Crisis Management

Crisis Management William L. Scherlisscherlis@cs.cmu.edu Carnegie Mellon University School of Computer Science

Crisis Management • An Application Case Study • What is Crisis Management • Crisis Management technologies • Crisis Management challenges for software technology research 1. “Software Swat” 2. Composition on demand 3. Managing rapid change 4. Code-ification 5. Quality: analysis, assurance, validation 6. Human interface NSF Software Workshop

Context Dimensions Distinct phases of activity Planning Preparedness/Mitigation Response Recovery Broad spectrum of players FEMA State, Local NGOs Business Citizens Diversity of artifacts Data inputs Databases Reports and documents Applications Communications channels Dimensions of Challenge Interdependent organizations Federal/state/local, NGOs, utilities, private sector supplies, etc. Thousands of organizations potentially involved Wide variation in access to IT resources Organizational structure variesby phase C2 during response Situation awareness Decision support Federation during planning Interoperation and metadata Transactional during recovery People under stress Human-systems interaction Dimensions of Crisis Management (CM) NSF Software Workshop

Examples Reliable communications Information integration Multi-source data analysis Variable quality Geographical info Modeling and simulation “Instant bureaucracy” Situation awareness Collaboration E-Commerce Supply chain creation Inventory management “Forward deployment” Business transactions Pre-certification Citizen single point-of-access Information Transactions Authentication and trust Citizens, responders, suppliers, organizations Reconfigurable authorization Information escrow CM Technologies NSF Software Workshop

1. Software Swat TeamsKey Software Research Issues • Elements of a “Software Swat” capability • Rapid assembly of reliable teams, components, and tools • The aggressive iterative process: • Requirements elicitation and analysis • Baseline technologies modeling • Contextual system design • Patterns of integration • Adaptation and assembly • Analysis, testing, and assurance • Early deployment • Continuous improvement and re-release • No new bugs • Rapid response to unanticipated needs • Rest on principles of predictability of evolvable processes • Predictable outcomes • Adjustment of features, quality, performance NSF Software Workshop

2. Composition on demand Key Software Research Issues • Composition: rapid system assembly and adaptation • Rapid integration of subsystems/components • Overcome diverse kinds of incompatibilities with Software Architecture • Use component attributes to enable predictable integration • Seek compositionality: Predict properties of systems from properties of components. • Without compositionality, the entire system must be retested • Analyze/assure component properties just once. • Rapid information integration • Reconcile/adapt similar data models • Program understanding to capture/express data design • Provide information assurance despite rapid assembly • Emply diverse techniques to adapt components for “safe” use • Sandbox, wrap, transform, etc. NSF Software Workshop

3. Managing Rapid ChangeKey Software Research Issues • Composition: rapid system assembly and adaptation • Enable geographically dispersed teams to collaborate • Example: Oklahoma City rapid software integration • Information sharing (and access control) • Information awareness • Coordination of effort (i.e., concurrency control) • Rapid adaptation of components and assemblies • With predictable results: • Use analyses to predict the effects of change • Use specifications to avoid full re-analysis and testing • Use manipulations to facilitate functional change • Continuous improvement • Rapid early deployment • Iterate and update while in use • (Also important for operational e-commerce sites) • Improvements in components, integration, user interface, etc. • Assimilate new releases from component suppliers NSF Software Workshop

4. Quality: Analysis, Assurance, ValidationKey Software Research Issues • Quality: Getting the important things right • Managing security-vs-responsiveness • Now: High security usually means highly constrained functionality • Validation of integration • Metadata about quality, sourcing, etc. • Trace conclusions/results to sources and retain audit trail • Compositionality • The “good-enough” test • Units, Order-of -magnitude, Reasonableness • Models and simulations • Develop explicit domain models to frame specifications and assurance • Exploit code-ified domain models • Crisis management exercises • The usual mode of operation for crisis responders • Include the IT dimension • Augmented reality • Modeling  Reality NSF Software Workshop

5. Creating the DisciplineKey Software Research Issues • Code-ification of new domains • Capture using domain-specific language and domain-specific tools • Example domains • FEMA business rules • Information policy: privacy, access • Response processes • Situation awareness • Analysis • Consequences of access changes • Business rule interactions NSF Software Workshop

6. Crisis Management User InterfacesKey Software Research Issues • Human interface • Rapid creation of new human interfaces • Responders • Citizens • Business • Collaboration • CM teams • Software engineering teams • Communities • Citizens • Under stress • Diverse information and transaction needs • Responders • Under stress • Diverse information and transaction needs NSF Software Workshop

Crisis Management • An Application Case Study • What is Crisis Management • Crisis Management technologies • Crisis Management challenges for software technology research 1. “Software Swat” 2. Composition on demand 3. Managing rapid change 4. Code-ification 5. Quality: Analysis, assurance, validation 6. Human interface • Success in Crisis Management depends increasingly on a solid foundation of software technologies NSF Software Workshop

Crisis Management