BoolTable

BoolTable is an expressive and functional alternative for complex and incongruous conditional structures in Javascript. It allows one to build logical branches not unlike truth tables and decision tables.

With BoolTable you can write more reliable, consistent, expressive, observable, and testable condition branching.

Install

npm i booltable

Summary of BoolTable APIs

booltable exposes three APIs: Truth, Decision, and BoolTable.

`Truth`

This API is akin to a truth table row, which allows one to specify any number of statements that may be true or false, and apply a boolean operator to the collection to achieve a result.

For example:

a table row of three items: [true, true, true] would return true for an AND operator, false for a NOR operator, etc;
a table row with [true, false] would return false for AND, and true for XOR, true for OR, etc

`Decision`

This API is akin to a decision table, which allows one to specify an action when certain conditions evaluate as true. One can use Truth in concert to allow for complex and specific decisions.

This can be used to indicate a list of actions that are triggered upon a complex set of conditions.

`BoolTable`

This API allows one to construct a more expressive conditions in the Decision table, for better logging and observability, and to avoid the necessity of adding comments explaining each complex evaluation.

This allows for more meaningful use of Decision, especially when used with a complex set of conditions.

Bringing them together

Each of these are designed to be used together to avoid deeply nested if/else/switch/etc statements.

Example: Thermostat

A simple example to start with that most people can relate to is how a thermostat works.

Let's first take a sneak peak of what our final code will be, to give a sample of the expressivity BoolTable can add:

const thermostat = table =>
    Decision.of([
        [table.q(`It's getting too cold in here`), turnOnFurnace],
        [table.q(`It's warm enough now`), turnOffFurnace],
        [table.q(`It's getting too hot in here`), turnOnAirConditioning],
        [table.q(`It's cool enough now`), turnOffAirConditioning],
        [true, nothingHappening]
    ]);

Premise

If a thermostat is set to "heat", it will turn on a furnace when below the threshold temperature. It will turn off when the temperature goes above the threshold, plus one.

If a thermostat is set to "cool", it will turn on air conditioning when below a threshold temperature. It will turn off when the temperature goes below the threshold, minus one.

Let's visualize first in an actual decision table:

mode	status	temperature	action to take
set to "heat"	currently off	thermometer is below threshold	turn the furnace on
set to "heat"	currently on	thermometer is above threshold + 1	turn the furnace off
set to "cool"	currently off	thermometer is above threshold	turn the air conditioning on
set to "cool"	currently on	thermometer is below threshold - 1	turn the air conditioning off

First pass: basic, unoptimized `Decision` example

const turnOnFurnace = () => console.log('Turning on the furnace');
const turnOffFurnace = () => console.log('Turning off the furnace');
const turnOnAirConditioning = () =>
    console.log('Turning on the air conditioning');
const turnOffAirConditioning = () =>
    console.log('Turning off the air conditioning');
const nothingHappening = () => console.log('Nothing happening');

const thermostat = conditions =>
    Decision.of([
        [
            conditions.mode === 'heat' &&
                conditions.operating === 0 &&
                conditions.thermometer < conditions.thresholdTemp,
            turnOnFurnace
        ],
        [
            conditions.mode === 'heat' &&
                conditions.operating === 1 &&
                conditions.thermometer > conditions.thresholdTemp + 1,
            turnOffFurnace
        ],
        [
            conditions.mode === 'cool' &&
                conditions.operating === 0 &&
                conditions.thermometer > conditions.thresholdTemp,
            turnOnAirConditioning
        ],
        [
            conditions.mode === 'cool' &&
                conditions.operating === 1 &&
                conditions.thermometer < conditions.thresholdtemp - 1,
            turnOffAirConditioning
        ],
        // a default response if no action is necessary
        [true, nothingHappening]
    ]);

// example conditions, this will turn off the furnace:

// get our action function
const actionFn = thermostat({
    mode: 'heat',
    operating: 1,
    thermometer: 21,
    thresholdTemp: 19
})
    .run()
    .join();

// console:
// > Turning off the furnace
actionFn();

Second pass: add hardening

While this works, the boolean statements make this code more fragile than it needs to be. Let's group our conditions with Truth.

const thermostat2 = conditions =>
    Decision.of([
        [
            Truth.of([
                conditions.mode === 'heat',
                conditions.operating === 0,
                conditions.thermometer < conditions.thresholdTemp
            ]).and(),
            turnOnFurnace
        ],
        [
            Truth.of([
                conditions.mode === 'heat',
                conditions.operating === 1,
                conditions.thermometer > conditions.thresholdTemp + 1
            ]).and(),
            turnOffFurnace
        ],
        [
            Truth.of([
                conditions.mode === 'cool',
                conditions.operating === 0,
                conditions.thermometer > conditions.thresholdTemp
            ]).and(),
            turnOnAirConditioning
        ],
        [
            Truth.of([
                conditions.mode === 'cool',
                conditions.operating === 1,
                conditions.thermometer < conditions.thresholdtemp - 1
            ]).and(),
            turnOffAirConditioning
        ],
        [true, nothingHappening]
    ]);

// get our action function
const actionFn2 = thermostat({
    mode: 'cool',
    operating: 0,
    thermometer: 24,
    thresholdTemp: 22
})
    .run()
    .join();

// console:
// > Turning on the air conditioning
actionFn2();

This is better as one does not need to follow a list of items followed by &&, but it is still a bit lengthy.

Let's make it more expressive, using Truth in a clearer way.

Third pass: optimizing readability with constant function expressions

const itIsGettingCold = conditions =>
    Truth.of([
        conditions.mode === 'heat',
        conditions.operating === 0,
        conditions.thermometer < conditions.thresholdTemp
    ]).and();

const itIsWarmEnough = conditions =>
    Truth.of([
        conditions.mode === 'heat',
        conditions.operating === 1,
        conditions.thermometer > conditions.thresholdTemp + 1
    ]).and();

const itIsGettingHot = conditions =>
    Truth.of([
        conditions.mode === 'cool',
        conditions.operating === 0,
        conditions.thermometer > conditions.thresholdTemp
    ]).and();

const itIsCoolEnough = conditions =>
    Truth.of([
        conditions.mode === 'cool',
        conditions.operating === 1,
        conditions.thermometer < conditions.thresholdtemp - 1
    ]).and();

const thermostat3 = conditions =>
    Decision.of([
        [itIsGettingCold(conditions), turnOnFurnace],
        [itIsWarmEnough(conditions), turnOffFurnace],
        [itIsGettingHot(conditions), turnOnAirConditioning],
        [itIsCoolEnough(conditions), turnOffAirConditioning],
        [true, nothingHappening]
    ]);

// get our action function
const actionFn3 = thermostat({
    mode: 'cool',
    operating: 0,
    thermometer: 22,
    thresholdTemp: 22
})
    .run()
    .join();

// console:
// > Nothing happening
actionFn3();

This is much more expressive, and readable for any developer who returns to the code in the future.

But what if we have a lot of options, and doing a camel-case const for every single option is beginning to look odd?

This is where BoolTable can help with adopting the expressivity of a unit test.

Final pass: optimizing expressivity with `BoolTable`

const bt = conditions =>
    BoolTable.of([
        [
            `It's getting too cold in here`,
            Truth.of([
                conditions.mode === 'heat',
                conditions.operating === 0,
                conditions.thermometer < conditions.thresholdTemp
            ]).and()
        ],
        [
            `It's warm enough now`,
            Truth.of([
                conditions.mode === 'heat',
                conditions.operating === 1,
                conditions.thermometer > conditions.thresholdTemp + 1
            ]).and()
        ],
        [
            `It's getting too hot in here`,
            Truth.of([
                conditions.mode === 'cool',
                conditions.operating === 0,
                conditions.thermometer > conditions.thresholdTemp
            ]).and()
        ],
        [
            `It's cool enough now`,
            Truth.of([
                conditions.mode === 'cool',
                conditions.operating === 1,
                conditions.thermometer < conditions.thresholdTemp - 1
            ]).and()
        ]
    ]);

const thermostat4 = table =>
    Decision.of([
        [table.q(`It's getting too cold in here`), turnOnFurnace],
        [table.q(`It's warm enough now`), turnOffFurnace],
        [table.q(`It's getting too hot in here`), turnOnAirConditioning],
        [table.q(`It's cool enough now`), turnOffAirConditioning],
        [true, nothingHappening]
    ]);

const condTable = bt({
    mode: 'cool',
    operating: 1,
    thermometer: 21,
    thresholdTemp: 23
});

// get our action function
const actionFn4 = thermostat4(condTable)
    .run()
    .join();

// console:
// > Turning off the air conditioning
actionFn4();

While this is slightly more code, it is more expressive and can reduce the need for comments in the code.

The APIs

If seeing something like Decision.of, Truth.of as an API looks unusual to you, that's ok! This is a oft-used pattern for functional libraries in Javascript, and the documentation here will attempt to cover anything you'll need to know.

`Truth`

Truth.of([ condition1, condition2, ...]);

Create a truth table. This allows you to collect multiple conditions and assess them with boolean logic.

Boolean expression methods

.and(), .or(), .xor(), .nor()

Running any of these methods will return a true or false value.

Truth.of([true, true]).and(); // === true : AND operation means all are true
Truth.of([false, false]).and(); // === false
Truth.of([true, false]).or(); // === true : OR operation means at least one is true
Truth.of([false, false, false]).or(); // === false
Truth.of([true, false, false]).xor(); // === true : XOR operation means at least one is true and at least one is false
Truth.of([true, true, true]).xor(); // === false
Truth.of([false, false, false]).nor(); // === true : NOR operation means all are false
Truth.of([true, false, true]).nor(); // === false

// applying an example
const x = 2;
// check a simple range
Truth.of([x < 0, x > 3]).or(); // === false
// check a simple range plus type
Truth.of([x < 3, x > 0, typeof x !== 'string']).and(); // === true
// validate `x` is not an unwanted type
Truth.of([typeof x !== 'string', typeof x !== 'undefined']).and(); // === true, or, written another way....
Truth.of([typeof x === 'string', typeof x === 'undefined']).nor(); // === true
// check a complex range
Truth.of([x > 1 && x < 6, x === 71, x > 656 && x < 765]).xor(); // === true

// make the complex range more scalable and expressive!
const lowRange = y => Truth.of([x > 1, x < 6]).and();
const higherRange = y => Truth.of([x > 656, x < 765]).and();

Truth.of([lowRange(x), x === 71, higherRange(x)]).xor(); // === true

Conditional function methods

The following uses the functional programming notions of Left/L (failure branch), and Right/R (successful branch) to be consistent with functional styles. In short, L = false, R = true. Failure first, then success.

.forkAnd(functionL, functionR), .forkOr(fL, fR), .forkNor(fL, fR), .forkXor(fL, fR)

The fork methods will run the first function provided if there is a false value, the second if there is a true value.

Useful for replacing if/else ternary branching. "Run one function if false, another function if true", for example.

const x = Truth.of([true, true]);

x.forkAnd(
    () => console.log('false branch, will NOT issue this console message!'),
    () => console.log('true branch, will issue this console message!')
);

x.forkNor(
    () => console.log('false branch, will issue this console message!'),
    () => console.log('true branch, will NOT issue this console message!')
);

Additionally, there are left (fL), and right (fR) -only versions that will run one function under the branch specified, and run no functions at all if that branch is not encountered.

.forkAndL(fL), .forkAndR(fR)
.forkOrL(fL), .forkOrR(fR)
.forkNorL(fL), .forkNorR(fR)
.forkXorL(fL), .forkXorR(fR)

This is useful for replacing simple if conditions. "Run function if true", for example.

const x = Truth.of([true, false]);

x.forkAndL(() => console.log('false branch, will issue this console message!'));

x.forkAndR(() =>
    console.log(
        'true branch, will NOT issue this console message, or do anything at all!'
    )
);

Inspection method

This is a simple functional concept for debugging purposes.

.inspect()

In case you want a peek inside a Truth statement, you can use this to convert the value to a string.

const a = 1;
const x = Truth.of([a > 0, a > 100]);

x.inspect(); // "Truth(true,false)"

BoolTable

BoolTable.of([ [string, condition], [string, condition], ... ]);

Create a descriptive conditions table. Each row takes two values, a string and a condition that evaluates to true or false.

Query method

.query(string), or .q(string)

Simply pass a string and it will return its matching condition. Useful to create expressive condition queries.

This API is best used in a Decision table, but the example below shows how it might work independent of that.

const isEven = x => Truth.of([typeof x === 'number', x % 2 === 0]).and();
const isOdd = x => Truth.of([typeof x === 'number', x % 2 !== 0]).and();

const t = v =>
    BoolTable.of([
        ['the value is an even number', isEven(v)],
        ['the value is an odd number', isOdd(v)],
        ['the value is not a number', isNaN(v)]
    ]);

const testString = t('string');

// > true
console.log(testString.q('the value is not a number'));
// > false
console.log(testString.q('the value is an odd number'));
// > false
console.log(testString.q('the value is an even number'));

Inspection method

This is a simple functional concept for debugging purposes.

.inspect()

In case you want a peek inside a BoolTable statement, you can use this to convert the value to a string.

Extending the previous example:

const testString = t('string');

testString.inspect();
// BoolTable(the value is an even number,false,the value is an odd number,false,the value is not a number,true)

Decision

Decision.of([ [condition, (value | function) [, fnParameter]], [...], ... ]]);

Create a decision table, which may either return a value, or execute a function with a given value.

This is easier to show in an example than to document by normal means.

const mergeObj = (objs) => objs.reduce((acc, cur) => Object.assign(acc, cur));
const age = 22;
const permissions = Decision.of([
    [age > 15, { allowedToDrive: true }],
    [age > 18, { allowedToVote: true }],
    [age > 21, { allowedToDrinkAlcohol: true }],
    [age > 65, { allowedSeniorsDiscount: true }]
]).run('any').chain(mergeObj); // (chain takes resulting values and passes to a function)
// > { "allowedToDrinkAlcohol": true, "allowedToDrive": true, "allowedToVote": true }

Run method

.run(method)

This will run through the table using either a specified method, or by default, just the first true row.

Methods

first: (default) Run only first true row encountered
last: Run only the last true row encountered
any: Run any true rows encountered, returning results as array
2: (any positive integer) Run only the first 2 rows encountered, returning result as array

Notes

There are two ways to use Decision: to return specific values, or to run specific functions (that may or may not return values).

If you require values, you will need to follow .run() with an unwrap method like .join() or .chain(), otherwise they will be inaccessible. (If you do not require values back, you need not add an unwrap method call.)

.join() will unwrap the results as they are. .chain() will pass them to a function. (These are both concepts from functional programming.)

Other functional methods (common to Truth, Decision, BoolTable)

Advanced section!

If you're familiar with functional programming, you might recognize Truth, Decision, and BoolTable to be monads. This means they comes with standard, out-of-the-box methods.

.ap(M), .chain(f), .map(f), .join()

Those all do what you'd expect of a monad, they obey the monad laws. See the unit tests for examples, and proof of monad law compliance.

.concat(M), .head(), .tail(), .isEmpty()

Because these are typed monads that contains an array, certain array-based methods have been added.

Only .concat takes a parameter, and that parameter must be another monad of the same type.

Example techniques

Below are some example techniques for how the API might be used.

Returning a Decision from a function to make multiple types of queries

import { Truth, Decision, BoolTable } from 'booltable';

// simplest: [Condition, Result]
const makeDecision = x =>
    Decision.of([
        [x > 1, 2],
        [x === 1, 3],
        [x === 0, 3.5],
        [(!x, 4)],
        // default, always true
        [true, 10]
    ]);

// result1 === 2;
// uses default 'first', meaning first true result returns
const result1 = makeDecision(2)
    .run()
    .join();

// result2 === [3.5, 4, 10];
// 'any' means any conditions are true, returns array of results
const result2 = makeDecision(0)
    .run('any')
    .join();

// result3 === 10
// 'last' means last true result returns
const result3 = makeDecision(101)
    .run('last')
    .join();

// result4 === [3.5, 4];
// '2' means first two true conditions -- this can be given positive integer
const result4 = makeDecision(0)
    .run(2)
    .join();

Returning a `Truth` from a function to make multiple queries

const data = {
    aa: 1,
    bb: true,
    cc: [0],
    dd: { test: 'a' },
    ee: false
};

// Taking an array parameter here allows memoization of the function
// This means one could use a memoizer to ensure `result5` through `result8` only execute this function once
const conditions = ([a, b, c]) => Truth.of([a, b, c]);

// result5 === true
// .or() means apply "OR" to these conditions, since data.aa is greater than 0, this returns true
// OR means at least one is true
const result5 = conditions([
    data.aa > 0,
    data.bb === true,
    data.cc.length
]).or();

// result6 === false
// .xor() means apply "XOR" to these conditions, since all items are true, this would return false
// XOR means at least one is true and at least one is false
const result6 = conditions([
    data.aa > 0,
    data.bb === true,
    data.cc.length
]).or();

// result7 === false
// .nor() means apply "NOR" to these conditions, since all items are true, this would return false
// NOR means all are false
const result7 = conditions([
    data.aa > 0,
    data.bb === true,
    data.cc.length
]).nor();

// result8 === true
// .and() means apply "AND" to these conditions, since all items are true, this would return true
// AND means all are true
const result8 = conditions([
    data.aa > 0,
    data.bb === true,
    data.cc.length
]).nor();

// since the results evaluate to `true` or `false`, can be used in Decision table
Decision.of([
    [result5, 3],
    [result6, 2],
    [result7, 3],
    [result8, 0],
    // default, always returns true
    [true, 10]
]);

`Truth` as a truth table

This is an example of how Truth can be used like a truth table, using the methods provided.

const a = 2;
const b = 3;
const c = 15;
const d = 150;

const logic1 = Truth.of([a > 11, b === 2, !c, d - 1 >= 100]);
const logic2 = Truth.of([a < b, b !== 4, c > a, d < 1000]);
const logic3 = Truth.of([a < b, b === 4, c === a, d > 1000]);

const	I	II	III	IV	.and()	.or()	.nor()	.xor()
logic1	a > 11	b === 2	!c	(d - 1) >= 100	false	true	false	true
logic2	a < b	b !== 4	c > a	d < 1000	true	true	false	false
logic3	a < b	b === 4	c === a	d > 1000	false	false	true	false

This can be also created using a more expressive API, BoolTable.

const tt = BoolTable.of([
    ['is logic1 true with and?', logic1.and()],
    ['is logic2 true with and?', logic2.and()],
    ['is logic3 true with xor?', logic3.xor()]
]);

// false
tt.q('is logic1 true with and?');

// true
tt.q('is logic2 true with and?');

// false
tt.q('is logic3 true with xor?');

`Decision` as a deicision table

This is an example of how Decision can be like a decision table.

const makeDecision = x =>
    Decision.of([
        [x > 1, warn('reading is too high')],
        [x === 1, notice('things look good')],
        [x === 0, warn('reading is zero')],
        [x === undefined, error('no reading found')],
        // default, always true
        [true, error('reading is out of range')]
    ]);

condition 1	action
x > 1	warn('reading is too high')
x === 1	notice('things look good')
!x	warn('reading is zero')
x === 0	warn('reading is zero')
x === undefined	error('no reading found')
default	error('reading is out of range')

Of course, this is very basic. One can the use Truth in combination to identify multiple conditions.

// we use ([x, y, z]) so the fns are still memoizable even though there are multiple params
const cond1 = ([x, y, z]) => Truth.of([x > 1, y > 1, z > 1]).and();
const cond2 = ([x, y, z]) => Truth.of([x > 1, y < 1, z < 1]).and();
const cond3 = ([x, y, z]) => Truth.of([x < 1, y < 1, z < 1]).and();

const makeDecision = ([x, y, z]) =>
    Decision.of([
        [cond1([x, y, z]), warn('all readings high')],
        [cond2([x, y, z]), warn('x is high')],
        [cond3([x, y, z]), notice('all readings in normal range')]
    ]);

makeDecison([1.25, 0.5, 0.1]).run();
// result runs `warn('x is high')`

Note that one could also write the above with three items in each row:

const makeDecisionExpanded = ([x, y, z]) =>
    Decision.of([
        // condition(s), fn, argument
        [cond1([x, y, z]), warn, 'all readings high'],
        [cond2([x, y, z]), warn, 'x is high'],
        [cond3([x, y, z]), notice, 'all readings in normal range']
    ]);

Let's add some expressivity:

const bt = ([x, y, z]) =>
    BoolTable.of([
        ['are all the readings high?', cond1([x, y, z])],
        ['is x high?', cond2([x, y, z])],
        ['are things normal?', cond3([x, y, z])]
    ]);

const makeDecisionExpanded = (
    vals // vals === Array [x, y, z], more readable and still memoizable
) =>
    Decision.of([
        // condition(s), fn, argument
        // are/is interchangable
        [bt(vals).q('are all the readings high?'), warn, 'all readings high'],
        [bt(vals).q('is x high?'), warn, 'x is high'],
        [
            bt(vals).q('are things normal?'),
            notice,
            'all readings in normal range'
        ]
    ]);

All these result in a decision table like this:

condition 1	condition 2	condition 3	action (AND)
x > 1	y > 1	z > 1	warn('all readings high')
x > 1	y < 1	z < 1	warn('x is high')
x < 1	y < 1	z < 1	notice('all readings in normal range')

This is a very basic example of a decision table, and is only using .and() in the calculation of true/false. One could have much more complex logic.

Development

Source is written in TypeScript. Run tests via npm run test.

MIT License

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

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BoolTable

Install

Summary of BoolTable APIs

Truth

Decision

BoolTable

Bringing them together

Example: Thermostat

Premise

First pass: basic, unoptimized Decision example

Second pass: add hardening

Third pass: optimizing readability with constant function expressions

Final pass: optimizing expressivity with BoolTable

The APIs

Truth

Boolean expression methods

Conditional function methods

Inspection method

BoolTable

Query method

Inspection method

Decision

Run method

Methods

Notes

Other functional methods (common to Truth, Decision, BoolTable)

Example techniques

Returning a Decision from a function to make multiple types of queries

Returning a Truth from a function to make multiple queries

Truth as a truth table

Decision as a deicision table

Development

MIT License

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`Truth`

`Decision`

`BoolTable`

First pass: basic, unoptimized `Decision` example

Final pass: optimizing expressivity with `BoolTable`

`Truth`

Returning a `Truth` from a function to make multiple queries

`Truth` as a truth table

`Decision` as a deicision table

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