Applying COCOMO II Effort Multipliers to Simulation Models

16th International Forum on COCOMO and Software Cost Modeling

Jongmoon Baik and Nancy EickelmannSoftware and System Engineering Research Laboratory

Motorola Labs

Oct 25, 2001

Outline

• Problems

• What is Model & Simulation?

• Simulation Model Comparison

• Why COCOMO II Parameters?

• Example– System Test Process – DSD (Distributed Software Development)

• Future Work

Problems

• Most Critical Decision Early in the lifecycle– Little information available to assess the

proposed process changes and technology insertions

• Difficult to understand problems in the current complex processes

Model and Simulation

• Model“ An abstraction or simplified representation of a real or

conceptual complex system. It is designed to display significant features and characteristics of the system under study.”

• Simulation“Computerized model that possesses the characteristics

described above and that represents some dynamic system or phenomenon.”

Primary Benefits of Simulation

• Process Characterization• Quantitative Analysis for Proposed Process

Changes and Technology Insertions– Support Decision Making and Risk Assessment

• Support to achieve Higher CMM levels– Quantitative process Management and software Quality

Management (CMM-Level 4)– Process/Technology Change Management and

Continuous Process Improvement (CMM_Level 5)

• Project Planning including Effort/Schedule/Cost Estimation

Change Process Comparison

Proposed Plan for Process Changes and Technology Insertions

Process Manager, Team, or Cost Estimators

Implementation of Process Changes and Technology

Insertions

Refine

Feed Back

Analysis

Proposed Plan for Process Changes and Technology

Insertions

Simulation Model

Simulation Model

Implementation of Process Changes and Technology

Insertions

Process Manager, Team, or Cost

Estimators

Feed Forward

Refine Quantitative Control Feed Back

Simulation Model Comparison

Continuous Model Discrete Event Model

Advantages -Continuous changes of process & product attributes-Captures stable or unstable feedback loops-Predict the unanticipated side effects from changes of process and product attributes

-Easy to represent queues-Delay b/w activities based on available resources-Unique attributes for each entity-Capture the effects of variation in the entities for each activity-Capture inter-dependencies b/w activities

Disadvantages

-Difficult to describe process steps

(Explicit mechanism for controlling the discrete activity sequence)-No individual entity and attributes-Same rate for each model run

-Variable changes only at the event times-Difficult to represent simultaneous activities

Common Use Economics, System Dynamics, Scientific (biology, Chemistry, Physic) processes, Electronics, Control Systems

Business Process Reengineering, Networks, Systems Engineering, Manufacturing

Why COCOMO II Parameters?

• Widely accepted public cost model – Calibrated with 161 actual project data

• Objective impact analysis for each factor- If There is no data available for the parameter

• Can be calibrated from the organization’s historical data

• Dynamic effect can be added into simulation model– Different rating values over time (COCOMO81

Detailed COCOMO)

COCOMO II EMs to Simulation

Product:RELY, DATA, DOCU,CPLX, RUSE

Platform:TIME, STOR, PVOL

Personnel:ACAP, APEX, PCAP,PLEX, LTEX, PCON

Project:TOOL, SITE, SCED

System Test Process Simulation

• Baseline a current System Test Process• Predict impact of process change and technology

insertion on schedule, quality, effort

SystemRequirements

SystemArchitecture

RequirementsSystemDetailedDesign

BoxRqmts

BoxDesign

SystemFunctional

Requirements

Box(auto)Coding

BoxUnit Test

BoxSystem

Test

SystemEarly SDLIntegration

testing

SystemEarly

Integrationtesting

System

IntegrationTest

System

SystemTest

SubsystemIntegration

Test

SubsystemSystem Test(host/target)

BoxIntegration

Test

SystemBetaTest

TextText

TextText

eMSCeMSC

SL + SDLSL + SDL

TextText

eMSCeMSC

SDL(process), CSDL(process), CBox Validation ActivitiesBox Validation ActivitiesSystem Validation ActivitiesSystem Validation Activities

eMSCeMSCExtended Message Sequence ChartsExtended Message Sequence ChartsSDLSDL Specification and Design LanguageSpecification and Design LanguageSLSL “SL”, data language“SL”, data language

eMSC, SDL(blocs)eMSC, SDL(blocs)

SDL (blocs)SDL (blocs)

Example: LTEX

• Used to assess the impact of SDL/MSC insertion into a system test process

• Map SDL Ranks (1-5) to LTEX ratings (VL to VH)

START

-

always takes too long

MEETING

PRESENT ARGUMENTS

COMPANY X OPINION

MOTOROLA OPINION

THROW OUT IDEA

COMPANY Y OPINION

AGREESUPERIOR ARGUMENT

COFFEE BREAK

where the real work is done

PROPOSE DECISION

MEETING AGREES

LUNCHwell deserved

MOTOROLAWITH

SDL

Test Planning

Test Development

Test Execution

Defect Tracking

Schedule Saving by LTEXMeeting Duration

0

0.5

1

1.5

1 2 3 4 5 6 7 8 9 10 11 12

Build

Du

rati

on

(D

ays)

VH

H

N

L

VL

Defect Tracking Duration

0

0.5

1

1.5

2

1 2 3 4 5 6 7 8 9 10 11 12

Build

Du

rati

on

(D

ays)

VH

H

N

L

VL

• Total Savings– Nominal (N to VH) 10.05 Days– Maximum (VL to VH) 24.51 Days

System Test Duration

0

5

10

15

1 2 3 4 5 6 7 8 9 10 11 12

Build

Du

rati

on

(D

ays)

VH

H

N

L

VL

DSD [Distributed Software Development]

• Communication Breakdown• Coordination Breakdown• Geographical Dispersion• Loss of Team Cohesiveness• Cultural DifferencesSource: IEEE Software March/April 2001, Robert D. Battin et. al.

“Leveraging Resources in Global Software Development”

SITE

PMAT

TEAM

PREC TOOL

Future Work

• More Application of Effort Multipliers to Simulation of Process Segments

• Refine the simulation model Through the calibration of applied COCOMO II parameters

• Expand simulation model to find out the dynamic impacts of the parameters