CSE563 Lecture 24

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CSE 563
Software Requirements and Specification
Lecture 24: COCOMO
Dr. Javier Gonzalez-Sanchez
[email protected]
javiergs.engineering.asu.edu | javiergs.com
PERALTA 230U
Office Hours: By appointment

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Announcements
§ All midterm grades are posted.
§ Midterms Exams are open for ASU Sync Students.
§ I am publishing Frequently Asked Questions on Canvas, and I will be
advising you to read it when applying.
§ Statistics – Over the last years, 5 exams were updated (~300 students).
Grade changes less than 3%. For instance, 74.7 moved to 75.9. Updates
can go up or down.

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Announcements
§ The final Exam is on December 5
(As scheduled by ASU)
“three exams in one day” is possible and not considered a conflict

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Final Project
§ User Stories in Taiga (Backlogs)
§ Sprint(s)
§ Tasks and their responsible (Taskboard)
§ Daily report (Burndown Chart)
§ Source Code
§ JavaDoc (Classes and Methods)
§ UML Class Diagram (Recommended but not mandatory). If you create one,
include it in your submission.

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We are here
Burndown
Chart

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Sprint(s) Review and Retrospective

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Final Project
§ User Stories in Taiga (Backlogs)
§ Sprint(s)
§ Tasks and their responsible (Taskboard)
§ Daily report (Burndown Chart)
§ Source Code
§ JavaDoc (Classes and Methods)
§ UML Class Diagram (Recommended but not mandatory). If you create one,
include it in your submission.
§ Sprint(s) Retrospective – A document about your team and team process
§ Sprint(s) Review - A document about the product (complete? Missing
parts?)

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Advice
• Take Screenshots
of your Taiga – Showing
dates, names, etc.
• Back up your code.
• You are a self-organized
team. TAs are not
responsible for you

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Where we are?

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Where we are?
Product Requirement Task
As a (role),
I want (feature),
So that (benefit)
… move the pacman
… show the pacman
… move a ghost
… show a ghost
… show power pills
features tasks
(new)

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Where we are?
§ How many hours (time)?
§ Or How many people?

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Where we are?
Timer KeyListener JFrame ActionListener
Game
Ghost
Pacman
Maze
Drawable
PowerDot
JPanel

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Where we are?
Timer KeyListener JFrame ActionListener
Game
Ghost
Pacman
Maze
Drawable
PowerDot
JPanel
Software Design (CSE 564)

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Javier Gonzalez-Sanchez | SER332 | Spring 2018 | 16

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Where we are?
§ How many hours (time)?
§ Or How many people?
VS
§ How many lines of code?

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Constructive Cost Model
Cocomo

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COCOMO
§ The constructive cost model was developed by Barry Boehm (the Spiral
model guy) in the late 1970 and published in Software Engineering
Economics.
§ It is a model for estimating effort, cost, and schedule for software projects.
§ It drew on a study of 63 projects at TRW Aerospace.
§ The study examined projects ranging in size from 2,000 to 100,000 lines of
code and diverse programming languages.
§ These projects were based on the waterfall model of software development
(prevalent in 1981).

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Regression-Based Model

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COCOMO
§ The constructive cost model was developed by Barry Boehm (the Spiral
model guy) in the late 1970 and published in Software Engineering
Economics.
§ It is a model for estimating effort, cost, and schedule for software projects.
§ It drew on a study of 63 projects at TRW Aerospace.
§ The study examined projects ranging in size from 2,000 to 100,000 lines of
code and diverse programming languages.
§ These projects were based on the waterfall model of software development
(prevalent in 1981).
Software Project, Process, & Quality Management (CSE 566)

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COCOMO II

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COCOMO II Web Tool by USC
http://softwarecost.org/tools/COCOMO/

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Factors of development cost
1. Software Size (Lines of Code)
2. Software Scale Drivers: sources of exponential effort variation
3. Software Cost Drivers: sources of linear effort variation. They group in 4
categories: product, platform, personnel and project
Factor are rated between very low and very high per rating guidelines

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COCOMO II - Inputs

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Scale Drivers Rating
Scale Factors (Wi
) Very Low Low Nominal High Very High Extra High
Precedentedness
(PREC)
thoroughly
unprecedented
largely
unprecedented
somewhat
unprecedented
generally
familiar
largely
familiar
throughly
familiar
Development
Flexibility (FLEX)
rigorous occasional
relaxation
some
relaxation
general
conformity
some
conformity
general
goals
Architecture/Risk
Resolution (RESL)*
little (20%) some (40%) often (60%) generally
(75%)
mostly
(90%)
full (100%)
Team Cohesion
(TEAM)
very difficult
interactions
some difficult
interactions
basically
cooperative
interactions
largely
cooperative
highly
cooperative
seamless
interactions
Process Maturity
(PMAT)
Weighted average of “Yes” answers to CMM Maturity Questionnaire
* % significant module interfaces specified, % significant risks eliminated

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COCOMO II - Inputs

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Cost Drivers | Product Factors
1.1. Required Reliability (RELY)
1. 2. Data Base Size (DATA)
1. 3. Complexity (CPLX)
1. 4. Developed for Reusability (RUSE)
1. 5. Documentation (DOCU)

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Cost Drivers | Personnel factors
2.1 Analyst capability (ACAP)
2.2 Programmer (Software Engineer) capability (PCAP)
2.3. Applications experience (APEX)
2.4. Platform (or VM) experience (PLEX)
2.5. Language and tool experience (LTEX)
2.6. Personnel continuity (PCON)

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Cost Drivers | Platform Factors
3.1. Time constraint (TIME)
3.2. Storage constraint (STOR)
3.3. Platform volatility (PVOL)

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Cost Drivers | Project Factors
Project Factors
4.1. Use of Software tools (TOOL)
4.2. Multisite development (SITE)
4.3. Required schedule - stretch-out or acceleration (SCED)
Multisite development

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Test Yourselves

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Pacman
§ It has 1200 LOC
§ Nothing to be reuse
§ What could be its cost in the best-case scenario?
§ What could be its cost in the worse-case scenario?
§ What is the best-case scenario? (value for the factors)
§ What is the worse-case scenario? (value for the factors)

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Questions

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Reference
§ Somerville, Chapter 23

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Appendix A: Product Factors

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1.1. Required 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?
Very Low Low Nominal High Very High Extra High
RELY slight
inconvenience
low, easily
recoverable losses
moderate, easily
recoverable losses
high financial loss risk to human life

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1.2. Data Base Size (DATA)
§ Captures the effect large data requirements have
on development to generate test data that will be used to exercise
the program
§ Calculate the data/program size ratio (D/P):
DatabaseSize(bytes) / ProgramSize (LOC)
DATA DB bytes/ Pgm SLOC < 10 10 £ D/P < 100 100 £ D/P < 1000 D/P > 1000

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1.3. Product Complexity (CPLX)
It is divided into five areas:
1. control operations,
2. computational operations,
3. device-dependent operations,
4. data management operations, and
5. user interface management operations.
Select the area or combination of areas that characterize the product or a
sub-system of the product.
Use a subjective weighted average of the attributes, weighted
by their relative product importance.

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1.3. Product Complexity (CPLX)
Control
Operations
Straightline code
with a few non-
nested structured
programming
operators: DOs,
CASEs,
IFTHENELSEs.
Simple module
composition via
procedure calls or
simple scripts.
Straightforward
nesting of
structured
programming
operators.
Mostly simple
predicates.
Mostly simple
nesting. Some
intermodule
control. Decision
tables. Simple
callbacks or
message
passing,
including
middleware-
supported
distributed
processing.
Highly nested
structured
programming
operators with many
compound
predicates. Queue
and stack control.
Homogeneous, dist.
processing. Single
processor soft real-
time ctl.
Reentrant and
recursive coding.
Fixed-priority
interrupt handling.
Task synchronization,
complex callbacks,
heterogeneous dist.
processing. Single-
processor hard real-
time ctl.
Multiple resource
scheduling with
dynamically changing
priorities. Microcode-
level control.
Distributed hard real-
time control.
Computational
Operations
Evaluation of
simple
expressions: e.g.,
A=B+C*(D-E)
Evaluation of
moderate-level
expressions:
e.g.,
D=SQRT(B**2-
4.*A*C)
Use of standard
math and
statistical
routines. Basic
matrix/vector
operations.
Basic numerical
analysis: multivariate
interpolation, ordinary
differential eqns.
Basic truncation,
roundoff concerns.
Difficult but structured
numerical analysis:
near-singular matrix
equations, partial
differential eqns.
Simple
parallelization.
Difficult and
unstructured
numerical analysis:
highly accurate
analysis of noisy,
stochastic data.
Complex
parallelization.
Device-
dependent
Operations
Simple read,
write
statements
with simple
formats.
No cognizance
needed of particular
processor or I/O
device
characteristics. I/O
done at GET/PUT
level.
I/O processing
includes device
selection, status
checking and error
processing.
Operations at physical
I/O level (physical
storage address
translations; seeks,
reads, etc.).
Optimized I/O overlap.
Routines for interrupt
diagnosis, servicing,
masking.
Communication line
handling.
Performance-intensive
embedded systems.
Device timing-
dependent coding,
micro-programmed
operations.
Performance-
critical embedded
systems.
Data
Management
Operations
Simple arrays
in main
memory.
Simple COTS-
DB queries,
updates.
Single file subsetting
with no data structure
changes, no edits, no
intermediate files.
Moderately complex
COTS-DB queries,
updates.
Multi-file input and
single file output.
Simple structural
changes, simple
edits. Complex
COTS-DB queries,
updates.
Simple triggers
activated by data
stream contents.
Complex data
restructuring.
Distributed database
coordination. Complex
triggers. Search
optimization.
Highly coupled,
dynamic relational
and object
structures. Natural
language data
management.
User
Interface
Management
Simple input
forms, report
generators.
Use of simple graphic
user interface (GUI)
builders.
Simple use of
widget set.
Widget set
development and
extension. Simple
voice I/O, multimedia.
Moderately complex
2D/3D, dynamic
graphics, multimedia.
Complex
multimedia, virtual
reality.

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1.4 Required Reusability (RUSE)
Accounts for the additional effort needed to construct components intended
for reuse.
RUSE none across project across program across product line across multiple product lines

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1.5. Documentation (DOCU)
Level of required documentation.
DOCU Many life-cycle
needs uncovered
Some life-cycle
needs uncovered
Right-sized to life-
cycle needs
Excessive for life-
cycle needs
Very excessive for
life-cycle needs

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Appendix B: Personal Factors

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2.1. Analyst Capability (ACAP)
Analysts work on requirements, high level design and detailed design.
Consider analysis and design ability, efficiency and thoroughness, and the
ability to communicate and cooperate.
ACAP 15th percentile 35th percentile 55th percentile 75th percentile 90th percentile

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2.2. Programmer Capability (PCAP)
Evaluate the capability of the programmers as a team rather than as
individuals. Consider ability, efficiency and thoroughness, and the ability to
communicate and cooperate.
PCAP 15th percentile 35th percentile 55th percentile 75th percentile 90th percentile

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2.3. Applications Experience (AEXP)
Assess the project team's equivalent level of experience with this type
of application.
AEXP £ 2 months 6 months 1 year 3 years 6 years

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2.4. Platform Experience (PEXP)
PEXP £ 2 months 6 months 1 year 3 years 6 year
Assess the project team's equivalent level of experience with this platform
including the OS, graphical user interface, database, networking, and
distributed middleware.

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2.5. Language and Tool Experience (LTEX)
Measures the level of programming language and software tool experience of
the project team.
o Very Low Low Nominal High Very High Extra High
LTEX £ 2 months 6 months 1 year 3 years 6 years

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2.6. Personnel Continuity (PCON)
The scale for PCON is in terms of the project's annual personnel turnover.
PCON 48% / year 24% / year 12% / year 6% / year 3% / year

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Appendix C: Platform Factors

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3.1. Time Constraint (TIME)
Measures the constraint imposed upon a system in terms of the percentage
of available execution time expected to be used by the system.
TIME £ 50% use of available execution time 70% 85% 95%

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3.2. Storage Constraint (STOR)
§ Measures the degree of main storage constraint imposed on a software
system or subsystem.
§ Given the remarkable increase in available processor execution time and
main storage, one can question whether these constraint variables are still
relevant. However, many applications continue to expand to consume
whatever resources are available, making these cost drivers still relevant.
STOR £ 50% use of available storage 70% 85% 95%

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3.3. Platform Volatility (PVOL)
Assesses the volatility of the platform, i.e., the complex of hardware and
software the software product calls on to perform its tasks
PVOL major change every 12 mo.;
minor change every 1 mo.
major: 6 mo.;
minor: 2 wk.
major: 2 mo.;
minor: 1 wk.
major: 2 wk.;
minor: 2 days

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Appendix D: Project Factors

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4.1. Use of Software Tools (TOOL)
Assess the usage of software tools used to develop the product in terms of
their capabilities and maturity. Software tools have improved significantly
since the 1970's projects used to calibrate COCOMO. The tool rating ranges
from simple edit and code, very low, to integrated lifecycle management
tools, very high.
edit, code,
debug
simple,
frontend,
backend CASE,
little integration
basic lifecycle
tools, moderately
integrated
strong, mature
lifecycle tools,
moderately
integrated
strong, mature,
proactive lifecycle
tools, well integrated
with processes,
methods, reuse

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4.2. Multisite Development (SITE)
Assess and average two factors: site collocation and communication
support.
SITE:
Collocation
International Multi-city and
Multi-company
Multi-city or
Multi-company
Same city or
metro. area
Same building or
complex
Fully collocated
SITE:
Communications
Some phone,
mail
Individual phone,
FAX
Narrowband
email
Wideband
electronic
communication
Wideband elect.
comm, occasional
video conf.
Interactive
multimedia

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4.3. Required Schedule (SCED)
Measure the imposed schedule constraint in terms of the percentage of
schedule stretch-out or acceleration with respect to a nominal schedule
for the project.
SCED 75% of nominal 85% 100% 130% 160%

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CSE 563 Software Requirements and Specification
Javier Gonzalez-Sanchez, Ph.D.
[email protected]
Fall 2021
Copyright. These slides can only be used as study material for the class CSE563 at ASU.
They cannot be distributed or used for another purpose.

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CSE563 Lecture 24

CSE563 Lecture 24

Javier Gonzalez-Sanchez
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CSE563 Lecture 24

CSE563 Lecture 24

Javier Gonzalez-Sanchez PRO

More Decks by Javier Gonzalez-Sanchez

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Javier Gonzalez-Sanchez
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