Fielding Systems-of-Systems, Riding the agile sw tiger

1 INCOSE_IL 2007Integration-unsolved questionFielding SoS – Ride the SW Tiger

The Fourth National Conference INCOSE_IL 2007

• Session: Integration – Unsolved Question• Lecture Name: Fielding Systems-of-Systems –

Ride the Software Tiger• Presented by Sergey Tozik


Outline• Challenge:

Fielding of SW-intensive SoS

• Method:

Knowledge driven IVVT

• Technique:

Explorative Modeling


Cap

abil

ity

Cap

abil

ity

Cap

abil

ity

Cap

abil

ity

SpecifyNeeds

SoS: Complexity of Operation

System

System

System

ModifySystems

Integrate

Test

Operate


SoS: Emergent Dependency

ReqsSystem 1

ReqsSystem 2

ReqsSystem 3

ChangeSystem 1

ChangeSystem 2

No ChangeSystem 3

No ChangeSystem 2

ChangeSystem 3

Project ACapability A

Project BCapability Bindependent

Capability A Capability Bdependent


• Simple designs, Agile development very short development

• Interdependence of systems abundance of surprises very long fielding times

• Challenge for integrators & testers: hang for your life and still deliver

SW Challenge


Hang for Your life, dear…It’s AGILE!!!!


What Users Want?

1. More Mission Capabilities

2. Easier Operation

3. No Surprises


Elements of Solution

• Focus on “Knowledge Creation”

instead of “Test against Spec”

• Hunt for unintended consequences

• Know what works and field it!


MaSK Methodology

• Explorative Modeling

• Semi-automatic test generation

• Session-based testing

• Knowledge factory concept


Integration Engineer Roles

Analyst

Knowledge

Test Ideas

Information

Information Gatherer Tester

Stakeholder

Directions of Inquire

• Information Gatherer searches the sources for information and clues about past and supposed behavior

• Tester creates and executes tests to capture information about actual behavior

• Analyst directs the gatherers, creates knowledge and morphs it to stakeholders’ needs


Knowledge Generation Steps

1. Gather Initial Batch of Information2. Analyze Information3. Create Knowledge4. Detect Knowledge Gaps5. Direct the Hunters for more Info6. Gather More Information7. Go to Step 2

Never Stop Asking Questions!


Sources of Information

1. Users’ Manuals

2. Requirements

3. Design Documentation

4. Interface Control Documents

5. Test Results

6. Interviews of Developers

7. Interviews of Users


The Knowledge Factory Workflow

Gather Info Info Create/Refine Models

Use Model Technical Model

Analyse ModelsQuestion Insight

Tests

1..N

1..N

1..N

Plan, Execute Tests

Test Results

Analyse Test ResultsReport1..N

Publish

Customer

1..N

Stakeholder Value Loop

KnowledgeRefinement

Loop

TestingLoop

InfoHunting

Loop


Explorative Modeling

1. Motivation: technique for fast learning with limited domain expertise

2. Language: Cause-Effect Graphs

3. Use Models captures Business Processes in Users’ Language

4. Technical Models capture Design Information in Developers’ Language


Have You a SPEC?No!!?

I beg You, Not Again!!!!

ExplorativeModeling

Tool


Processing

Trigger

Input Entity

Pre-ContitionPost-Condition

Output Entity

Basic link in Cause-Effect Graph

Data, Matter, Energy

Environment State

System Event causes changes in

system/environment

Data, Matter, Energy

EnvironmentState

Event


Knowledge Gaps Discovery

1. Not enough information to complete Use Model

2. Not enough information to understand processes initiated by System Event

3. Inconsistencies in information sources

4. Developer’s insecurity (Oops factor)


Example – Story of Two Cities

• Two neighbor cities

• Each city has Traffic Light Control System (TLCS)

• Every TLCS has manual and automatic modes

• Each TLCS did the job well until some day suddenly

the effectiveness of the AUTO mode have dropped.

• Why?

• We’ll try to generate clues using Exploratory

Modeling technique


Use ModelFocus: visible system behavior, user actions

Identify System Events (Identify Trigger)

• Set System to Manual (User)

• Set System to Automatic (User)

• Change Single Traffic Light Mode (User)

• Change Traffic Light Pattern (System, Periodic)

• Respond to Traffic Light Pattern (Natural)

Connect Events with I/O Entities/Conditions

Build Cause-Effect Graph


System AAuto/Man

Operator City AOperator City B

Set to MANUAL

Set to AUTO

Set to MANUAL

Set to AUTO

System BAuto/Man

Generate TrafficLight Pattern - City A

Generate TrafficLight Pattern - City B

City ATraffic Light Pattern

City BTraffic Light Pattern

Respond to Traffic Lights

City ATraffic Pattern

Respond to Traffic Lights

City BTraffic Pattern

MutualInfluence

Change Traffic Light

Change Traffic Light

Disable when AUTO

Disable when AUTO

System ACycle Clock

System BCycle Clock

Display TrafficPatternDisplay Traffic

Pattern

Cause-Effect Graph

AutoFeedback

Loop

TransientGenerator

PeriodicActivation

Nothing happens without a reason!

AutoFeedback

Loop

ManualFeedback

Loop


Directions for Inquiry

1. Analyze mutual influence and concurrency of automatic control feedback loops

2. Analyze mutual influence and concurrency of manual control feedback loops

3. Analyze mutual influence of automatic and manual feedback loops

4. Analyze concurrency of AUTO/MANUAL transients


Direct Test Case Derivation

1. Identify EVENT

2. Prepare INPUT ENTITYs for the EVENT

3. Set INPUT CONDITIONs for the EVENT

4. Initiate EVENT

5. Verify OUTPUT ENTITYs

6. Verify OUTPUT CONDITIONs


5-Step Test Cycle

1. Design Initial Test Event

2. Execute Initial Test Event, Gather Data

3. Analyze Data, Identify Knowledge Gaps

4. Execute Investigative Test, Gather Data

5. Analyze Data, Draw Conclusions, Report


Technical Models

• Motivation: enrich understanding of System Events

• Analysis of cause-effect chainstriggered by System Events

• Utilize developers’ expertise

• Discover missing conditions and entities

• Technique: anything useful!


What’s Next?

• Enrich Technical Analysis

• Discover appropriate CAD tools

• Add Simulation Capabilities

• Add Knowledge Management Tools

• Evaluate utility of Systems Theory


Summary

• SW + SoS = the real challenge

• Methodology: Knowledge Factory

• Techniques: Explorative Modeling

• There’s still a lot to learn to ride the tiger and survive!

Fielding Systems-of-Systems, Riding the agile sw tiger

Technology

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