [modified]

Productivity metrics • Size related measures based on some output from the software process. This may be lines of delivered source code (SLOC), object code instructions, etc. – E. g. , SLOC / person-month • Function-related measures based on an estimate of the functionality of the delivered software. Function-points are the best known of this type of measure – E. g. , FP / person-month 11 ©Ian Sommerville 1995 [modified]

Lines of code • What's a line of code? – Many different ways to count lines (e. g. , with or without comments, counting statements rather than lines, or counting lines in a automatically formatted code) – Need to know the measurement method before comparing SLOC numbers • Assumes linear relationship between system size and volume of documentation 12 ©Ian Sommerville 1995 [modified]

Cross-language comparisons • Problems of LOC-based comparisons – The lower level the language, the more productive the programmer – The more verbose the programmer, the higher the productivity • Function points provide a more accurate measure of productivity than LOC 13 ©Ian Sommerville 1995 [modified]

System development times 14 ©Ian Sommerville 1995

The “Vicious Square” Quality + Scope + Productivity Development time - - + + Cost 15

Quality and productivity • All metrics based on volume/unit time are flawed because they do not take quality into account • Productivity may generally be increased at the cost of quality • It is not clear how productivity/quality metrics are related 16 ©Ian Sommerville 1995

Productivity estimates • Real-time embedded systems, 40 -160 LOC/P-month • Systems programs , 150 -400 LOC/P-month • Commercial applications, 200 -800 LOC/P-month 17 ©Ian Sommerville 1995

The four variables • The main four variables of a project – – Development cost Time Quality Scope • Only three of these variables can be (more or less) freely adjusted • Development cost, time and quality are bad control variables – The number of developers can only be incrementally increased (negative effects beyond the optimal count) – Deadlines are often predetermined externally (e. g. , market window, important presentation) – Low quality upsets customers and developers • Scope is the only real control variable 18

Accuracy of Estimation 4 x 2 x x x – the actual cost of the system Estimates on projects studied by Barry Boehm occupied the area between the curves Feasibility Requirements Design Code Delivery 0. 5 x 0. 25 x As a project progresses, more information about the progress becomes available and the accuracy 19 of estimation can be increased over time.

Estimation techniques • • Expert judgement Estimation by analogy Parkinson's Law Pricing to win Top-down estimation Bottom-up estimation Function point estimation Algorithmic cost modelling 20 ©Ian Sommerville 1995 [modified]

Expert judgement • One or more experts in both software development and the application domain use their experience to predict software costs. Process iterates until some consensus is reached. • Advantages: Relatively cheap estimation method. Can be accurate if experts have direct experience of similar systems • Disadvantages: Very inaccurate if there are no experts! 21 ©Ian Sommerville 1995

Estimation by analogy • The cost of a project is computed by comparing the project to a similar project in the same application domain • Advantages: Accurate if project data available • Disadvantages: Impossible if no comparable project has been tackled. Needs systematically maintained cost database 22 ©Ian Sommerville 1995

Parkinson's Law • The project costs whatever resources are available • Advantages: No overspend • Disadvantages: System is usually unfinished 23 ©Ian Sommerville 1995

Pricing to win • The project costs whatever the customer has to spend on it • Advantages: You get the contract • Disadvantages: The probability that the customer gets the system he or she wants is small. Costs do not accurately reflect the work required 24 ©Ian Sommerville 1995

Top-down estimation • Approaches may be applied using a top-down approach. Start at system level and work out how the system functionality is provided • Takes into account costs such as integration, configuration management and documentation • Can underestimate the cost of solving difficult low-level technical problems 25 ©Ian Sommerville 1995

Bottom-up estimation • Start at the lowest system level. The cost of each component is estimated individually. These costs are summed to give final cost estimate • Accurate method if the system has been designed in detail • May underestimate costs of system level activities such as integration and documentation 26 ©Ian Sommerville 1995

Function Points • The idea of function point was first proposed by Albrecht in 1979. • The function point of a system is a measure of the “functionality” of the system. • Steps – Counting the information domain – counting FPs – Assessing complexity of the software – adjusting FPs – Applying an empirical relationship to come up with LOC or P-months based on the adjusted FPs • This method cannot be performed automatically 27 ©Ian Sommerville 1995

Counting Function Points 28

Counting Function Points • User inputs. Each user input that provides distinct application oriented data to the software is counted. • User outputs. Each user output that provides application oriented information to the user is counted. Individual data items within a report are not counted separately. • User inquiries. This is an on-line input that results in the generation of some response. • Files. Each master file is counted. • External interfaces. Each interface that is used to transmit information to another system is counted. 29

Adjusting Function Points Answer the following questions using a scale of [0 -5]: 0 not important; 5 absolutely essential. We call them influence factors (Fi). 1. Does the system require reliable backup and recovery? 2. Are data communications required? 3. Are there distributed processing functions? 4. Is performance critical? 5. Will the system run in an existing, heavily utilized operational env. ? 6. Does the system require on-line data entry? 30

Adjusting Function Points 7. Does the on-line data entry require the input transaction to be built over multiple screens or operations (user efficiency)? 8. Are the master files updated on-line? 9. Are the inputs, outputs, files, or inquiries complex? 10. Is the internal processing complex? 11. Is the code designed to be reusable? 12. Is installation included in the design? 13. Is the system designed for multiple installations? 14. Is the application designed to facilitate change and ease of use by the user? 31

Map FPs to LOC • Use an empirical relationship – Function point = count total [0. 65 + 0. 01 (sum of the 14 Fi)] – Companies may want to refine their own version • According to a 1989 study, implementing a function point in a given programming language requires the following number of lines of code – – – Assembly C COBOL C++ Visual Basic SQL 320 128 106 64 32 12 • See www. ifpug. org for more information on FP 32

Example: Your PBX project 33

Example: Your PBX project • Total of FPs = 25 • F 4 = 4, F 10 = 4, other Fi’s are set to 0. Sum of all Fi’s = 8. • FP = 25 x (0. 65 + 0. 01 x 8) = 18. 25 • Lines of code in C = 18. 25 x 128 LOC = 2336 LOC • In the past, students have implemented their projects using about 2500 LOC. 34

Algorithmic cost modelling • Cost is estimated as a mathematical function of product, project and process attributes whose values are estimated by project managers • The function is derived from a study of historical costing data • Most commonly used product attribute for cost estimation is LOC (code size) • Most models are basically similar but with different attribute values 35 ©Ian Sommerville 1995

The COCOMO model • Developed at TRW, a US defence contractor • Based on a cost database of more than 60 different projects • Exists in three stages – Basic - Gives a 'ball-park' estimate based on product attributes – Intermediate - Modifies basic estimate using project and process attributes – Advanced - Estimates project phases and parts separately 36 ©Ian Sommerville 1995

Project classes • Organic mode small teams, familiar environment, well-understood applications, no difficult non-functional requirements (EASY) • Semi-detached mode Project team may have experience mixture, system may have more significant non-functional constraints, organization may have less familiarity with application (HARDER) • Embedded Hardware/software systems, tight constraints, unusual for team to have deep application experience (HARD) 37

Basic COCOMO Formula • Organic mode: PM = 2. 4 (KDSI) 1. 05 • Semi-detached mode: PM = 3 (KDSI) 1. 12 • Embedded mode: PM = 3. 6 (KDSI) 1. 2 • KDSI = Kilo Delivered Source Instructions 38 ©Ian Sommerville 1995

Effort estimates 39 ©Ian Sommerville 1995

COCOMO examples • Organic mode project, 32 KLOC – PM = 2. 4 (32) 1. 05 = 91 person months – TDEV = 2. 5 (91) 0. 38 = 14 months – N = 91/15 = 6. 5 people • Embedded mode project, 128 KLOC – PM = 3. 6 (128)1. 2 = 1216 person-months – TDEV = 2. 5 (1216)0. 32 = 24 months – N = 1216/24 = 51 40 ©Ian Sommerville 1995

COCOMO assumptions • Implicit productivity estimate – Organic mode = 16 LOC/day – Embedded mode = 4 LOC/day • Time required is a function of total effort NOT team size • Not clear how to adapt model to personnel availability 41 ©Ian Sommerville 1995

Intermediate COCOMO • Takes basic COCOMO as starting point • Identifies personnel, product, computer and project attributes which affect cost • Multiplies basic cost by attribute multipliers which may increase or decrease costs 42 ©Ian Sommerville 1995

Personnel attributes • Personnel attributes – – – Analyst capability Virtual machine experience Programmer capability Programming language experience Application experience • Product attributes – Reliability requirement – Database size – Product complexity 43 ©Ian Sommerville 1995

Computer attributes • Computer attributes – – Execution time constraints Storage constraints Virtual machine volatility Computer turnaround time • Project attributes – Modern programming practices – Software tools – Required development schedule 44 ©Ian Sommerville 1995

Attribute choice • These are attributes which were found to be significant in one organization with a limited size of project history database • Other attributes may be more significant for other projects • Each organization must identify its own attributes and associated multiplier values 45 ©Ian Sommerville 1995

Model tuning • All numbers in cost model are organization specific. The parameters of the model must be modified to adapt it to local needs • A statistically significant database of detailed cost information is necessary 46 ©Ian Sommerville 1995

Predicted costs 47 ©Ian Sommerville 1995

Example • Embedded software system on microcomputer hardware. • Basic COCOMO predicts a 45 person-month effort requirement • Attributes = RELY (1. 15), STOR (1. 21), TIME (1. 10), TOOL (1. 10) • Intermediate COCOMO predicts – 45*1. 15*1. 21. 1. 10*1. 10 = 76 person-months. • Total cost = 76*$7000 = $532, 000 48 ©Ian Sommerville 1995

Development time estimates • • Organic: TDEV = 2. 5 (PM) 0. 38 Semi-detached: TDEV = 2. 5 (PM) 0. 35 Embedded mode: TDEV = 2. 5 (PM) 0. 32 Personnel requirement: N = PM/TDEV – This last formula needs to be adjusted (see next slide) 49 ©Ian Sommerville 1995 [modified]

Staffing requirements • Staff required can’t be computed by diving the development time by the required schedule • The number of people working on a project varies depending on the phase of the project • The more people who work on the project, the more total effort is usually required • Very rapid build-up of people often correlates with schedule slippage • Adding more people to a delayed project will delay it even more 50 ©Ian Sommerville 1995 [modified]

Rayleigh manpower curves Rc Resources Rc=(t/k 2) e-t 2/2 k 2 k 1 k 2 k 3 51 ©Ian Sommerville 1995

Estimation methods - Summary • Function points – SRS -> LOC – SRS -> PM • COCOMO – LOC -> PM – May use FP as a front-end to COCOMO • COCOMO II – Refined version with different estimation models based on • Requirements (FP->PM), • Early design (FP->PM), and • Architecture (FP or LOC->PM) 52

Estimation methods - Summary • Each method has strengths and weaknesses • Estimation should be based on several methods • If these do not return approximately the same result, there is insufficient information available • Some action should be taken to find out more in order to make more accurate estimates • Pricing to win is sometimes the only applicable method 53 ©Ian Sommerville 1995