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    sam-pattern

    1.5.10 • Public • Published

    A Temporal Programming library

    Traditional programming models (OOP, FP, RP, FRP...) offer few temporal logic constructs, if any. Yet, we wrestle with implementing temporal aspects in many parts of our code, not just on the client but also on the server.

    This library is an implementation of the SAM pattern, a software engineering pattern based on the semantics of TLA+ (the Temporal Logic of Actions). SAM (State-Action-Model) offers a systematic approach to managing and reasoning about the application state from a temporal perspective. SAM's founding principle is that State Mutation must be a first class citizen of the programming model and as such mutations must occur in a well defined synchronized step. SAM defines a step as:

         _______________________... event ..._________________________
        |                                                             |
        |        ___________Model___________                          |
        v       |       (synchronized)      |                         |
      Action -> | Acceptor(s) -> Reactor(s) | -> Next-Action and|or Render 
        ^       |___________________________|        |              State
        |                                            |        
        |____________________________________________|        
    
    

    An action is initiated by the SAM client/consumer of the state representation. An action computes a proposal to mutate the application state. The proposal is presented to the model which accepts, partially accepts or rejects the proposal (acceptors are units of mutation and functions of proposals). Once the application state has mutated, the reactors compute the resulting application state. Reactors are invariant mutations, i.e. functions of the state that are independent of proposals. The factoring of your code as actions, acceptors and reactors leads to cleaner, more compact and easy to maintain code.

    SAM is generally implemented as a singleton and a single state tree, but that's not a requirement. SAM instances can work cooperatively, especially in a parent/child relationship (to manage a specific but ephemeral aspect of your application, e.g. a form or a wizard).

    The library supports a simple component model to modularize the application logic. Components implement any combination of actions, acceptors and reactors and can either operate of their local state or the instance state tree.

    Actions are converted into intents at setup time. Intents are invoked by the client/consumer in response to events. SAM supports asynchronous actions readily. Intents have magic powers such as automatic retries, ordering or debouncing. Intents can be gated and only applied to the model when allowed (see allowedActions below)

    SAM's structure is so precise that the library comes with a model checker that is capable of checking the correctness of your code by exploring all possible combinations of intents and values and validate that liveness conditions will be reached and that, on the other hand, no safety condition will be triggered.

    The sam-fsm library is an add-on that allows you to simplify the definition of finite state machines. One or more FSMs can run in the same SAM instance and FSMs cohexist with standard SAM actions, acceptors and reactors.

    The sam-pattern library is implemented following SAM's own principles.

    The pattern was first introduced in June 2015 as STAR and then in it's final form in February 2016.

    Code Samples

    TODOMVC

    RealWorld

    • uce (via @imnutz)

    Rocket Launcher

    Please check the unit tests for specific use cases.

    Table of Contents

    Installation

    Node.js

    The library is available on npm. To install it, type:

    $ npm install --save sam-pattern
    const { api, createInstance } = require('sam-pattern')
    
    // API to the global SAM instance
    const {
      addInitialState, addComponent, setRender
    } = api()
    
    // Create a new SAM instance
    const child = api(createInstance())

    Browsers

    You can also use it within the browser; install via npm and use the ./dist/SAM.js file. For example:

    <script src="./node_modules/sam-pattern/dist/SAM.js"></script>
    
    // or
    
    <script src="https://unpkg.com/sam-pattern"></script>

    The library's name is tp (as in temporal programming)

    // API to the global SAM instance
    const { SAM } = tp

    Getting started

    SAM requires an initial state, one or more components and a render method that will be called after each step.

    import { addInitialState, addComponent, setRender } from 'sam-pattern'
    
    addInitialState({
      counter: 0
    })
    
    const { intents } = addComponent({ 
      actions: [
        () => ({ incBy: 1 }),
        ['LABELED_ACTION', () => ({ incBy: 2})]
      ],
      acceptors: [
        model => proposal => model.counter += proposal.incBy || 1
      ]
    })
    
    setRender((state) => console.log(state.counter))
    
    const [inc, incBy2] = intents
    
    // Apply actions
    inc() 
    incBy2()

    You can also take a look at this sample in CodePen.io: Rocket Launcher

    Library

    Constructors

    • SAM : global SAM instance
    • createInstance : creates a SAM instance
    • api : api(samInstance) will return the actions that control samInstance. When no instance is provided, it returns the global instance actions.

    API to the Global SAM instance

    • addInitialState : adds to the model's initial state (or simply state when called at a later time)

    • addComponent : adds one of many components (Actions, Acceptors, Reactors). Returns intents from actions

    • addAcceptors : adds a list of acceptors to the SAM instance (acceptors are executed in the order in which they are defined)

    • addReactors : adds a list of reactors to the SAM instance

    • addNAPs : adds a list of next-action-predicates to the SAM instance. When a predicate returns true, the rendering is suspended until the next-action is completed

    • getIntents : returns a list of intents, given a list of actions. Intents wrap actions with the call to the present method

    • setRender : sets the render method

    • addHandler : adds an event handler to the SAM loop (for instance, as an alternative to render)

    • allowedActions : gets the allowed actions for the next step. Actions fail silently when not allowed

    • addAllowedActions : adds an action to the allowedActions array

    • allow : adds an array of actions to the allowedActions array

    • clearAllowedActions: clears all allowed actions

    • step : a simple action that executes a SAM step without changing the application state

    • doNotRender : a nap that allows to you to prevent rendering the current state (for one step)

    A component specification includes options:

    • ignoreOutdatedProposals when true, the model's will reject all action proposals that out of order. In the event that a proposal comes after another more recent one was processed, it will be rejected. Note: this option is only available for asynchronous actions.
    • debounce when providing a value greater than 0, all intents of the corresponding component will be debounced by that amount in ms. Note: this option is only available for asynchronous actions.
    • retry { delay, max } when specified, it will retry invoking an intent in case of an unhandled exception up to max times and after delay ms

    Note: actions can be labeled using an array of two elements, the first element being the action label:

    const actions = [
        () => ({ incBy: 1 }),
        ['LABELED_ACTION', () => ({ incBy: 2})]
      ]

    Labels can be used in specifying the allowed actions in a given state. Please see the sam-fsm library for some examples.

    Time Travel

    SAM's implementation is capable of time traveling (return to a prior state of the model)

    • addTimetraveler : adds a time traveler instance. The method takes an optional array of snapshots which allows you to initialize the SAM instance's history
    • travel : returns to the nth snapshot of the model's history
    • hasNext : returns true you have have reached the end of time
    • next : returns the next snapshot of the model
    • last : returns the last snapshot of history

    Model Checker

    The library includes a model checker capable of computing the behavior leading to a liveness or safety conditon (see example below). The checker method arguments are:

    • instance : The SAM instance used for checking
    • intents : Model checker intents - intent: the SAM intent, name: its name, values: an array of all possible permutations for the intent arguments }
    • reset : A function that is called after each iteration to return the model to the proper state,
    • liveness : a function that takes the application state as an input and returns a liveness condition (exected condition to be reached by some behavior)
    • safety : a function that takes the application state as an input and returns a safety condition (unexpected occurence of a state)
    • options : checker options that restrict the search space - depthMax: how many steps in a behavior, noDuplicateAction: whether the model supports duplicate actions (in general it's true) , doNotStartWith: an array of intent names that should not be used to start a behavior, clone: when true, renders a shallow copy of the model
    • success : a callback for every liveness condition detected
    • err : a callback for every safety condition detected

    Utils

    • first : returns the first element of its argument (array)
    • match : Given an array of booleans and an array object, it returns the first object which corresponding boolean value is true
    • on : a helper function which takes an object o and a function f as arguments and calls f(o) if the object exists. on calls can be chained. This function is used to chain a series of acceptors
    • oneOf : same as on but will stop after the first value that is found to exist

    Exception Handling

    SAM handles all uncaught action, acceptor, reactor and nap exceptions. The application model and state representation expose four methods to check for exceptions:

    • hasError
    • error
    • errorMessage
    • clearError

    When a component has been defined with the options: { retry: { max: 3, delay: 100}} all its actions will be retried up to 3 times every 100ms.

    render: (state) => {
      if (state.hasError()) {
        console.log(state.errorMessage())
        state.clearError()
      } 
    }

    Code samples

    Synchronized mutation

    In its pure form, the SAM pattern does not support asynchronous acceptors, all model mutations must be synchronous. If you wanted to call a downstream API to create, update or delete some entity that would technically be incorrect. The way to do it would be to use a next-action-predicate (NAP) that will make the call and present the results back to the model.

    That can be a little bit of a boiler plate, especially if your UX is expected to be synchronous. Very often users are willing to wait for an API call to complete before they want to do something else.

    SAM allows you to synchronize the present method and queue all other action proposals in the mean time. There is an option to create a SAM instance that will be synchronized:

    let SyncSAM = createInstance({ instanceName: 'sync\'ed', synchronize: true })
    
    // You may at some point need to clear the internal queue used for proposals
    SyncSAM({ clearInterval: true })

    Safety Conditions

    Temporal programming (and TLA+) supports invariants which can be checked after each step as Safety conditions (an invalid state). When a Safety Condition is detected, SAM will roll back the application state to the latest valid snapshot of the model (if history is turned on) and notify the client of the corresponding exception.

    // Create a local SAM instance (different from the Global one)
    const SafeSAM = createInstance()
    const { intents } = SafeSAM({
        // set initial state
        initialState: {
            counter: 10,
            status: 'ready'
        },
        // use time timetravel to enable rollback
        history: [],
        component: {
            // Standard counter component
            actions: [
                () => ({ incBy: 1 })
            ],
            acceptors: [
                model => ({ incBy }) => {
                    if (incBy) {
                        model.counter += incBy
                    }
                }
            ],
            reactors: [
                model => () => {
                    if (model.counter > 10) {
                        model.status = 'error'
                    }
                }
            ],
            // Safety condition, when true, will roll back to the
            // latest safe version of the application state
            safety: [
            {
                expression: model => model.counter > 10,
                name: 'Counter value is dangerously high'
            }
            ]
        },
        logger: {
            error: (err) => {
                console.log(err.name) // -> Counter value is dangerously high
            }
        },
        render: (state) => {
            // the model should have rolled back
            console.log(state.counter) // -> 10
        }
    })
    
    const [inc] = intents
    
    // Increment counter from 10 to 11
    // to trigger the safety condition
    inc()

    Asynchronous actions

    SAM supports and welcomes the use of asynchronous actions. It can also operate in a mode where it ignores outdated proposals (proposals that come out of order, when compared to the intent's invocation). This is useful to implement the "cancellations" of long running asynchronous requests. A cancel is equivalent to a synchronous action invoked to simply advance the step counter and ignore the initial request's proposal when it comes.

    const { intents } = SAM({
        initialState: {
            counter: 10,
            status: 'ready'
        },
        component: {
            actions: [
                () => new Promise(r => setTimeout(r, 1000)).then(() => ({ test: true }))
                () => ({ incBy: 1 })
                () => setTimeout(() => ({ incBy: 1 }), 500)
            ],
            acceptors: [
              model => ({ test }) => {
                  if (test) {
                      model.status = 'testing'
                  }
              },
              model => ({ incBy }) => {
                if (incBy) {
                    model.counter += incBy
                }
              }
            ],
            options: {
              ignoreOutdatedProposals: true
            }
        },
        render: (state) => {
            console.log(state.status)
            console.log(state.counter)
        }
    })
    
    const [test, inc, incLater] = intents
    incLater()  // this action is ignored, proposal is outdated
    inc()       // -> 11, this action cancels the effects of the previous action
    test()      // -> testing, 11

    Components with Local State

    A named component operates on its local state (which can be initialized via the localState property). The component's acceptors and reactors can access the state tree of the SAM instance via the parent property.

    const [tick] = SAM({
        initialState: {
              counter: 10,
              status: 'ready',
              color: 'blue'
        },
        component: {
            name: 'local',
            localState: {
                color: 'blue'
            },
            actions: [
              () => ({ test: true })
            ],
            acceptors: [
                localState => ({ test }) => {
                    if (test) {
                        localState.color = 'purple'
                    }
                }
            ]
        },
        render: (state) => {
            console.log(state.status)                               // -> ready
            console.log(state.localState('local').color)            // -> purple
            console.log(state.color)                                // -> blue
            console.log(state.localState('local').parent.color)     // -> purple
            
        }
    }).intents
    
    tick()    

    Time Traveler

    // Add a time traveler to the global SAM instance 
    // with no prior history
    addTimeTraveler([])
    
    addInitialState({
        counter: 0
    })
    
    const { intents } = addComponent({
        actions: [() => ({ incBy: 1 })],
        acceptors: [
            model => (proposal) => {
                model.counter += proposal.incBy || 1
            }
        ]
    })
    
    setRender(state => console.log(state.counter))
    
    const [inc] = intents
    
    inc()       // --> 1
    inc()       // --> 2
    inc()       // --> 3
    
    // Reset the model to its
    // original state
    travel(0)   // --> 0
    next()      // --> 1
    if (hasNext()) {
        next()  // --> 2
    }
    last()      // --> 3

    Debounce

      const { intents } = SAMDebouceTest({
        initialState: {
          counter: 0
        },
    
        component: {
          actions: [
            () => ({ incBy: 1, debounceTest: true })
          ],
          acceptors: [
            model => (proposal) => {
              model.counter += proposal.incBy || 1
            }
          ],
          // Debounce for 100ms
          options: { debounce: 100 }
        },
    
        render: state => console.log(state.counter) // -> 1
      })
    
      const [inc] = intents
    
      // Simulate a series of events trying 
      // to increment the counter
      setTimeout(inc, 0)
      setTimeout(inc, 10)
      setTimeout(inc, 20)
      setTimeout(inc, 30)

    Model Checker

    The library a model checker capable of detecting liveness and safety conditions. For instance, this is an implementation of Dr. Lamport's Die Hard example:

    // This code is implementing the dieharder TLA+ specification
    // https://github.com/tlaplus/Examples/blob/master/specifications/DieHard/DieHarder.pdf
    
    /* eslint-disable no-unused-expressions */
    /* eslint-disable no-undef */
    
    const { api, createInstance } = require('sam-pattern')
    
    const { utils: { E, or } } = require('sam-pattern')
    
    const { checker } = require('sam-pattern')
    
    const dieHarder = createInstance({ hasAsyncActions: false, instanceName: 'dieharder' })
    
    const {
      addInitialState, addComponent, setRender
    } = api(dieHarder)
    
    let checkerIntents = []
    
    addInitialState({
      n: 2,
      jugs: [0, 0],
      capacity: [3, 5],
      goal: 4
    })
    
    const { intents } = addComponent({
      actions: [
        (j1, j2) => ({
          jug2jug: { j1, j2 }, __name: 'jug2jug'
        }),
        j => ({ empty: j, __name: 'empty' }),
        j => ({ fill: j, __name: 'fill' })
      ],
      acceptors: [
        state => ({ fill }) => {
          if (E(fill) && fill < state.n && fill >= 0) {
            state.jugs[fill] = state.capacity[fill]
          }
        },
        state => ({ empty }) => {
          if (E(empty) && empty < state.n && empty >= 0) {
            state.jugs[empty] = 0
          }
        },
        state => ({ jug2jug }) => {
          if (E(jug2jug)) {
            const { j1, j2 } = jug2jug
            if (j1 !== j2) {
              if (E(j1) && j1 < state.n && j1 >= 0
                        && E(j2) && j2 < state.n && j2 >= 0) {
                const maxAllowed = state.capacity[j2] - state.jugs[j2]
                const transfer = Math.min(maxAllowed, state.jugs[j1])
                state.jugs[j1] -= transfer
                state.jugs[j2] += transfer
              }
            }
          }
        }
      ]
    })
    
    setRender((state) => {
      const { goal, jugs = [] } = state
      const goalReached = jugs.map(content => content === goal).reduce(or, false)
      console.log(`Goal: ${goal} [${jugs.map(content => content).join(', ')}]`)
      console.log( goalReached ? 'Goal reached!!!' : '')
    })
    
    const [
      jug2jug,
      empty,
      fill
    ] = intents
    
    // fill(1)
    // jug2jug(1, 0)
    // empty(0)
    // jug2jug(1, 0)
    // fill(1)
    // jug2jug(1, 0)
    
    checkerIntents = [{
      intent: fill,
      name: 'fill',
      values: [
        [0],
        [1]
      ]
    }, {
      intent: empty,
      name: 'empty',
      values: [
        [0],
        [1]
      ]
    }, {
      intent: jug2jug,
      name: 'jug2jug',
      values: [
        [0, 1],
        [1, 0]
      ]
    }
    ]
    
    checker({
      instance: dieHarder,
      intents: checkerIntents,
      reset: () => {
        empty(0)
        empty(1)
      },
      liveness: ({ goal, jugs = [] }) => jugs.map(content => content === goal).reduce(or, false),
      safety: ({ jugs = [], capacity = [] }) => jugs.map((content, index) => content > capacity[index]).reduce(or, false),
      options: {
        depthMax: 6,
        noDuplicateAction: true,
        doNotStartWith: ['empty', 'jug2jug'],
        format: (actionName, proposal, model) => {
            const act = `${actionName}(${JSON.stringify(proposal.fill || proposal.jug2jug || proposal.empty || 0)})`
            return `${act.padEnd(30, ' ')}==> ${JSON.stringify(model.jugs)} (goal: ${model.goal})`
        }
      }
    }, (behavior) => {
      console.log(`\nthe model checker found this behavior to reach the liveness condition:\n${behavior.join('\n')}\n`)
    }, (err) => {
      console.log('The model checker detected a safety condition: ', err)
    })
    
    // Expected output
    // The model checker found this behavior to reach the liveness condition:
    // fill(1)                       ==> [0,5] (goal: 4)
    // jug2jug({"j1":1,"j2":0})      ==> [3,2] (goal: 4)
    // empty(0)                      ==> [0,2] (goal: 4)
    // jug2jug({"j1":1,"j2":0})      ==> [2,0] (goal: 4)
    // fill(1)                       ==> [2,5] (goal: 4)
    // jug2jug({"j1":1,"j2":0})      ==> [3,4] (goal: 4)
    
    
    // The model checker found this behavior to reach the liveness condition:
    // fill(1)                       ==> [0,5] (goal: 4)
    // jug2jug({"j1":1,"j2":0})      ==> [3,2] (goal: 4)
    // empty(0)                      ==> [0,2] (goal: 4)
    // jug2jug({"j1":1,"j2":0})      ==> [2,0] (goal: 4)
    // fill(1)                       ==> [2,5] (goal: 4)
    // jug2jug({"j1":1,"j2":0})      ==> [3,4] (goal: 4)
    // empty(0)                      ==> [0,4] (goal: 4)

    Support

    Please post your questions/comments on the SAM-pattern forum

    Change Log

    • 1.5.10 Adds action parameter stateMachineId to support composite state machines (sam-fsm)
    • 1.5.9 Adds disallowedActions to support composite state machines (sam-fsm)
    • 1.5.8 Adds an optional action label which can be used to specify allowed actions
    • 1.5.5 Fixes a defect associated to sam-fsm guarded transitions
    • 1.5.2 Minifies the lib (10kB)
    • 1.5.1 Augments the allowedActions implementation to use action labels to identify allowed actions
    • 1.4.9 Adds reference to the sam-fsm library
    • 1.4.6 Adds access to the state representation as an alternative rendering mechanism
    • 1.4.4 Adds event handlers as an alternative rendering mechanism
    • 1.4.3 Adds links to TODOMVC code samples
    • 1.4.1 Changes setRender to accept only one function (or two)
    • 1.4.0 Adds an option to run the model in synchronized mode
    • 1.3.10 Adds the ability to skip rendering if necessary
    • 1.3.9 Adds allowed actions
    • 1.3.7 Adds exception handling
    • 1.3.6 Adds a debounce mode
    • 1.3.5 Adds a new component option to skip processing outdated proposals

    Copyright and license

    Code and documentation copyright 2019 Jean-Jacques Dubray. Code released under the ISC license. Docs released under Creative Commons.

    Install

    npm i sam-pattern

    DownloadsWeekly Downloads

    199

    Version

    1.5.10

    License

    ISC

    Unpacked Size

    66.7 kB

    Total Files

    12

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