IOA: Distributed Algorithms ? Distributed Programs

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IOA Distributed Algorithms ? Distributed
Programs

• Nancy Lynch
• PODC 2000
• Collaborators
• Steve Garland, Josh Tauber,
• Anna Chefter, Antonio Ramirez,
• Michael Tsai, Mandana Vaziri, Tina Nolte

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What we want to do

• See how abstract I/O automaton models of
  distributed algorithms and services could be used
  in producing and maintaining actual distributed
  programs.

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Why use models in programming?

• Models let you
• Build complex things and get them right
• Change things and understand the consequences
• Explain clearly how things work
• Other engineering disciplines use them

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But why I/O automaton models?

• Simple mathematical basis for describing
  structure behavior of systems of interacting
  components
• Already used for
• Distributed algorithms, impossibility results
• System case studies
• Group communication services
  (Orca, Transis,
  Ensemble,)
• Communication protocols
• (TCP, T/TCP,)
• Hybrid (continuous/discrete) systems (TCAS,)

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I/O automataLynch, Tuttle 87

• Nondeterministic state machines
• Infinite state
• Input/output/internal actions
• Transitions, executions, traces
• Supports modularity
• Composition
• Levels of abstraction
• Mathematical model, language-independent

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How I/O automata are used

• Model service specs, distributed algorithms
• Refine, from high level global service spec
• to detailed distributed algorithm
• Make models as nondeterministic as possible
  
  
• Prove correctness, using invariants,
  simulation relations, composition

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TO Broadcast Service Spec Fekete, Lynch,
Shvartsman, PODC 97

• Signature
• input broadcast(a,p)
• output receive(a,p,q)
• internal order(a,p)
• State
• queue, sequence of (a,p), initially empty
• for each p
• pendingp, sequence of a, initially
  empty
• nextp, positive integer, initially 1

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TO Broadcast

• Transitions
• broadcast(a,p)
• Effect
• append a to pendingp
• order(a,p)
• Precondition
• a is head of pendingp
• Effect
• remove head of pendingp
• append (a,p) to queue

• receive(a,p,q)
• Precondition
• queuenextq (a,p)
• Effect
• nextq nextq 1

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IOA LanguageGarland, Lynch 97

• Programming/specification language for defining
  I/O automata
• Similar to pseudocode
• Explicitly describes
• Signature, structured state, precondition/effects
• Nondeterministic choice, composition, invariants,
  levels of abstraction
• Declarative imperative

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IOA Tools

• Front end Parser, static checker, intermediate
  Java representation Garland, Ramirez
• Support for
• Composing models
• Chefter 98 Garland, Lynch
• Refining models, from global specification
• to low-level distributed algorithm model
  
• Step correspondence Ramirez 00

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IOA Tools

• Prototype code generator, for generating
  distributed code from low-level distributed
  algorithm models Tauber, Tsai
• Validation tools
• Simulator Chefter 98 Ramirez 00
• Paired simulation
• Theorem-prover interfaces
• PVS Devillers, Isabelle? LP? NuPRL?
  Nolte
• Automatic?

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Modeling Projects

• Distributed spanning tree algorithms
• Luhrs, Nolte
• Distributed replicated data management
  algorithms
• Lamport state machines Attiya, Bar-Noy, Dolev,
  
• Dean, Karlovich, Rosen
• Future
• Practical communication protocols, services
• Interacting Java objects

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TLA and IOA

• TLA and IOA both
• Use precondition/effect style
• Support nondeterministic choice
• Support similar kinds of assertional proofs
• TLA
• Is typeless
• Is declarative
• Has good automatic tools
• IOA
• Uses Larch Shared Language data types
• Declarative imperative
• Emphasizes system decomposition