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Analysis of System “ility” Synergies and Conflicts
Barry Boehm, USC
NDIA SE Conference October 30, 2014
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Ilities Tradespace and Affordability Analysis
• Critical nature of the ilities – Or non-functional requirements; quality attributes
– Major source of project overruns, failures
– Significant source of stakeholder value conflicts
– Poorly defined, understood
– Underemphasized in project management
– Need for ilities ontology
• Ility synergies and conflicts analysis – Stakeholder value-based, means-ends hierarchy
– Synergies and Conflicts matrix and expansions
– Affordability means-ends hierarchy
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Importance of ility Tradeoffs Major source of DoD system overruns
• System ilities have systemwide impact – System elements generally just have local impact
• ilities often exhibit asymptotic behavior – Watch out for the knee of the curve
• Best architecture is a discontinuous function of ility level – “Build it quickly, tune or fix it later” highly risky
– Large system example below
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Value Conflicts: Security IPT
• Single-agent key distribution; single data copy – Reliability: single points of failure
• Elaborate multilayer defense – Performance: 50% overhead; real-time deadline problems
• Elaborate authentication – Usability: delays, delegation problems; GUI complexity
• Everything at highest level – Modifiability: overly complex changes, recertification
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Proliferation of Definitions: Resilience
• Wikipedia Resilience variants: Climate, Ecology, Energy Development, Engineering and Construction, Network, Organizational, Psychological, Soil
• Ecology and Society Organization Resilience variants: Original-ecological, Extended-ecological, Walker et al. list, Folke et al. list; Systemic-heuristic, Operational, Sociological, Ecological-economic, Social-ecological system, Metaphoric, Sustainabilty-related
• Variants in resilience outcomes
– Returning to original state; Restoring or improving original state; Maintaining same relationships among state variables; Maintaining desired services; Maintaining an acceptable level of service; Retaining essentially the same function, structure, and feedbacks; Absorbing disturbances; Coping with disturbances; Self-organizing; Learning and adaptation; Creating lasting value
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Example of Current Practice
• “The system shall have a Mean Time Between Failures of 10,000 hours”
• What is a “failure?” – 10,000 hours on liveness
– But several dropped or garbled messages per hour?
• What is the operational context? – Base operations? Field operations? Conflict operations?
• Most management practices focused on functions – Requirements, design reviews; traceability matrices; work
breakdown structures; data item descriptions; earned value management
• What are the effects on other –ilities? – Cost, schedule, performance, maintainability?
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Need for ilities Ontology
• Oversimplified one-size-fits all definitions – ISO/IEC 25010, Reliability: the degree to which a system ,
product, or component performs specified functions under specified conditions for a specified period of time
– OK if specifications are precise, but increasingly “specified conditions” are informal, sunny-day user stories. Satisfying just these will pass ISO/IEC, but fail on rainy-day use cases
– Need to reflect that different stakeholders rely on different capabilities (functions, performance, flexibility, etc.) at different times and in different environments
• Proliferation of definitions, as with Resilience
• Weak understanding of inter-ility relationships – Synergies and Conflicts
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Initial SERC ilities Ontology
• Modified version of IDEF5 ontology framework – Classes, Subclasses, and Individuals
– States, Processes, and Relations
• Top classes cover stakeholder value propositions – Mission Effectiveness, Resource Utilization, Dependability, Flexibiity
• Subclasses identify means for achieving higher-class ends – Means-ends one-to-many for top classes
– Ideally mutually exclusive and exhaustive, but some exceptions
– Many-to-many for lower-level subclasses
• States, Processes, and Relations cover sources of ility variation • States: Internal (beta-test); External (rural, temperate, sunny)
• Processes: Operational scenarios (normal vs. crisis; experts vs. novices)
• Relations: Impact of other ilities (security as above, synergies & conflicts)
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Ilities Tradespace and Affordability Analysis
• Critical nature of the ilities – Or non-functional requirements; quality attributes
– Major source of project overruns, failures
– Significant source of stakeholder value conflicts
– Poorly defined, understood
– Underemphasized in project management
– Need for ilities ontology
• Ility synergies and conflicts analysis – Stakeholder value-based, means-ends hierarchy
– Synergies and Conflicts matrix and expansions
– Affordability means-ends hierarchy
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Stakeholder value-based, means-ends hierarchy
• Mission operators and managers want improved Mission Effectiveness
– Involves Physical Capability, Cyber Capability, Human Usability, Speed, Accuracy, Impact, Endurability, Maneuverability, Scalability, Versatility, Interoperability
• Mission investors and system owners want Mission Cost-Effectiveness – Involves Cost, Duration, Personnel, Scarce Quantities (capacity, weight, energy, …);
Manufacturability, Sustainability
• All want system Dependability: cost-effective defect-freedom, availability, and safety and security for the communities that they serve – Involves Reliability, Availablilty, Maintainability, Survivability, Safety, Security
• In an increasingly dynamic world, all want system Flexibility: to be rapidly and cost-effectively changeable – Involves Modifiability, Tailorability, Adaptability
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7x7 Synergies and Conflicts Matrix
• Mission Effectiveness expanded to 4 elements – Physical Capability, Cyber Capability, Interoperability, Other
Mission Effectiveness (including Usability as Human Capability)
• Synergies and Conflicts among the 7 resulting elements identified in 7x7 matrix – Synergies above main diagonal, Conflicts below
• Work-in-progress tool will enable clicking on an entry and obtaining details about the synergy or conflict – Ideally quantitative; some examples next
• Still need synergies and conflicts within elements – Example 3x3 Dependability subset provided
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Software Development Cost vs. Reliability
0.8
Very Low
Low Nominal High Very High
0.9
1.0
1.1
1.2
1.3
1.4
1.10
1.0
0.92
1.26
0.82
Relative Cost to Develop
COCOMO II RELY Rating MTBF (hours) 1 10 300 10,000 300,000
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Software Ownership Cost vs. Reliability
0.8
Very Low
Low Nominal High Very High
0.9
1.0
1.1
1.2
1.3
1.4
1.10
0.92
1.26
0.82
Relative Cost to Develop, Maintain, Own and Operate
COCOMO II RELY Rating
1.23
1.10
0.99
1.07
1.11
1.05
70% Maint.
1.07
1.20
0.76 0.69
VL = 2.55 L = 1.52
Operational-defect cost at Nominal dependability = Software life cycle cost
Operational - defect cost = 0
MTBF (hours) 1 10 300 10,000 300,000
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COCOMO II-Based Tradeoff Analysis Better, Cheaper, Faster: Pick Any Two?
0
1
2
3
4
5
6
7
8
9
0 10 20 30 40 50
Development Time (Months)
Cos
t ($M
)
(VL, 1)
(L, 10)
(N, 300)
(H, 10K)
(VH, 300K)
-- Cost/Schedule/RELY:
“pick any two” points
(RELY, MTBF (hours))
•For 100-KSLOC set of features •Can “pick all three” with 77-KSLOC set of features
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Ilities Tradespace and Affordability Analysis
• Critical nature of the ilities – Or non-functional requirements; quality attributes
– Major source of project overruns, failures
– Significant source of stakeholder value conflicts
– Poorly defined, understood
– Underemphasized in project management
– Need for ilities ontology
• Ility synergies and conflicts analysis – Stakeholder value-based, means-ends hierarchy
– Synergies and Conflicts matrix and expansions
– Affordability means-ends hierarchy
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Legacy System Repurposing
Eliminate Tasks
Eliminate Scrap, Rework
Staffing, Incentivizing, Teambuilding
Kaizen (continuous improvement)
Work and Oversight Streamlining Collaboration Technology
Early Risk and Defect Elimination
Modularity Around Sources of Change Incremental, Evolutionary Development
Risk-Based Prototyping
Satisficing vs. Optimizing Performance Value-Based Capability Prioritization
Composable Components,Services, COTS
Affordability Improvements and Tradeoffs
Get the Best from People
Make Tasks More Efficient
Simplify Products (KISS)
Reuse Components
Facilities, Support Services
Tools and Automation
Lean and Agile Methods
Evidence-Based Decision Gates
Domain Engineering and Architecture
Task Automation Model-Based Product Generation
Value-Based, Agile Process Maturity
Affordability and Tradespace Framework
Reduce Operations, Support Costs
Streamline Supply Chain Design for Maintainability, Evolvability Automate Operations Elements
Anticipate, Prepare for Change Value- and Architecture-Based Tradeoffs and Balancing
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Costing Insights: COCOMO II Productivity Ranges
Productivity Range 1 1.2 1.4 1.6 1.8 2 2.2 2.4
Product Complexity (CPLX)
Analyst Capability (ACAP)
Programmer Capability (PCAP)
Time Constraint (TIME)
Personnel Continuity (PCON)
Required Software Reliability (RELY)
Documentation Match to Life Cycle Needs (DOCU)
Multi-Site Development (SITE)
Applications Experience (AEXP)
Platform Volatility (PVOL)
Use of Software Tools (TOOL)
Storage Constraint (STOR)
Process Maturity (PMAT)
Language and Tools Experience (LTEX)
Required Development Schedule (SCED)
Data Base Size (DATA)
Platform Experience (PEXP)
Architecture and Risk Resolution (RESL)
Precedentedness (PREC)
Develop for Reuse (RUSE)
Team Cohesion (TEAM)
Development Flexibility (FLEX)
Scale Factor Ranges: 10, 100, 1000 KSLOC
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Staffing
Teambuilding
Continuous Improvement
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COSYSMO Sys Engr Cost Drivers
21 10-30-2014
Teambuilding
Staffing
Continuous Improvement
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Conclusions • Ilities or non-functional requirements are success-critical
– Major source of project overruns, failures
– Significant source of stakeholder value conflicts
– Poorly defined, understood
– Underemphasized in project management
• Ilities ontology clarifies nature of ilities – Using value-based, means-ends hierarchy
– Identifies sources of variation: states, processes, relations
– Relations enable ility synergies and conflicts identification
• Continuing SERC research creating tools, formal definitions
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Backup charts
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Legacy System Repurposing
Eliminate Tasks
Eliminate Scrap, Rework
Staffing, Incentivizing, Teambuilding
Kaizen (continuous improvement)
Work and Oversight Streamlining Collaboration Technology
Early Risk and Defect Elimination
Modularity Around Sources of Change Incremental, Evolutionary Development
Risk-Based Prototyping
Satisficing vs. Optimizing Performance Value-Based Capability Prioritization
Composable Components,Services, COTS
Affordability Improvements and Tradeoffs
Get the Best from People
Make Tasks More Efficient
Simplify Products (KISS)
Reuse Components
Facilities, Support Services
Tools and Automation
Lean and Agile Methods
Evidence-Based Decision Gates
Domain Engineering and Architecture
Task Automation Model-Based Product Generation
Value-Based, Agile Process Maturity
Tradespace and Affordability Framework
Reduce Operations, Support Costs
Streamline Supply Chain Design for Maintainability, Evolvability Automate Operations Elements
Anticipate, Prepare for Change Value- and Architecture-Based Tradeoffs and Balancing
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Value-Based Testing: Empirical Data and ROI — LiGuo Huang, ISESE 2005
-1.5
-1
-0.5
0
0.5
1
1.5
2
0 10 20 30 40 50 60 70 80 90 100
% Tests Run
Retu
rn O
n In
vest
men
t (RO
I)
Value-Neutral ATG Testing Value-Based Pareto Testing
% of Valuefor
CorrectCustomer
Billing
Customer Type
100
80
60
40
20
5 10 15
Automated test generation (ATG) tool
- all tests have equal value
Bullock data– Pareto distribution% of
Valuefor
CorrectCustomer
Billing
Customer Type
100
80
60
40
20
5 10 15
Automated test generation (ATG) tool
- all tests have equal value
% of Valuefor
CorrectCustomer
Billing
Customer Type
100
80
60
40
20
5 10 15
Automated test generation (ATG) tool
- all tests have equal value
Bullock data– Pareto distribution
(a)
(b)
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Value-Neutral Defect Fixing Is Even Worse
% of Value for Correct Customer Billing
Customer Type
100
80
60
40
20
5 10 15
Automated test generation tool - all tests have equal value
Value-neutral defect fixing: Quickly reduce # of defects
Pareto 80-20 Business Value
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Product Line Engineering and Management: NPS
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Cost-Schedule Tradespace Analysis • Generally, reducing schedule adds cost
– Pair programming: 60% schedule * 2 people = 120% cost
• Increasing schedule may or may not add cost – Pre-planned smaller team: less communications overhead
– Mid-course stretchout: pay longer for tech, admin overhead
• Can often decrease both cost and schedule – Lean, agile, value-based methods; product-line reuse
• Can optimize on schedule via concurrent vs. sequential processes – Sequential; cost-optimized: Schedule = 3 * cube root (effort)
• 27 person-months: Schedule = 3*3=9 months; 3 personnel
– Concurrent, schedule-optimized: Schedule = square root (effort) • 27 person-months: Schedule = 5.5 months; 5.4 personnel
• Can also accelerate agile square root schedule – SERC Expediting SysE study: product, process, people, project, risk
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Context: SERC iTAP Initiative Elements
• Ilities Tradespace and Affordability Project (iTAP) foundations – More precise ility definitions and relationships
– Stakeholder value-based, means-ends relationships
– Ility strategy effects, synergies, conflicts
– USC, MIT, U. Virginia
• Next-generation system cost-schedule estimation models – Initially for full-coverage space systems (COSATMO)
– Extendable to other domains
– USC, AFIT, GaTech, NPS
• Applied iTAP methods, processes, and tools (MPTs) – For concurrent cyber-physical-human systems
– Experimental MPT piloting, evolution, improvement
– Wayne State, AFIT, GaTech, NPS, Penn State, USC 10-30-2014 29
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COSATMO Concept • Co-sponsored by OSD, USAF/SMC • Focused on current and future satellite systems
– Accommodating rapid change, evolutionary development, Net-Centric SoSs, families of systems, future security and self-defense needs, microsats, satellite constellations, model-based development
– Recognizes new draft DoDI 5000.02 process models • Hardware-intensive, DoD-unique SW-intensive, Incremental SW-
intensive, Accelerated acquisition, 2 Hybrids (HW-, SW-dominant) – Covers full life cycle: definition, development, production, operations,
support, phaseout – Covers full system: satellite(s), ground systems, launch – Covers hardware, software, personnel costs
• Extensions to cover systems of systems, families of systems • Several PhD dissertations involved (as with COSYSMO)
– Incrementally developed based on priority, data availability • Upcoming workshop at USC Annual Research Review April 29-
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MIT: ilities in Tradespace Exploration Based on SEAri research
For this plot, Ĉ=C∞
More changeable(ie including flexible, adaptable, scalable
and modifiable)
Colored by outdegree
Enabling Construct: Tradespace Networks Changeability
Survivability
Value Robustness Enabling Construct: Epochs and Eras
Set of Metrics
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GaTech – FACT Tradespace Tool Being used by Marine Corps
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Configure vehicles from the “bottom up”
Quickly assess impacts on performance
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SysML Building Blocks for Cost Modeling GaTech-USC Work in RT46 Phase 2 (Oct-Dec 2013)
• Implemented reusable SysML building blocks – Based on SoS/COSYSMO SE cost (effort)
modeling work by Lane, Valerdi, Boehm, et al.
• Successfully applied building blocks to healthcare SoS case study from [Lane 2009]
• Provides key step towards affordability trade studies involving diverse “-ilities” (see MIM slides)
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Healthcare SoS Case Study [Lane 2009] Implemented Using SysML Building Blocks: Selected SysML Diagrams
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SERC Expediting SysE study: Product, process, people, project; risk factors
Final Database Over 30 Interviews with Gov’t/ Industry Rapid Development
Organizations Over 23,500 words from interview notes
Product, Process, People … all in a Project Context 10-30-2014 35
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CORADMO-SE Rating Scales, Schedule Multipliers
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CORADMO-SE Calibration Data Mostly Commercial; Some DoD
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Case Study: From Plan-Driven to Agile Initial Project: Focus on Concurrent SE
Expected schedule reduction of 1.09/0.96 = 0.88 (green arrow) Actual schedule delay of 15% due to side effects (red arrows) Model prediction: 0.88*1.09*1.04*1.06*1.06 = 1.13
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Case Study: From Plan-Driven to Agile Next Project: Fix Side Effects; Reduce Bureaucracy
Model estimate: 0.88*(0.92/0.96)*(0.96/1.05) = 0.77 speedup Project results: 0.8 speedup Model tracks project status; identifies further speedup potential