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APPENDIX
F
SOME
CURRENTLY AVAILABLE
SOFTWARE
ESTIMATION PRODUCTS
PRODUCED
BY THE SOFTWARE
SUBGROUP
OF THE
SPACE
SYSTEMS
APPENDIX
F
SOME CURRENTLY AVAILABLE SOFTWARE
ESTIMATION PRODUCTS
This section incorporates
inputs from a variety of sources, primarily from model developers. No attempt
has been made to substantiate the information at this point. Comments and
updates are welcome, as are full descriptions of other models not discussed
here.
Contents:
PRICE-S
REVIC
SASET
SEER-
SLIM
SoftCost-R
& SoftCost-Ada
Other
Models
PRICE-S
This
model was developed originally by Martin Marietta Price Systems (initially RCA
Price, then GE Price) as one of a family of models for hardware and software
cost estimation. Developed in 1977 by F. Freiman and Dr. R. Park, it was the
first commercially available detailed parametric software cost model to be
extensively marketed and used. In 1987, the model was modified and re-validated
for modern software development practices. The PRICE-S model is proprietary, it
can be leased for yearly use on
Inputs
One of the primary inputs for the PRICE-S
model is source lines of code (SLOC). This may be input by the user or computed
using either object-oriented or function point sizing models. Both sizing
models are included in the PRICE-S package. Other key inputs include:
1. Application:
a measure of the type (or types) of software, described by one of seven
categories (mathematical, string manipulation, data storage and retrieval,
on-line, real-time, interactive, or operating system).
2. Productivity
Factor: A calibratable parameter which relates the software program to the
productivity, efficiency/inefficiencies, software development practices and
management practices of the development organization.
3. Complexities:
Three complexity parameters which relate the project to the expected completion
time, based on organizational experience, personnel, development tools,
hardware characteristics, and other complicating factors.
4. Platform:
the operating environment, in terms of specification, structure and reliability
requirements.
5. Utilization:
Percentage of hardware memory or processing speed utilized by the software.
6. New
Design/New Code: Percentage of new design and new code.
7. Integration
(Internal): Effort to integrate various software components together to form an
integrated and tested CSCI.
8. Integration
(Extenal): Effort to integrate various software CSCI’s together to form an
integrated and tested software system.
9. Schedule:
Software project start and/or end dates.
10. Optional
Input Parameters: Financial factors, escalation, risk simulation.
Processing
The
PRICE-S algorithms are published in the paper entitled "Central Equations
of PRICE S" which is available from PRICE Systems. It states that PRICE-S
computes a "weight" of software based on the product of instructions
and application inputs. The productivity factor and complexity inputs are very
sensitive parameters which affect effort and schedule calculations. Platform is
known to be an exponential input; hence, it can be very sensitive. A new
weighted design and code value are calculated by the model based on the type or
category of instructions. Both new design and code affect schedule and cost
calculations. Internal integration input parameters affect the CSCI cost and schedule
for integrating and testing the CSCI. The external integration input parameter
is used to calculate software to software integration cost and schedule.
Outputs
PRICE-S
computes an estimate in person effort (person hours or months). Effort can be converted
to cost in dollars or other currency units using financial factors parameters.
Software development schedules are calculated for nine DoD-STD-2167A phases:
System Concept through Operational Test and Evaluation. Six elements of costs
are calculated and reported for each schedule phase: Design Engineering,
Programming, Data, Systems Engineering Project Management, Quality Assurance,
and Configuration Management. The PRICE-S model also contains several optional
outputs including over thirty graphs, Gantt charts, sensitivity matrices,
resource expenditure profiles, schedule reports. In addition, Microsoft Project
files, spreadsheet files, and risk analysis reports can be generated. The risk
analysis report is a Cumulative Probability Distribution and is generated using
either
Calibration
The
PRICE-S model can be run in ECIRP (PRICE backwards) mode to calibrate selected
parameters. The most common calibration is that of the productivity factor,
which, according to the PRICE-S manual, tends to remain constant for a given
organization. It is also possible to calibrate platform, application, and
selected internal factors.
Life Cycle Considerations
The
PRICE-S life cycle model, included in the PRICE-S package, is a detailed model
which computes software support costs. The primary inputs include PRICE-S
development inputs, support descriptors which include software support life,
number of installations, expected growth, and support productivity factors. The
model also has a modification mode which allows up to four modifications per
software CSCI. The PRICE-S life cycle model calculates support effort and
outputs the cost in three support phases: maintenance, enhancements, and
growth. The model allocates effort or cost across six elements of costs for
each support phase.
Risk Analysis
The
PRICE-S model contains a robust
Contact
Lockheed-Martin PRICE Systems
Mt. Laurel, NJ
08054
(800) 437-7423 a.k.a (800) 43PRICE
REVIC
The
Revised Intermediate COCOMO (REVIC) model was developed by Ray Kile and the
U.S. Air Force Cost Analysis Agency. It is a copyrighted program that runs
under DOS on an IBM PC or compatible computer. The model predicts the
development costs for software development from requirements analysis through
completion of the software acceptance testing and maintenance costs for fifteen
years. REVIC uses the intermediate COCOMO set of equations for calculating the
effort (man-power in staff-months and staff-hours) and schedule (elapsed time
in calendar months) to complete software development projects based on an
estimate of the lines of code to be developed and a description of the
development environment. The forms of the basic equations are:
(I) MM = AB(KDSI)P(Fi)
(2) TDEV = CD(MM)
Equation (1) predicts the manpower in
man-months (MM) based on the estimated lines of code to be developed (KDSI = Delivered
Source Instructions in thousands) and the product of a group of environmental
factors (Fi). The coefficients (A,C), exponents (B,D) and the factor (Fi) are
determined by statistical analysis from a database of completed projects. These
variables attempt to account for the variations in the total development
environment (such as programmer's capabilities or experience with the hardware
or software) that tend to increase or decrease the total effort and schedule.
The results from equation (1) are input to equation (2) to determine the
schedule (TDEV = Development Time) in months needed to complete the
development.
REVIC
enhancement of the intermediate COCOMO includes:
The addition of a fourth mode -
Addition of the first and last development
phases. COCOMO provides a set of
tables distributing the effort and schedule to the phases of development
(system engineering, preliminary design, critical design, etc.) and activities
(system analysis, coding, test plarming, etc.) as a percentage of the total.
COCOMO covers four development phases (preliminary design, critical design,
code and unit test, and integration and test) in the estimate. REVIC adds two
more development phases: software requirements engineering, and integration
& test after FQT.
REVIC
predicts the effort and schedule in the software requirements engineering phase
by taking a percentage of the development phases. It provides a default value
(12% for effort, 30% for schedule) for this percentage based on average
programs, but allows the user to change the percentage.
COCOMO
development phase ends at completion of the integration & test phase (after
successful FQT). This phase covers the integration of software CSC's into
CSCI's and testing of the CSCI's against the test criteria developed during the
program. It does not include the systemlevel integration (commonly called
software builds) of CSCI's, and the system-level testing to ensure that
system-level specification requirements are met. The software to software and
software to hardware integration and testing is accounted for in the
Development Test and Evaluation (DT&E) phase. REVIC predicts the effort and
schedule for this phase by taking a percentage of the development effort. REVIC
provides a default percentage of 22% for effort and 26% for schedule based on
average programs. It allows the user to modify these percentages if desired.
Complete interface between the model and
the user. Users are not required to
have extensive knowledge about the model or detailed knowledge of algorithms.
REVIC contains extensive prompting and help screens. REVIC also removes the
typical intimidation factor that prevents analysts from successfully using
models.
Provide the capability to interactively
constrain the schedules and staffing levels. Schedules can be constrained either in the aggregate or by phase of the
development effort. Staffing can be constrained by phase. Using these features,
the analyst can estimate cost overruns, underruns, and schedule slips at any
major milestone by entering the actuals-to-date at any milestone, and letting
the program calculate the remaining effort and schedule.
Inputs: Same as COCOMO inputs.
Processing
While
REVIC processing is mostly the same as Intermediate COCOMO, it provides a
single weighted "average" distribution for effort and schedule, along
with the ability to allow the user to vary the percentages in the system
engineering and DT&E phases. On the other hand, COCOMO provides a table for
distributing the effort and schedule over the development phases, depending on
the size of the code being developed. REVIC has been enhanced by using
statistical methods for determining the lines of code to be developed. Low,
high, and most probable estimates for each CSC are used to calculate the effective
lines of code and standard deviation. The effective lines of code and standard
deviation are then used in the equations, rather than the linear sum of the
estimates. This quantifies, and to some extent, reduces the existing
uncertainties regarding software size. [see Boehm's Software Engineering
Economics for a discussion of effective lines of code]. REVIC automatically
performs sensitivity analysis showing the plus and minus three sigma values for
effort, and the approximate resultant schedule.
Outputs
The user is presented with a menu allowing
full exercise of the analytical features and displays of the program. All
inputs are easily recalled and changed to facilitate analyses and the user can
constrain the solution in a variety of ways.
Calibration and Accuracy
REVIC's
coefficients have been calibrated using recently completed DoD projects
(development phase only) by using the techniques in Dr. Boehm's book. On the
average, the values predicted by the effort and schedule equations in REVIC are
higher than in COCOMO. A study validating REVIC equations using a database
different from that used for initial calibration was published by the Air
Force's HQ AFCMD/EPR. In terms of accuracy, the model compares favorably with
expensive commercial models.
The
level of accuracy provided by the model is directly proportional to the user's
confidence in the lines-of-code (LOC) estimates and a description of the
development environment. When little is known about the project or environment,
the model can be run leaving all environment parameters at their default
(nominal) settings. The only required input is LOC. As the details of the
project become known, the data file can be reloaded into the program, and the
nominal values can be changed to reflect the new knowledge permitting continual
improvement of the accuracy of the model.
Maintenance Estimate
REVIC
provides an estimate for software maintenance over a fifteen year period by
using the Boehm's COCOMO equation:
(3) MMam = MMnom * ACT P (MFi), where MMnom
is the result of equation (1) without multiplying by the environmental factor
(Fi); ACT is annual change traffic as a percentage, and Mfi is the
environmental factors for maintenance.
REVIC
provides a default percentage of ACT and allows it to be changed. REVIC also
assumes a transition period after delivery of the software, during which
residual errors are found before reaching a steady state condition. This
provides a declining, positive delta to the ACT during the first three years.
Beginning the fourth year, REVIC assumes the maintenance activity consists of
both error correction and new software enhancements.
Other Reference Materials
There
is context-sensitive help available on-line while running REVIC, and the
information is enough to input data and obtain results in all cases. However,
the developers recommend that Boehm's Software Engineering Economics be read to
fully understand the implications of parametric modeling.
Contact
The Air Force Cost Analysis Agency has
assumed responsibility for REVIC upkeep and distribution. For suggestions for
upgrades or problem reporting, contact:
Air Force Analysis Agency
AFCSTC/IS (REVIC)
1111 Jefferson Davis Highway, Suite 403
Arlington, VA 22202
[information current as of 5/92]
(703) 604-0412
REVIC is available on the Air Force cost
bulletin board at (800) 344-3602 or from Washington, D.C. at . (703) 604-0412.
Connection should be 1200 or 2400 BAUD with 8 bits, no parity, and one stop
bit. [information current as of 5/92]
REVIC and its user manual are also
available on the Air Force Software Technology Support Center (STSC) bulletin
board at autovon 458-7653 or (801) 777-7653. Connection at 2400 BAUD with 8
bits, no parity, and one stop bit. For access problems call Vern Phipps or Rick
Dahl at (801) 777-7703. [information current as of 5/92]
SASET
SASET
is a sophisticated software cost estimating model built by Martin Marietta
Astronautics during 1986-1990 under contract with the Naval Center for Cost
Analysis under auspices of the Office of Naval research. Enhancements to the
model were accomplished under contract with both the Navy and Air Force cost
centers. The model combines database information from over 500 successfully
completed software projects with "expert" factors to determine software
development and maintenance costs, schedules, and sizing numbers used by
engineers, estimators, and top-level management.
Cost
estimating relationships were created, project complexity factors were
established, and independent variables were quantified. The result was
database-derived software estimating equations for assembly and high-order
language software. These equations and resulting software parametric models
have been validated by comparing project sizing, labor actuals, and schedules
with SASET outputs.
During
data collection, analysis, and model requirements generation activities, it was
decided that the parametric model would include the entire software development
life cycle from systems requirements through systems test, with an option to
add maintenance, and provide budget and schedule outputs for the engineering
development organizations. The database collection approach consists of
decomposing software actuals by CSCI class, type and language.
Inputs
SASET
starts from an initial state of no information about the software project, and
then proceeds to prompt the user in an orderly fashion for the information
necessary to gain insight and emulation of project environment, complexities,
and sizing for up to 50 CSCI's, to produce schedule and effort outputs.
Processing
SASET
is a database-derived expert system. The calibrated equations for effort budget
and schedule are computed for the system environment, and software complexity,
brought together for a common set and then multiplied against the equivalent
new HOL SLOC.
Outputs
The
computerized model has the capability of sizing, costing, scheduling and
integrating up to 50 multiple CSCI's simultaneously. The model determines a
labor estimate expressed in staff months and spread over the phases and
subphases of software development life cycle for each individual CSCI and the
total project and helps to establish a logical development sequence. The model
also identifies an optimal schedule and effort.
Calibration
All
input variables and calibration constants of SASET are open and capable of
being changed. The calibration process requires a set of software development
records as input. The required data from each record includes staff hours,
source lines of code, schedule, and project complexity. Records are sorted by
class (manned flight, avionics, ground, etc.) and type of software (system,
application, support), then run through multiple regression analysis for
productivity constants for each type of software.
Life Cycle Considerations
SASET
performs detailed environment effort allocation across subphases of the
development life cycle. It will also spread calculated maintenance effort
across time. The effort included is for engineering organizations only; any
other efforts needing coverage need to be added manually.
Contact
Air Force Analysis Agency
AFCSTC/IS (REVIC)
1111 Jefferson Davis Highway, Suite 403
Arlington, VA 22202
[information current as of 5/92]
(703) 604-0412
SEER-SEM
SEER-SEM
is part of a family of software and hardware cost, schedule and risk estimation
tools. SEER models run on IBM, Macintosh, and Sun/UNIX platforms with no
special hardware requirements. SEER-SEM is used throughout the aerospace and
defense industry on two continents. All issues found in today's software
environments are addressed.
Inputs
SEER-SEM
accepts source lines of code (SLOC) or function points or both. When selecting function
points, the user may use IFPUG standard function points or SEER function-based
inputs which include internal functions. Users follow a Work Breakdown
Structure (WBS) describing each CSCI, CSC, and CSU (module or element) to be
estimated. Knowledge bases are used to provide fast and consistent inputs
describing complexity, personnel capabilities and experience, development
support environment, product development requirements, product reusability
requirements, development environment complexity, target environment, schedule,
staffing and probability. Users can modify all inputs to their specifications
at any time.
There
are four sets of knowledge bases that automatically input environment factors.
These knowledge bases cover a wide variety of scenarios and help users produce
fast and reliable estimates. Knowledge bases are easily calibrated to user
environments to give quick and accurate estimates for the entire life cycle.
Users can also change and modify each input at any time. Knowledge bases include
the following:
Platform describes the primary operating platform. Platform knowledge bases
include avionics, business, ground-based, manned space, unmanned space,
shipboard, and more.
Application describes the overall function of the software under
estimation. Application knowledge bases include computer-aided design, command
& control, database, MIS, office automation, radar, simulation, and more.
Development Method describes the development methods to be used during
the development. These knowledge bases include Ada, spiral, prototyping, object
oriented design, evolving, traditional waterfall, and more.
Development Standard describes the development documentation, quality,
test standards and practices which will be followed during the development.
These knowledge bases include commercial, ISO-9000, 2167A, 1703, 1679, 7935A
and more.
Processing
SEER-SEM
uses proprietary algorithms which are found in the back of the User's Manual.
Parameter (input) sensitivities and other insights into the model are also
found in the user's documentation. Knowledge bases can be printed out by users.
SEER-SEM utilizes a unique process that simulates a 10,000 iteration Monte
Carlo for risk analysis.
Outputs
SEER-SEM
has almost 30 informative reports and charts covering all aspects of software
costs, schedules and risk. The Quick Estimate Report is easily tailored to
instantly give the user specific details for trade-off analyses and decision
support information. A Detailed Staffing Profile follows SEI suggested staffing
categories. Risk reports and graphs based on person months, costs, and schedule
are standard features. SEER-SEM gives a minimum schedule output. However,
schedules, personnel, and other factors can be changed to give effort and cost
tradeoffs.
Calibration
Calibration
of SEER-SEM involves the effort to customize input values to more closely
reflect particular program development characteristics. SEER-SEM's Design To
Technology and Design To Size functions provide the tools for calibration activities.
The SEER knowledge bases are flexible and easy to create and modify, providing
the user with a mechanism for building custom calibrated knowledge bases.
Life Cycle Considerations
SEER-SEM
estimates all elements of the life-cycle, beginning with the preliminary design
phase and ending with software maintenance. SEER-SEM has many features which
support Life Cycle Cost Analysis. Total life cycle cost is reported in the
Basic Estimate Report, Activity Report, and the Labor Allocation Reports. The
Set Reference feature allows for quick analysis of what happens to both
development and maintenance costs with the change of any parameter.
Maintenance
SEER-SEM
baseline maintenance includes all adaptive, perfective and corrective
maintenance. Additionally, you may add annual change rate and growth percents
to anticipate any functional growth or enhancements over the software
maintenance period. Enhancements and block upgrades can also be estimated.
Contact
Galorath Associates, Inc.,
SEER Technologies Division
P.O. Box 90579
Los Angeles, CA 90009 (3 1 0)670-3404.
SLIM
SLIM
for Windows 3.1 was developed by Quantitative Software Management, Inc. (QSM).
All of the theory behind the model has been published by Prentice Hall in 1992 in
the book, Measures for Excellence: Reliable Software, on Time, Within Budget
by Lawrence H. Putnam and Ware Meyers. SLIM is based on QSM's Software
Equation. This was derived from the Rayleigh-Norden model and has been
validated over a 15 year time period with thousands of real, completed
projects. The equation takes the conceptual form:
(1) Quantity of Function = Process
Productivity * Effort * Schedule
This
means that the product of the time and effort coupled with the process
productivity of the development organization determines how much function can
be delivered. Extensive empirical study of software data has shown that very
strong linearities exist in software behavior. This is taken into account by
the calculational form of the software equation and discloses how these
non-linearities can be exploited by management. The calculation form of the
equation is expressed:
(2) Size = Process Productivity Parameter *
(Effort/B)(1/3) * Time(4/3)
where,
1. The
process Productivity Parameter is the development process proficiency of the
organization. It is determined from historical data.
2. Size
is the quantity of function created in source lines of code written, function
points, objects, or other measures of function.
3. Effort
is the development effort required. It includes all categories of labor used on
the project. Effort is consistent with the time specified below.
4. B
is a complexity adjustment factor. It provides for specialized skills for
integration testing, documentation, and management as the size of the system
increases.
5. Time
is the elapsed calendar development time from the start of detailed design
until the product is ready to enter into operational service (frequently this
is a 95% reliability level).
SLIM
is applicable to all types and sizes of projects. It computes schedule, effort,
cost, staffing for all software development phases and reliability for the main
construction phase. Because the software equation effectively models design
intensive processes and is not methodology dependent, SLIM works well with
waterfall, spiral, incremental, and prototyping development methodologies. It
works with all languages, and function points as well as other sizing metrics.
It is specifically designed to address the concerns of senior management, such
as:
1. What
options are available if the schedule is accelerated by four months to meet a
tight market window?
2. How
many people must be added to get two months schedule compression and how much
will it cost?
3. When
will the defect rate be low enough so I can ship a reliable product and have
satisfied customers?
4. If
the requirements grow or substantially change, what will be the impact on
schedule, cost, and reliability?
5. How
can I quantify the value of my process improvement program?
Computing Platforms
SLIM
is available for use on IBM PC or compatible machines running Windows 3.1. SLIM
is licensed on an annual basis with full support and free upgrades.
Inputs
The
primary input for SLIM is SLOC, function points, objects, CSCI, or any valid
measure of function to be created. The model uses size ranges for input:
minimum, most likely, and maximum. Other important inputs include:
1. Language:
Multiple choices and mixes.
2. System
Type: One of nine (business, scientific, command & control, real time,
etc.).
3. Environmental
Information: Tools, methods, practices, database usage; standards in place and
adherence and usage of those standards.
4. Experience:
Personnel skill and qualifications.
5. Process
Productivity Parameter: a macroscopic factor determined by calibration from
historical data. It is a reliable tuning factor that accurately reflects
application complexity and the efficiency of the organization in building
software. This is a secsitive parameter that is capable of measuring real
productivity and process improvement. SLIM contains and expert system to
determine the Process Productivity Parameter when the user has no historical
data. This [non-linear] parameter is dealt with in terms of a linear scale
ranging from 0 to 40.
6. Management
Constraints: Maximum allowavle schedule, manimum cost, maximum and minimum
staff size, required reliability at the time the software goes into service as
well as the desired probabilities for each of these constraints.
7. Accounting: Labor rates, inflation rates,
and other economic factors.
8. Flexibility:
Extensive tailoring for milestones, phase definitions, and fraction of time and
effort applied to each phase based on the organization’s own history.
Processing
There
are three primary modes of operation: building and using an historical
database, performing estimating and analysis, and creating presentations and
reports.
For
estimation, SLIM uses the software equation in conjunction with management
constraints for schedule, cost, staffing and required reliability to determine
an optimal solution with the highest probability of successful completion.
Through Monte Carlo simulation techniques, the size range estimates are mapped
through the software equation to provide estimates of the uncertainty in
schedule, cost staffing and reliability. The solution obtained can be compared
with the user's historical data and QSM's historical data to test its
reasonableness. This discloses impossible or highly improbable solutions so
that expensive mistakes are avoided.
Outputs
The
primary output of SLIM is the optimal solution, which provides development
time, cost, effort and reliability expected at delivery. It also provides
comprehensive sensitivity and risk profiles for all key input and output
variables, and a consistency check with similar projects. SLIM's graphical
interactive user interface makes it easy to explore quickly extensive tradeoff
and "what if" scenarios including design to cost, schedule, effort
and risk. It has 181 different output tables and graphs from which the user can
choose. These outputs constitute a comprehensive set of development plans to
measure and control the project while it is underway.
Calibration
The
process productivity parameter for SLIM can (and should) be obtained by
calibration using historical data. All that is required are project size,
development time and effort. These numbers are input into the software equation
to solve for the process productivity. The historical data can also be used to
compare with any current solution to compare for reasonableness.
Life Cycle Considerations
The
user can customize his life cycle in terms of phases, sub-phases, staffing
profile shapes and milestones. Explicit shapes are provided after delivery to
deal with maintenance, ongoing support and enhancement releases.
Contact
Quantitative
Software Management, Inc.
1057 Waverly Way
McLean, VA 22102
(703) 790-0055
SOFTCOST-R & SOFTCOST-ADA
The
SoftCost-R model was developed by Dr. Don Reifer based on the work of Dr.
Robert Tausworthe of the NASA Jet Propulsion Laboratory. SoftCost is now
marketed by Resource Calculations, Inc. of Englewood, Colorado. It contains a
database of over 1500 data processing, scientific and real-time programs.
SoftCost-R is applicable to all types of prograrns and considers all phases of
the software development cycle. The model is available for lease on IBM PC's. A
separate model SoftCost-Ada is available to model Ada language and other
object-oriented environments.
SoftCost-Ada
has been developed to match the new object-oriented and reuse paradigm which
are emerging not only in Ada, but also C++ and other object-oriented
techniques. It contains a database of over 150 completed projects, primarily
Ada.
SoftCost-R Inputs
A
key input of SoftCost-R is size, which can either be directly input in SLOC or
computed from function points. SoftCost-R uses a more sophisticated sizing
model than COCOMO; besides reused code, sizes of modules added or deleted may
be included. The other inputs are in four categories like COCOMO. Some
SoftCost-R inputs are similar to COCOMO, but many of the more than thirty
inputs are unique. Examples of unique inputs are use of peer reviews, customer
experience, and degree of standardization. Each input except size requires a
rating ranging from "very low" to "extra high", with
"nominal" ratings having no effect on effort calculations. SoftCost-R
also uses COCOMO inputs to compare the results of SoftCost-R with those of an
updated version of COCOMO.
SoftCost-Ada Inputs
In
the main, the inputs are the same as SoftCost-R, with some changes to reflect
the new paradigm. There is no COCOMO comparison.
Processing
SoftCost-R
is not a simple regression model. It uses powerful multivariable differential
calculus to develop solutions relying on the T-W probability distribution. This
provides the ability for the user to perform "what-if" analysis and
look at what would happen to schedule if effort were constrained. Such a
capability is not present in COCOMO. SoftCost-R is one of the few models for
which the mathematical algorithms are completely described in the user's
manual. The SoftCost-R equation is:
(1) PM = P0 * Al * A2 * (SLOC)B
where,
1. PM = number of person-months,
2. P0 is a constant factor that may be
calibrated,
3. A 1 is the "Reifer cost factor"
which is an exponential product of nine inputs,
4. A2 is a productivity factor computed from
22 inputs,
5. B is an exponent which may be calibrated.
The
user's manual illustrates values assigned to ratings for all model inputs to
help the user understand the effect of each input on effort and schedule.
Outputs
SoftCost-R
computes an estimate in person-months of effort and schedule for each project,
plus a productivity value. Other outputs include a side-by-side comparison with
a recent version of COCOMO, several "what if" analysis options, a
resource allocation summary for any of three development methods (traditional
waterfall, incremental development, or Ada object-oriented), and schedule
outputs for Gantt and PERT charts. SoftCost-Ada output formats are similar, and
can interface with project planning tools in the same way.
Calibration
The
model contains a calibration file which contains values for multiple
calibration constants and cost drivers. The user may change these values to
better describe the user's unique environment, and store alternative
calibration and WBS files for different jobs. SoftCost-Ada and SoftCost-R are
similar.
Life Cycle Considerations
SoftCost-R
contains a separate life cycle model for support costs. In addition to
SoftCost-R development inputs, life cycle inputs include annual change traffic,
length of support period, a sustaining engineering factor, and economic
factors. In addition to annual and total support costs, the life cycle model
has optional reports for various staffing options, fixed levels of maintenance,
and fixed work force levels. Both SoftCost versions are similar, and use the
same staff limited approach to life cycle resource allocation.
Contact
Mr. A.J. (Tony) Collins
Resource Calculations, Inc.
7853 East Arapahoe Court, Suite 2500
Englewood, CO 80112-1361
Telephone: (303) 267-0379
Facsimile: (303) 220-5620
OTHER
MODELS
CHECKPOINT
Software Productivity Research, Inc.
I New England Park
Burlington, MA 01803
(617) 273-0140
COSTAR
SoftStar Systems
28 Ponemah Road
Arnherst,NH 03031
(603) 672-0987
SOFTSTY R
Softstar Systems
28 Ponemah Road
Arnherst,NH 03031
(603) 672-0987
Sells COSTAR, a COCOMO variant; supports Ada
COCOMO and function points
IBM PC, VAX/VMS
Dan Ligett (personal letter - Jan 16, 1987)
[info checked brochure 10/92]
SWAN
IIT Research Institute
201 Mill Street
Rome, NY 13440
(315)336-2359
Fax: (315) 339-7002
Personto Contact: Anthony H. Williarns
(315)339-7105 [ok 12/13/93]
A COCOMO variant developed for US Arrny, PM
Training Devices, 12350 Research
Parkway, Orlando, FL. 32826
Written in Ada; runs on IBM AT, MS-DOS 3.0 or
higher
Includes Ada COCOMO & Function Point
Analysis
Target Software
Dr. George Bozoki
552 Marine Parkway, #1202
Redwood City, CA 94065
(415)592-2560
SSM, the Software Sizing Model
Computer Economics
4560 Admiralty Way, Suite 109
Marina Del Rey, CA 90292
(213) 827-7300
Jensen Model ("System 4"), CEIS
(CEI Sizer), training
[ref. 1987 IITRI Software Sizing model paper]
Mainstay Software Corporation
1099 18th Street, Suite 2920
Denver, COLO 80202
(303) 298-8961
Dan Walkovitz, President
Product: Mainstay - an analytical database
system
[ok 8/92, Setzer]
Howard Rubin Associates, Inc.
1666
Massachusetts Avenue, Suite 7
Lexington, MA.
02173
(617)861-7171
Products:
FPXpert - an expert system for function point
counting, analysis and management;
RA-METRICS - a measurement tool and metrics
respository; primarily oriented toward information systems, promotes concept of
"measurement dashboard"
COSTMODL
Developed at the Software Technology Branch
at NASA/JSC to be used for Space Station Freedom Software Support Environment
and will be available from COSMIC.
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