4. bonneau - software and systems

8/7/2019 4. Bonneau - Software and Systems

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Software and Systems14 March 2011

Dr. Robert J. Bonneau

Program Manager

AFOSR/RSL

Air Force Research Laboratory

AFOSR

Distribution A: Approved for public release; distribution is unlimited. 88ABW-2011-0781


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2011 AFOSR SPRING REVIEW2311G PORTFOLIO OVERVIEW

NAME: Robert Bonneau

BRIEF DESCRIPTION OF PORTFOLIO:

Provide foundations for design and construction of

software-intensive systems operating in complex

environments

LIST SUB-AREAS IN PORTFOLIO:

Algorithms

Model-based synthesisLanguages

Analysis and verification

Human-machine interaction


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Software & Systems Goals/Payoffs

Systems and Software Goals Enable quantifiable performance evaluation of critical

software systems

Manage software environments in order to preserve vitalmission functions

Comprehensively understand distributed effects in largesoftware infrastructures to predict global system failures

Payoffs

Enable evaluation of mission performance that is criticallydependent on software functions

Enable software and resource policies that guaranteeperformance of software in dynamic heterogeneousenvironments


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Current Program Scope

Language-based assurance New programming languages or language constructs reduce

errors at run-time

Domain-specific languages enhance capabilities for code

generation Formal Analysis and Verification

Verification of system properties based on formal

specifications

Automated reasoning for detection of errors and model-basedsynthesis

Abstract models of systems and their interactions facilitate

automated generation of code


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Current Program Scope

Advanced Algorithms for Real-Time and DistributedSystems

New algorithmic techniques provide theoretical basis for

more efficient and reliable operation in networked and

real-time environments Logic-based approaches for test selection Modeling

Human-Machine Interaction

Cognitive and mathematical approaches allow for

development of new models of human-machine

systems


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Systems and SoftwareAgency Interaction

NITRD Coordinating Group High Confidence Systems and Software (HCSS)

NSF Software Design and Productivity

2010 Workshop on the Future of SoftwareEngineering Research

NASA V&V of Flight Critical Systems Ames Research Laboratory

Human Systems Integration Division Intelligent Systems Division

High Performance Computing Modernization Office Software and Many-Core


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Systems and SoftwareOther funding agencies

Army Research OfficeSoftware investment mostly directed toward information

assurance

ONR

Software and Computing SystemsPrinciples for Correctness and Security Properties

Human Robot Interaction

Perception and Cognitive Control

NSF

- Software and Hardware Foundations

DARPA: Software Producibility

Part of Disruptive Manufacturing Technologies program


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Systems and SoftwareProgram Trends

Model-based Synthesis

Formal Analysis and Verification

Advanced Algorithms for Real-Time and Distributed

Systems

Language-based approaches

Modeling Human-Machine Interaction

Agent-based approaches


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Scalable Model CheckingC. Tinelli U Iowa, C. Barret, NYU

Approach: Formal verification suffers from state space explosion.

Compactly represent logical symbols in scalable nested satisfiability modulotheory (SMT)

Payoff: More automated more scalable verification to handle large

heterogeneous systems

Compact SMT Language Improved Lower DimensionalModel


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Automated Model RevisionKulkarni, Mich State

Question : Is it possible to revise the model automatically such that it

satisfies the failed property while preserving the other properties?

Approach: Verification tends to use approaches that are fixed based on the notion

of pre-existing code and logical structures. In order to adapt to unanticipatedconditions it is necessary to be able to revise models if conditions change.

Payoff: In dynamic heterogeneous systems, it is necessary to update the

verification of the system as it evolves

Adaptive Verification Adaptive Verification

Space


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Feedback in Software ArchitectureGrolku, Smolka, Stony Brook, Havelund, JPL

Approach: Many software systems are introduced into environments thathave uncertain conditions that result in unforeseen failures. How can

software systems be augmented to adapt to failures

Payoff: Systems such as those on networks or those subject to uncertain

physical environments can adapt to conditions.

Robust Architecture with Feedback Adaptive Software Feedback

Performance


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Composable Software ServicesEdmund Durfee, UMichigan

Approach: Reliability and latency in software is difficult to compute in the

context of online management of real time software. Use composablesoftware design and optimization in scheduling to get the best reliability

and latency tradeoff.

Payoff: Allow time critical mission functions to be guaranteed under

dynamic heterogeneous constraints

Modular Composable Scheduling

Architecture

Resulting Latency vs.

Robust Performance Tradeoff


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Runtime RepairS. Khurshid, UT Austin

Approach: A functional approach can be developed for real time softwareruntime repair using new paradigms for online verification

Payoff: Faults in software can be corrected in real time and tracked rigorously

Real Time Runtime

Software Repair ArchitectureResults in Corrections of

Multiple Faults

Mi i V ifi i


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Mission VerificationElbaum, Dwyer U. Neb., Rosenblum, U. Col. London

Mission

Planning

Mission

Simulation

Mission

Deployment

Mission

ready

Program Analysis

Mission

Analysis

Approach: Develop a language to represent mission scenarios tied to

integrated distributed software architecture.

Payoff: Verify global mission properties as function of lower level

software constructs for quantifiable fault tolerance in achieving mission

objectives

ABCD

ABCD

ABD

ABD

AB

Mission AnalysisLanguage Architecture

Fault Tolerant

Mission Design


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SPRUCEDrager/RI

Approach: Use parallel processing resources and network infrastructure asmeans of emulating and detecting system faults in new software deployment

Payoff: Deployment of new software tools has far fewer defects and more

detailed assessment of integrated system performance


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VerificationHoman/RB

EnhancedAnalysis forVerification

Run-TimeArchitecture

Shift in VerificationParadigm

Shift in AssuranceParadigm

Reqmts

Design

Development

Test

V&V

Analysis

Analysis Analysis

Payoffs:

* Catch errors earlier

* Less costly analysis

* Improved coverage

* Run time techenforces safeoperating limits

Cost & Schedule

Confidence & Assurance

SystemsEngineering V

Approach: Global systems analysis must have a principled strategy forverification. Verification architectures must integrate with measurement.

Payoff: Less time will be spent debugging mission performance or forensically

discovering why failures occurred after mission deployment


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Increased Scale/Integration via DSMLs Anchored in DEVS

(Douglass, 711th HPW/RH)

Navigator

Plans routes

from targets to

targets under

constraints

DEVS (discrete event

system specification) Formal rigor

Model reusability

Interoperability

S t d S ft


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Systems and SoftwareAFRL Tech Directorate Interest/Coordination

Information Directorate Systems and Software Producibility

Multi-core Computing

Air Vehicles

Flight-critical systems and software

Mixed-criticality architectures

Human Effectiveness

Modeling of human-machine systems

Meta-information portrayal STTR

Robust Decision Making STT Large Scale Cognitive Modeling/C2WT


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Transitions

Sztipanovits (Vanderbilt)

AFRL/RI using C2 Wind Tunnel to build composable environmentswithin which to design and conduct capability-based integrated C2experiments

Tinelli/Barrett (Iowa/NYU)

Rockwell-Collins interested in transitioning SMT-based verifierresearch into formal methods toolkits for avionics systems

Smolka/Havelund (Stony Brook/JPL)

JPL Mars Science Laboratoryusing rule-based specificationlanguage to ensure correct execution of software on next MarsRover

Durfee (Univ of Michigan)

Collaboration on SBIR with Intelligent Automation Inc., applyinghybrid scheduling techniques to large-scale human expert teamingproblems involving dozens of teams, hundreds of experts, andthousands of constraints.

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