Download - CS 540 – Quantitative Software Engineering
![Page 1: CS 540 – Quantitative Software Engineering](https://reader035.vdocument.in/reader035/viewer/2022062222/56815736550346895dc4d84f/html5/thumbnails/1.jpg)
Lecture 6 Estimation
Estimate size, thenEstimate effort, schedule and cost from sizeBound estimates
CS 540 – Quantitative Software Engineering
![Page 2: CS 540 – Quantitative Software Engineering](https://reader035.vdocument.in/reader035/viewer/2022062222/56815736550346895dc4d84f/html5/thumbnails/2.jpg)
Proposed System
Proposed System
Check Status
Create Order
Shipment Notice
Inventory
Assign Inventory to Order
Inventory Assigned
New Inventory for Held Orders
Assign Order to Truck
Truckload Report
Shipping Invoices
Order Update
Order Display
Problem ResolutionDispatch
Accounting
Management Reports
Customer
Check Credit &
Completion
Users
Catalog
Orders
OrderCreation
Credit Check
InventoryAssignment
Held OrderProcessing
Completion
DispatchSupport
ProblemResolution
ManagementReporting
OA&M
![Page 3: CS 540 – Quantitative Software Engineering](https://reader035.vdocument.in/reader035/viewer/2022062222/56815736550346895dc4d84f/html5/thumbnails/3.jpg)
Project Metrics
Cost and schedule estimation Measure progress Calibrate models for future estimating Metric/Scope Manager Product
Number of projects x number of metrics = 15-20
![Page 4: CS 540 – Quantitative Software Engineering](https://reader035.vdocument.in/reader035/viewer/2022062222/56815736550346895dc4d84f/html5/thumbnails/4.jpg)
Approaches to Cost Estimation
• By expert
• By analogies
• Decomposition
• Parkinson’s Law; work expands to fill time available
• Price to win/ customer willingness-to -pay
• Lines of Code
• Function Points
• Mathematical Models: Function Points & COCOMO
![Page 5: CS 540 – Quantitative Software Engineering](https://reader035.vdocument.in/reader035/viewer/2022062222/56815736550346895dc4d84f/html5/thumbnails/5.jpg)
Time
Staff-month
Ttheoretical
75% * Ttheoretical
Impossible design
Linear increase
Boehm: “A project can not be done in less than 75% of theoretical time”
Ttheoretical = 2.5 * 3√staff-months
But, how can I estimate staff months?
![Page 6: CS 540 – Quantitative Software Engineering](https://reader035.vdocument.in/reader035/viewer/2022062222/56815736550346895dc4d84f/html5/thumbnails/6.jpg)
Sizing Software Projects
Effort = (productivity)-1 (size)c
productivity ≡ staff-months/kloc
size ≡ kloc
Staff
months
Lines of Code or
Function Points
500
![Page 7: CS 540 – Quantitative Software Engineering](https://reader035.vdocument.in/reader035/viewer/2022062222/56815736550346895dc4d84f/html5/thumbnails/7.jpg)
Understanding the equations
Consider a transaction project of 38,000 lines of code, what is the shortest time it will take to develop? Module development is about 400 SLOC/staff month
Effort = (productivity)-1 (size)c
= (1/.400 KSLOC/SM) (38 KSLOC)1.02
= 2.5 (38)1.02 ≈ 100 SMMin time = .75 T= (.75)(2.5)(SM)1/3
≈ 1.875(100)1/3
≈ 1.875 x 4.63 ≈ 9 months
![Page 8: CS 540 – Quantitative Software Engineering](https://reader035.vdocument.in/reader035/viewer/2022062222/56815736550346895dc4d84f/html5/thumbnails/8.jpg)
0
2
4
6
8
10
12
20 40 80 160 320 640 1280 2560 5120 10240 20480 40960
Function Points
Bell Laboratories data
Capers Jones data
Prod
uctiv
ity (F
unct
ion
poin
ts /
staf
f mon
th)
Productivity= f(size)
![Page 9: CS 540 – Quantitative Software Engineering](https://reader035.vdocument.in/reader035/viewer/2022062222/56815736550346895dc4d84f/html5/thumbnails/9.jpg)
Lines of Code
LOC ≡ Line of Code KLOC ≡ Thousands of LOC KSLOC ≡ Thousands of Source LOC NCSLOC ≡ New or Changed KSLOC
![Page 10: CS 540 – Quantitative Software Engineering](https://reader035.vdocument.in/reader035/viewer/2022062222/56815736550346895dc4d84f/html5/thumbnails/10.jpg)
Productivity per staff-month:» 50 NCSLOC for OS code (or real-time system)
» 250-500 NCSLOC for intermediary applications (high risk, on-line)
» 500-1000 NCSLOC for normal applications (low risk, on-line)
» 10,000 – 20,000 NCSLOC for reused code
Reuse note: Sometimes, reusing code that does not provide the exact functionality needed can be achieved by reformatting input/output. This decreases performance but dramatically shortens development time.
Bernstein’s rule of thumb
![Page 11: CS 540 – Quantitative Software Engineering](https://reader035.vdocument.in/reader035/viewer/2022062222/56815736550346895dc4d84f/html5/thumbnails/11.jpg)
Productivity: Measured in 2000
Classical rates 130 – 195 NCSLOC
Evolutionary approaches 244 – 325 NCSLOC
New embedded flight software
17 – 105 NCSLOC
![Page 12: CS 540 – Quantitative Software Engineering](https://reader035.vdocument.in/reader035/viewer/2022062222/56815736550346895dc4d84f/html5/thumbnails/12.jpg)
QSE Lambda Protocol
Prospectus Measurable Operational Value Prototyping or Modeling sQFD Schedule, Staffing, Quality Estimates ICED-T Trade-off Analysis
![Page 13: CS 540 – Quantitative Software Engineering](https://reader035.vdocument.in/reader035/viewer/2022062222/56815736550346895dc4d84f/html5/thumbnails/13.jpg)
Heuristics for requirements engineering
Move some of the desired functionality into version 2
Deliver product in stages 0.2, 0.4… Eliminate features Simplify Features Reduce Gold Plating Relax the specific feature specifications
![Page 14: CS 540 – Quantitative Software Engineering](https://reader035.vdocument.in/reader035/viewer/2022062222/56815736550346895dc4d84f/html5/thumbnails/14.jpg)
Function Point (FP) Analysis
Useful during requirement phase Substantial data supports the methodology Software skills and project characteristics are accounted
for in the Adjusted Function Points FP is technology and project process dependent so that
technology changes require recalibration of project models.
Converting Unadjusted FPs (UFP) to LOC for a specific language (technology) and then use a model such as COCOMO.
![Page 15: CS 540 – Quantitative Software Engineering](https://reader035.vdocument.in/reader035/viewer/2022062222/56815736550346895dc4d84f/html5/thumbnails/15.jpg)
Function Point Calculations
Unadjusted Function Points
UFP= 4I + 5O + 4E + 10L + 7F, Where
I ≡ Count of input types that are user inputs and change data structures. O ≡ Count of output typesE ≡ Count of inquiry types or inputs controlling execution.
[think menu selections]L ≡ Count of logical internal files, internal data used by system
[think index files; they are group of logically related data entirely within the applications boundary and maintained by external inputs. ]
F ≡ Count of interfaces data output or shared with another application
Note that the constants in the nominal equation can be calibrated to a specific software product line.
![Page 16: CS 540 – Quantitative Software Engineering](https://reader035.vdocument.in/reader035/viewer/2022062222/56815736550346895dc4d84f/html5/thumbnails/16.jpg)
External Inputs – One updates two files
External Inputs (EI) - when data crosses the boundary from outside to inside. This data may come from a data input screen or another application.
![Page 17: CS 540 – Quantitative Software Engineering](https://reader035.vdocument.in/reader035/viewer/2022062222/56815736550346895dc4d84f/html5/thumbnails/17.jpg)
External Interface Table
For example, EIs that reference or update 2 File Types Referenced (FTR’s) and has 7 data elements would be assigned a ranking of average and associated rating of 4.
File Type References (FTR’s) are the sum of Internal Logical Files referenced or updated and External Interface Files referenced.
![Page 18: CS 540 – Quantitative Software Engineering](https://reader035.vdocument.in/reader035/viewer/2022062222/56815736550346895dc4d84f/html5/thumbnails/18.jpg)
External Output from 2 Internal Files
External Outputs (EO) – when data passes across the boundary from inside to outside.
![Page 19: CS 540 – Quantitative Software Engineering](https://reader035.vdocument.in/reader035/viewer/2022062222/56815736550346895dc4d84f/html5/thumbnails/19.jpg)
External Inquiry drawing from 2 ILFs
External Inquiry (EQ) - an elementary process with both input and output components that result in data retrieval from one or more internal logical files and external interface files. The input process does not update Internal Logical File, and there is no derived data.
![Page 20: CS 540 – Quantitative Software Engineering](https://reader035.vdocument.in/reader035/viewer/2022062222/56815736550346895dc4d84f/html5/thumbnails/20.jpg)
EO and EQ Table mapped to Values
![Page 21: CS 540 – Quantitative Software Engineering](https://reader035.vdocument.in/reader035/viewer/2022062222/56815736550346895dc4d84f/html5/thumbnails/21.jpg)
Adjusted Function Points
Accounting for Physical System Characteristics
Characteristic Rated by System User
• 0-5 based on “degree of influence”
• 3 is average
UnadjustedFunction
Points (UFP)
UnadjustedFunction
Points (UFP)
General SystemCharacteristics
(GSC)
General SystemCharacteristics
(GSC)
X
=
AdjustedFunction
Points (AFP)
AdjustedFunction
Points (AFP)
AFP = UFP (0.65 + .01*GSC), note GSC = VAF= TDI
1. Data Communications
2. Distributed Data/Processing
3. Performance Objectives
4. Heavily Used Configuration
5. Transaction Rate
6. On-Line Data Entry
7. End-User Efficiency
8. On-Line Update
9. Complex Processing
10. Reusability
11. Conversion/Installation Ease
12. Operational Ease
13. Multiple Site Use
14. Facilitate Change
![Page 22: CS 540 – Quantitative Software Engineering](https://reader035.vdocument.in/reader035/viewer/2022062222/56815736550346895dc4d84f/html5/thumbnails/22.jpg)
Complexity Table
TYPE: SIMPLE AVERAGE COMPLEX
INPUT (I) 3 4 6
OUTPUT(O) 4 5 7
INQUIRY(E) 3 4 6
LOG INT (L) 7 10 15
INTERFACES (F)
5 7 10
![Page 23: CS 540 – Quantitative Software Engineering](https://reader035.vdocument.in/reader035/viewer/2022062222/56815736550346895dc4d84f/html5/thumbnails/23.jpg)
Complexity Factors
1. Problem Domain ___2. Architecture Complexity ___3. Logic Design -Data ___4. Logic Design- Code ___
Total ___
Complexity = Total/4 = _________
![Page 24: CS 540 – Quantitative Software Engineering](https://reader035.vdocument.in/reader035/viewer/2022062222/56815736550346895dc4d84f/html5/thumbnails/24.jpg)
Problem Domain Measure of Complexity (1 is simple and 5 is complex)
1. All algorithms and calculations are simple.2. Most algorithms and calculations are simple.3. Most algorithms and calculations are moderately
complex.4. Some algorithms and calculations are difficult.5. Many algorithms and calculations are difficult.
Score ____
![Page 25: CS 540 – Quantitative Software Engineering](https://reader035.vdocument.in/reader035/viewer/2022062222/56815736550346895dc4d84f/html5/thumbnails/25.jpg)
Architecture ComplexityMeasure of Complexity (1 is simple and 5 is complex)
1. Code ported from one known environment to another. Application does not change more than 5%.2. Architecture follows an existing pattern. Process design is straightforward. No complex hardware/software interfaces.3. Architecture created from scratch. Process design is straightforward. No complex hardware/software interfaces.4. Architecture created from scratch. Process design is complex. Complex hardware/software interfaces exist but they are well defined and unchanging.5. Architecture created from scratch. Process design is complex. Complex hardware/software interfaces are ill defined and changing.
Score ____
![Page 26: CS 540 – Quantitative Software Engineering](https://reader035.vdocument.in/reader035/viewer/2022062222/56815736550346895dc4d84f/html5/thumbnails/26.jpg)
Logic Design -Data
1. Simple well defined and unchanging data structures. Shallow inheritance in class structures. No object classes have inheritance greater than 3.
2. Several data element types with straightforward relationships. No object classes have inheritance greater than
3. Multiple data files, complex data relationships, many libraries, large object library. No more than ten percent of the object classes have inheritance greater than three. The number of object classes is less than 1% of the function points
4. Complex data elements, parameter passing module-to-module, complex data relationships and many object classes has inheritance greater than three. A large but stable number of object classes.
5. Complex data elements, parameter passing module-to-module, complex data relationships and many object classes has inheritance greater than three. A large and growing number of object classes. No attempt to normalize data between modules
Score ____
![Page 27: CS 540 – Quantitative Software Engineering](https://reader035.vdocument.in/reader035/viewer/2022062222/56815736550346895dc4d84f/html5/thumbnails/27.jpg)
Logic Design- Code
1. Nonprocedural code (4GL, generated code, screen skeletons). High cohesion. Programs inspected. Module size constrained between 50 and 500 Source Lines of Code (SLOCs).
2. Program skeletons or patterns used. ). High cohesion. Programs inspected. Module size constrained between 50 and 500 SLOCs. Reused modules. Commercial object libraries relied on. High cohesion.
3. Well-structured, small modules with low coupling. Object class methods well focused and generalized. Modules with single entry and exit points. Programs reviewed.
4. Complex but known structure randomly sized modules. Some complex object classes. Error paths unknown. High coupling.
5. Code structure unknown, randomly sized modules, complex object classes and error paths unknown. High coupling.
Score __
![Page 28: CS 540 – Quantitative Software Engineering](https://reader035.vdocument.in/reader035/viewer/2022062222/56815736550346895dc4d84f/html5/thumbnails/28.jpg)
Complexity Factors
1. Problem Domain ___2. Architecture Complexity ___3. Logic Design -Data ___4. Logic Design- Code ___
Total ___
Complexity = Total/4 = _________
![Page 29: CS 540 – Quantitative Software Engineering](https://reader035.vdocument.in/reader035/viewer/2022062222/56815736550346895dc4d84f/html5/thumbnails/29.jpg)
Computing Function Points
See http://www.engin.umd.umich.edu/CIS/course.des/cis525/js/f00/artan/functionpoints.htm
![Page 30: CS 540 – Quantitative Software Engineering](https://reader035.vdocument.in/reader035/viewer/2022062222/56815736550346895dc4d84f/html5/thumbnails/30.jpg)
Adjusted Function Points
Now account for 14 characteristics on a 6 point scale (0-5) Total Degree of Influence (DI) is sum of scores. DI is converted to a technical complexity factor (TCF)
TCF = 0.65 + 0.01DI Adjusted Function Point is computed by
FP = UFP X TCF For any language there is a direct mapping from Function
Points to LOC
Beware function point counting is hard and needs special skills
![Page 31: CS 540 – Quantitative Software Engineering](https://reader035.vdocument.in/reader035/viewer/2022062222/56815736550346895dc4d84f/html5/thumbnails/31.jpg)
Function Points Qualifiers
Based on counting data structures Focus is on-line data base systems Less accurate for WEB applications Even less accurate for Games, finite state machine and
algorithm software Not useful for extended machine software and compliers
An alternative to NCKSLOC because estimates can be based on requirements and design data.
![Page 32: CS 540 – Quantitative Software Engineering](https://reader035.vdocument.in/reader035/viewer/2022062222/56815736550346895dc4d84f/html5/thumbnails/32.jpg)
Initial Conversion
Language Median SLOC/function pointC 104
C++ 53
HTML 42
JAVA 59
Perl 60
J2EE 50
Visual Basic 42
http://www.qsm.com/FPGearing.html
![Page 33: CS 540 – Quantitative Software Engineering](https://reader035.vdocument.in/reader035/viewer/2022062222/56815736550346895dc4d84f/html5/thumbnails/33.jpg)
![Page 34: CS 540 – Quantitative Software Engineering](https://reader035.vdocument.in/reader035/viewer/2022062222/56815736550346895dc4d84f/html5/thumbnails/34.jpg)
SLOC
Function Points = UFP x TCF = 78 * .96 = 51.84 ~ 52 function points
78 UFP * 53 (C++) SLOC / UFP = 4,134 SLOC
≈ 4.2 KSLOC
.
(Reference for SLOC per function point: http://www.qsm.com/FPGearing.html)
![Page 35: CS 540 – Quantitative Software Engineering](https://reader035.vdocument.in/reader035/viewer/2022062222/56815736550346895dc4d84f/html5/thumbnails/35.jpg)
Understanding the equations
For 4,200 lines of code, what is the shortest time it will take to develop? Module development is about 400 SLOC/staff month
From COCOMO:Effort = 2.4 (size)c
By Barry Boehm
![Page 36: CS 540 – Quantitative Software Engineering](https://reader035.vdocument.in/reader035/viewer/2022062222/56815736550346895dc4d84f/html5/thumbnails/36.jpg)
What is ‘2.4?’
Effort = 2.4 (size)c = 1/(.416) (size)c
Effort = (productivity)-1 (size)c
where productivity = 400 KSLOC/SM from the statement of the problem
= (1/.400 KSLOC/SM)(4.2 KSLOC)1.16
= 2.5 (4.2)1.16 ≈ 13 SM
![Page 37: CS 540 – Quantitative Software Engineering](https://reader035.vdocument.in/reader035/viewer/2022062222/56815736550346895dc4d84f/html5/thumbnails/37.jpg)
Minimum Time
Theoretical time = 2.5 * 3√staff-months
Min time = .75 Theorectical time= (.75)(2.5)(SM)1/3
≈ 1.875(13)1/3
≈ 1.875 x 2.4 ≈ 4.5 months
![Page 38: CS 540 – Quantitative Software Engineering](https://reader035.vdocument.in/reader035/viewer/2022062222/56815736550346895dc4d84f/html5/thumbnails/38.jpg)
How many software engineers?
1 full time staff week = 40 hours, if 1 student week = 10 hours.
Therefore, the estimate of 13 staff months is actually 52 student months.
The period of coding is December 2004 through April 2005; a period of 5 months.
52 staff months/5 months = 10 student software engineers
Design Simplification to cut FP in half is a must, as there are only five student software engineers onboard
![Page 39: CS 540 – Quantitative Software Engineering](https://reader035.vdocument.in/reader035/viewer/2022062222/56815736550346895dc4d84f/html5/thumbnails/39.jpg)
Function Point pros and cons
Pros:
• Language independent
• Understandable by client
• Simple modeling
• Hard to fudge
• Visible feature creep
Cons:• Labor intensive• Extensive training • Inexperience results in
inconsistent results• Weighted to file
manipulation and transactions
• Systematic error introduced by single person, multiple raters advised
![Page 40: CS 540 – Quantitative Software Engineering](https://reader035.vdocument.in/reader035/viewer/2022062222/56815736550346895dc4d84f/html5/thumbnails/40.jpg)
Specification for Development Plan
Project Feature List Development Process Size Estimates Staff Estimates Schedule Estimates Organization Gantt Chart
![Page 41: CS 540 – Quantitative Software Engineering](https://reader035.vdocument.in/reader035/viewer/2022062222/56815736550346895dc4d84f/html5/thumbnails/41.jpg)
Wide Band Delphi
Convene a group of expert Coordinator provides each expert with spec Experts make private estimate in interval format: most
likely value and an upper and lower bound Coordinator prepares summary report indicating group
and individual estimates Experts discuss and defend estimates Group iterates until consensus is reached
![Page 42: CS 540 – Quantitative Software Engineering](https://reader035.vdocument.in/reader035/viewer/2022062222/56815736550346895dc4d84f/html5/thumbnails/42.jpg)
Heuristics to do Better Estimates
Decompose Work Breakdown Structure to lowest possible level and type of software.
Review assumptions with all stakeholders Do your homework - past organizational experience Retain contact with developers Update estimates and track new projections (and warn) Use multiple methods Reuse makes it easier (and more difficult) Use ‘current estimate’ scheme
![Page 43: CS 540 – Quantitative Software Engineering](https://reader035.vdocument.in/reader035/viewer/2022062222/56815736550346895dc4d84f/html5/thumbnails/43.jpg)
Heuristics to Cope with Estimates
Add and train developers early Use gurus for tough tasks Provide manufacturing and admin support Sharpen tools Eliminate unrelated work and red tape (50% issue) Devote full time end user to project Increase level of exec sponsorship to break new ground (new
tools, techniques, training) Set a schedule goal date but commit only after detailed design Use broad estimation ranges rather than single point estimates
![Page 44: CS 540 – Quantitative Software Engineering](https://reader035.vdocument.in/reader035/viewer/2022062222/56815736550346895dc4d84f/html5/thumbnails/44.jpg)
Easy?
“When performance does not meet the estimate, there are two possible causes:
poor performance or poor estimates.
In the software world, we have ample evidence that our estimates stink, but virtually no evidence that people in general don’t work hard enough or intelligently enough.” -- Tom DeMarco
![Page 45: CS 540 – Quantitative Software Engineering](https://reader035.vdocument.in/reader035/viewer/2022062222/56815736550346895dc4d84f/html5/thumbnails/45.jpg)
Capers Jones Expansion Table
![Page 46: CS 540 – Quantitative Software Engineering](https://reader035.vdocument.in/reader035/viewer/2022062222/56815736550346895dc4d84f/html5/thumbnails/46.jpg)
Bernstein’s Trends in Software Expansion
Small ScaleReuse
1990SubsecTime Sharing
1995ObjectOrientedProgramming
1960MachineInstructions
1965MacroAssembler
1970High LevelLanguage
1975Database Manager
1980On-line
1985Prototyping
2000Large ScaleReuse
1
10
100
1000
3
15
3037.5
47
75 81113
142
475
638
RegressionTesting
4GL
Order of MagnitudeEvery Twenty Years
ExpansionFactor
TechnologyChange
![Page 47: CS 540 – Quantitative Software Engineering](https://reader035.vdocument.in/reader035/viewer/2022062222/56815736550346895dc4d84f/html5/thumbnails/47.jpg)
SLOC Defined
:• Single statement, not two separated by semicolon• Line feed• All written statements (OA&M)• No Comments• Count all instances of calls, subroutines, …
There are no industry standards and SLOC can be fudged
![Page 48: CS 540 – Quantitative Software Engineering](https://reader035.vdocument.in/reader035/viewer/2022062222/56815736550346895dc4d84f/html5/thumbnails/48.jpg)
Sizing Software Projects
Effort = (productivity)-1 (size)c
Staff
months
Lines of Code or
Function Points
500 1000
![Page 49: CS 540 – Quantitative Software Engineering](https://reader035.vdocument.in/reader035/viewer/2022062222/56815736550346895dc4d84f/html5/thumbnails/49.jpg)
Regression Models
• Effort:» Watson-Felix: Effort = 5.2 KLOC 0.91
» COCOMO: Effort = 2.4 KLOC 1.05 » Halstead: Effort = 0.7 KLOC 1.50
• Schedule:» Watson-Felix: Time = 2.5E 0.35
» COCOMO: Time = 2.5E 0.38
» Putnam: Time = 2.4E 0.33
![Page 50: CS 540 – Quantitative Software Engineering](https://reader035.vdocument.in/reader035/viewer/2022062222/56815736550346895dc4d84f/html5/thumbnails/50.jpg)
COCOMO
COnstructive COst MOdel Based on Boehm’s analysis of a database of 63 projects -
models based on regression analysis of these systems Linked to classic waterfall model Effort is number of Source Lines of Code (SLOC) expressed in
thousands of delivered source instructions (NCKSLOC) - excludes comments and unmodified software
Original model has 3 versions and considers 3 types of systems:• Organic - e.g.,simple business systems• Embedded -e.g., avionics• Semi-detached -e.g., management inventory systems
![Page 51: CS 540 – Quantitative Software Engineering](https://reader035.vdocument.in/reader035/viewer/2022062222/56815736550346895dc4d84f/html5/thumbnails/51.jpg)
COCOMO Model
Effort in staff months =b*NCKSLOCc
b c
organic 2.4 1.05
semi-detached
3.0 1.12
embedded 3.6 1.20
![Page 52: CS 540 – Quantitative Software Engineering](https://reader035.vdocument.in/reader035/viewer/2022062222/56815736550346895dc4d84f/html5/thumbnails/52.jpg)
COCOMO System Types
SIZE INNOVATION DEADLINE CONSTRAINTS
Organic Small Little Not tight Stable
Semi-Detached
Medium Medium Medium Medium
Embedded Large Greater Tight Complex hdw/customer interfaces
![Page 53: CS 540 – Quantitative Software Engineering](https://reader035.vdocument.in/reader035/viewer/2022062222/56815736550346895dc4d84f/html5/thumbnails/53.jpg)
Intermediate COCOMO
Adds 15 attributes of the product that has to be rated on a six point scale from Very Low to Extra High
There are 4 categories of attributes: product, computer, personnel and project.
The ratings are reflected in P of the equation
Effort in staff months =(b*KDLOCc)*P
![Page 54: CS 540 – Quantitative Software Engineering](https://reader035.vdocument.in/reader035/viewer/2022062222/56815736550346895dc4d84f/html5/thumbnails/54.jpg)
Intermediate COCOMO attributes
PRODUCT:
• RELY - required reliability
• DATA- data bytes per DSI (smaller db)
• CPLX - code complexity (VH= real time)
COMPUTER:
• TIME - execution time, % used
• STOR - storage requirements, % used
• VIRT - changes made to hdw and OS
• TURN- Dev turnaround time, batch vs interactive
PERSONNEL
• ACAP - analyst capability, skills
• PCAP - programmer capability
• AEXP- applications experience
• LEXP - language experience
• VEXP- virtual machine experience PROJECT
• MODP - Modern Development Practices
• TOOL - use of sfw tools
• SCED - amount of schedule compression
![Page 55: CS 540 – Quantitative Software Engineering](https://reader035.vdocument.in/reader035/viewer/2022062222/56815736550346895dc4d84f/html5/thumbnails/55.jpg)
Intermediate COCOMO Attributeshttp://www.cs.unc.edu/~stotts/COMP145/cocomo6.gif
![Page 56: CS 540 – Quantitative Software Engineering](https://reader035.vdocument.in/reader035/viewer/2022062222/56815736550346895dc4d84f/html5/thumbnails/56.jpg)
COCOMO II
Post Architecture Model is the most detailed model. Differs from original COCOMO in set of cost drivers, and range of values to parameters. New cost drivers are:
» Documentation needs
» Personnel continuity
» Required reusability
» Multi-site development
» (-) computer turnaround time
» (-) use of modern programming practices
![Page 57: CS 540 – Quantitative Software Engineering](https://reader035.vdocument.in/reader035/viewer/2022062222/56815736550346895dc4d84f/html5/thumbnails/57.jpg)
COCOMO II
Effort = a (size)c П EM(i)c = 1.01 + 0.01+∑SF(j); where SF(j) are 5 scale factors and EM(i) has 17 cost
drivers
See: http://sunset.usc.edu/research/COCOMOII
We will use the original COCOMO model in CS 540.
![Page 58: CS 540 – Quantitative Software Engineering](https://reader035.vdocument.in/reader035/viewer/2022062222/56815736550346895dc4d84f/html5/thumbnails/58.jpg)
Case Study
Light Planning Undergraduate Project Eight students October 15 to May 1
![Page 59: CS 540 – Quantitative Software Engineering](https://reader035.vdocument.in/reader035/viewer/2022062222/56815736550346895dc4d84f/html5/thumbnails/59.jpg)
Prospectus
Theater group uses a CAD tool to design and set up lighting plots. Our objective is to design an easy to use, GUI based system that guides the user through the lighting design phase.
It will be capable of representing the lighting design of a theatre of any size. The involved parts of the theatre include: the room that encloses the stage, the stage itself, show set, lighting bars, their wiring, and the objects that hang on them. All items in the diagram will be selected from an inventory through the use of an inventory management system.
The program will also be able to print out clear, concise, lighting plots and wiring plots that conform to the industry standards for lighting.
Since the theatre has several different Operating System portability is an issue. As a result, the project will be written in JAVA, with an XML backend to store the data.
![Page 60: CS 540 – Quantitative Software Engineering](https://reader035.vdocument.in/reader035/viewer/2022062222/56815736550346895dc4d84f/html5/thumbnails/60.jpg)
MOV
Cut Time spent learning/using CAD software by 25%.
Cut Time spent by electricians by 5%,with clearer diagrams and save $7308.00
No software licensing fee
![Page 61: CS 540 – Quantitative Software Engineering](https://reader035.vdocument.in/reader035/viewer/2022062222/56815736550346895dc4d84f/html5/thumbnails/61.jpg)
Requirements
1. Design a lighting scheme for a show2. Edit stage space, set space, bars, lighting plot, and instrument properties.3. Save and load all data in XML4. Create and maintain equipment inventory.5. View concurrent information between different aspects of design with a GUI driven
interface using 2D drawing and text.6. Store each design in its own separate XML file.7. Maintain multiple lighting schemes for different plays. 8. Load user defined design space; use default on startup.9. Open one scheme at a time.10. Use JAVA data structures while the program is running.11. Read and write to XML file on saves, loads and timed backups and error check
XML files for design types when this happens. 12. Build a print routine for workspace, inventory screen, wiring sheet, bar diagram.13. Print workspace design aspects individually or overlapped.14. Use English or Metric measures for integer coordinates
![Page 62: CS 540 – Quantitative Software Engineering](https://reader035.vdocument.in/reader035/viewer/2022062222/56815736550346895dc4d84f/html5/thumbnails/62.jpg)
![Page 63: CS 540 – Quantitative Software Engineering](https://reader035.vdocument.in/reader035/viewer/2022062222/56815736550346895dc4d84f/html5/thumbnails/63.jpg)
![Page 64: CS 540 – Quantitative Software Engineering](https://reader035.vdocument.in/reader035/viewer/2022062222/56815736550346895dc4d84f/html5/thumbnails/64.jpg)
UFP = 4I + 5O + 4E + 10L + 7F
Number of input types, I =3 Number of output types O=1 Number of inquiry types E =5 Number of logical internal files L=1 Number of interfaces F =1 UFP = 4(3) + 5(1) + 4(5) + 10(1) + 7(1) = 54
Unadjusted Function Points
![Page 65: CS 540 – Quantitative Software Engineering](https://reader035.vdocument.in/reader035/viewer/2022062222/56815736550346895dc4d84f/html5/thumbnails/65.jpg)
Technical Complexity Factor (TCF)
General System Characterists Influence (GSC) Rating• Data Communication = 2• Distributed Function =1• Performance = 3• Heavily Used Configuration =1• Transaction Rate= 2• Online Data Entry =0• End-User Efficiency =5• Online Update =0• Complex Processing= 3• Reusability= 4• Installation Ease =3• Operational Ease= 3• Multiple Sites =1• Facilitate Change =3 Total:31
TCF = .65 + .01GSC TCF = .65 + .01(31) = .96
![Page 66: CS 540 – Quantitative Software Engineering](https://reader035.vdocument.in/reader035/viewer/2022062222/56815736550346895dc4d84f/html5/thumbnails/66.jpg)
SLOC
Function Points = UFP x TCF = 54 * .96 = 51.84 ~ 52 function points
54 UFP * 77 (C)LOC / UFP = 4,158 SLOC
= 4.2 KSLOC
.
(Reference for SLOC per function point: http://www.qsm.com/FPGearing.html)
![Page 67: CS 540 – Quantitative Software Engineering](https://reader035.vdocument.in/reader035/viewer/2022062222/56815736550346895dc4d84f/html5/thumbnails/67.jpg)
Time
Staff-month
Ttheoretical
75% * Ttheoretical
Impossible design
Linear increase
Boehm: “A project can not be done in less than 75% of theoretical time”
Ttheoretical = 2.5 * 3√staff-months
But, how can I estimate staff months?
![Page 68: CS 540 – Quantitative Software Engineering](https://reader035.vdocument.in/reader035/viewer/2022062222/56815736550346895dc4d84f/html5/thumbnails/68.jpg)
Sizing Software Projects
Effort = (productivity)-1 (size)c
productivity ≡ staff-months/KSLOC
size ≡ KSLOC
Staff
months
Lines of Code or
Function Points
500
![Page 69: CS 540 – Quantitative Software Engineering](https://reader035.vdocument.in/reader035/viewer/2022062222/56815736550346895dc4d84f/html5/thumbnails/69.jpg)
Understanding the equations
For 4,200 lines of code, what is the shortest time it will take to develop? Module development is about 400 SLOC/staff month
From COCOMO:Effort = 2.4 (size)c
![Page 70: CS 540 – Quantitative Software Engineering](https://reader035.vdocument.in/reader035/viewer/2022062222/56815736550346895dc4d84f/html5/thumbnails/70.jpg)
What is ‘2.4?’
From COCOMO:Effort = 2.4 (size)c
Effort = (productivity)-1 (size)c
where productivity = 400 KSLOC/SM
= (1/.400 KSLOC/SM)(4.2 KSLOC)1.16
= 2.5 (4.2)1.16 ≈ 13 SM
![Page 71: CS 540 – Quantitative Software Engineering](https://reader035.vdocument.in/reader035/viewer/2022062222/56815736550346895dc4d84f/html5/thumbnails/71.jpg)
Exponent
Calculate c using c = 1.01 + .01(w) where w is the sum of the weights in the following table.
Precedentness =3
Development Flexibility =3
Architecture/Risk Resolution = 4
Team Cohesion =2
Process Maturity = 3; w = 15
c = 1.01 + .01(w) = 1.01 + .15 = 1.16
![Page 72: CS 540 – Quantitative Software Engineering](https://reader035.vdocument.in/reader035/viewer/2022062222/56815736550346895dc4d84f/html5/thumbnails/72.jpg)
Minimum Time
Theoretical time = 2.5 * 3√staff-months
Min time = .75 Theorectical time= (.75)(2.5)(SM)1/3
≈ 1.875(13)1/3
≈ 1.875 x 2.4 ≈ 4.5 months
![Page 73: CS 540 – Quantitative Software Engineering](https://reader035.vdocument.in/reader035/viewer/2022062222/56815736550346895dc4d84f/html5/thumbnails/73.jpg)
How many software engineers?
1 full time staff week = 40 hours, 1 student week = 20 hours.
Therefore, our estimation of 13 staff months is actually 26 student months.
The period of coding is December 2004 through April 2005, which is a period of 5 months.
26 staff months/5 months = 5 student software engineers
![Page 74: CS 540 – Quantitative Software Engineering](https://reader035.vdocument.in/reader035/viewer/2022062222/56815736550346895dc4d84f/html5/thumbnails/74.jpg)
Proposed System
Proposed System
Check Status
Create Order
Shipment Notice
Inventory
Assign Inventory to Order
Inventory Assigned
New Inventory for Held Orders
Assign Order to Truck
Truckload Report
Shipping Invoices
Order Update
Order Display
Problem ResolutionDispatch
Accounting
Management Reports
Customer
Check Credit &
Completion
Users
Catalog
Orders
OrderCreation
Credit Check
InventoryAssignment
Held OrderProcessing
Completion
DispatchSupport
ProblemResolution
ManagementReporting
OA&M
![Page 75: CS 540 – Quantitative Software Engineering](https://reader035.vdocument.in/reader035/viewer/2022062222/56815736550346895dc4d84f/html5/thumbnails/75.jpg)
Case Study:Use Cases Transactions Type Complexity UFP
End UsersLogon 1 I 3 3View Last Bill 1 Q 6 6Create Account 1 I 6 6View Current Services 1 Q 4 4Establish Analog CATV Service 1 I 6 6Add Data Service 1 I 6 6Add/Delete a Premium Channel 1 I 4 4Add/Delete a Digital Package 1 I 6 6View Trouble Status 1 Q 4 4View Order Status 1 Q 3 3View Information 5 Q 3 15
BackEndGet Account & Service Info 1 N 10 10Get Last Bill 1 N 10 10Create Account 1 N 10 10Create Order 1 N 10 10Account Validation 3 N 7 21Order Validation 3 N 7 21Get Trouble Status 1 N 7 7Get Order Status 1 N 7 7
ManagementView Customer Use Statistics 5 Q 4 20Troubleshoot Customer Scenario 5 Q 6 30
OA&MUser Administration 2 F 7 14Table Administration 15 F 7 105Usage DB Administration 1 F 15 15Temp DB Admin 1 F 15 15Schedule Reports 1 I 4 15Control Application 1 I 4 15Create Reports 1 I 6 15Application Alarms 1 O 7 15
Total Unadjusted Function Points 418
![Page 76: CS 540 – Quantitative Software Engineering](https://reader035.vdocument.in/reader035/viewer/2022062222/56815736550346895dc4d84f/html5/thumbnails/76.jpg)
GSC
General System Characteristic Rating1 Data Communications 52 Distributed Data/Processing 43 Performance Objectives 54 Heavily Used Configuration 55 Transaction Rate 56 On-Line Data Entry 37 End-User Efficiency 58 On-Line Update 39 Complex Processing 3
10 Reusability 211 Conversion/Installation Ease 312 Operational Ease 413 Multiple Site Use 414 Facilitate Change 4
Total Degree of Influence 55
UFP (.65+.01*GSC)418 1.2
Adjusted Function Points 502
![Page 77: CS 540 – Quantitative Software Engineering](https://reader035.vdocument.in/reader035/viewer/2022062222/56815736550346895dc4d84f/html5/thumbnails/77.jpg)
Average Median Low High Consultant
![Page 78: CS 540 – Quantitative Software Engineering](https://reader035.vdocument.in/reader035/viewer/2022062222/56815736550346895dc4d84f/html5/thumbnails/78.jpg)
Applying the equations
For 418 UFP x 63 (Java) SLOC/FP = 26334 SLOC
≈ 30 KSLOC
How long will it take to develop?
Module development is about 330 SLOC/staff month
![Page 79: CS 540 – Quantitative Software Engineering](https://reader035.vdocument.in/reader035/viewer/2022062222/56815736550346895dc4d84f/html5/thumbnails/79.jpg)
COCOMO Model
Effort in staff months =b*NCKSLOCc
b c
organic 2.4 1.05
semi-detached
3.0 1.12
embedded 3.6 1.20
![Page 80: CS 540 – Quantitative Software Engineering](https://reader035.vdocument.in/reader035/viewer/2022062222/56815736550346895dc4d84f/html5/thumbnails/80.jpg)
What is ‘2.4?’
From COCOMO:Effort = (productivity)-1 (size)c
where productivity = 330 KSLOC/SM
= (1/330 KSLOC/SM)(30 KSLOC)1.12
= 3 (30)1.12 ≈ 100 SM
![Page 81: CS 540 – Quantitative Software Engineering](https://reader035.vdocument.in/reader035/viewer/2022062222/56815736550346895dc4d84f/html5/thumbnails/81.jpg)
Minimum Time
Theoretical time = 2.5 * 3√staff-months
= (2.5)(100)1/3
≈ 12 months
![Page 82: CS 540 – Quantitative Software Engineering](https://reader035.vdocument.in/reader035/viewer/2022062222/56815736550346895dc4d84f/html5/thumbnails/82.jpg)
Software Costs by extrapolated history
Cost Development using FPA Estimate
• Requirements Engineering (1/3 of implementation
• Design (1/5 of implementation)• Testing (1/4 of implementation• Documentation & Training
FP per mo 5Dev Staff Mos 65.8Dev Staff Yrs 5.5Sys Eng 1.8Design 1.1Test 1.8Doc 1.0Trng 1.0Total 12.2
Staff Cost $150,000Project Cost $1,836,173
7.6