sam-pattern
v1.5.10
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SAM Pattern library
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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
- vanilla.js with
sam-fsm
library
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 instancecreateInstance
: creates a SAM instanceapi
:api(samInstance)
will return the actions that controlsamInstance
. 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 actionsaddAcceptors
: 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 instanceaddNAPs
: adds a list of next-action-predicates to the SAM instance. When a predicate returnstrue
, the rendering is suspended until the next-action is completedgetIntents
: returns a list of intents, given a list of actions. Intents wrap actions with the call to the present methodsetRender
: sets the render methodaddHandler
: 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 allowedaddAllowedActions
: adds an action to the allowedActions arrayallow
: adds an array of actions to the allowedActions arrayclearAllowedActions
: clears all allowed actionsstep
: a simple action that executes a SAM step without changing the application statedoNotRender
: 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 tomax
times and afterdelay
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 historytravel
: returns to the nth snapshot of the model's historyhasNext
: returns true you have have reached the end of timenext
: returns the next snapshot of the modellast
: 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 checkingintents
: 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 modelsuccess
: a callback for every liveness condition detectederr
: 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 trueon
: a helper function which takes an objecto
and a functionf
as arguments and callsf(o)
if the object exists.on
calls can be chained. This function is used to chain a series of acceptorsoneOf
: same ason
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 100
ms.
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.