JSCheck

Douglas Crockford
2017-09-21

JSCheck is a testing tool for JavaScript. It was inspired by QuickCheck, a testing tool for Haskell developed by Koen Claessen and John Hughes of Chalmers University of Technology.

JSCheck is a specification-driven testing tool. From a description of the properties of a system, function, or object, it will generate random test cases attempting to prove those properties, and then report its findings. That can be especially effective in managing the evolution of a program because it can show the conformance of new code to old code. It also provides an interesting level of self-documentation, because the executable specifications it relies on can provide a good view of the workings of a program.

The JSCheck module is loaded from the JSCheck.js file. It produces a single function that is used to create a jsc object.

import JSCheck from "./jscheck.js"
let jsc = JSCheck();

The source is available at https://github.com/douglascrockford/jscheck. This page is available at http://www.jscheck.org/.

Making a Claim

JSCheck is concerned with the specification and checking of claims. (QuickCheck called these properties. We use the term claim instead of property to avoid confusion with JavaScript's use of property to mean a member of an object.)

jsc.claim returns a claim function, which may be passed as an argument to the jsc.check function, which will randomly generate the cases that will attempt to prove the claim. You can set the number of cases generated per claim with the jsc.reps function.

To make a claim, you pass three or four components to jsc.claim(name, predicate, signature, classifier), which will then return a function.

name

The name is descriptive text that will be used in making the report.

predicate

The predicate is a function that will return a verdict of true if the claim holds. The predicate will do something with the system being tested, perhaps examining its result or examining the consistency of its data structures. If you are testing a set of functions that do encoding and decoding, the predicate can assert things like

function predicate(verdict, value) {
    return verdict(value === decode(encode(value)));
}

You won't need to select the value. JSCheck can generate random values for you.

The first parameter to the predicate will always be the verdict function. The predicate function uses the verdict function to announce the result of the case (true if the case succeed, and false if it failed). The verdict function makes it possible to conduct tests that might be completed in a different turn, such as tests involving event handling, network transactions, or asynchronous file processing.

The remaining parameters must match the specifiers.

signature

The signature is an array of specifiers that describe the types of the predicate's arguments. (From a procedural perspective, specifiers are generators, but are quite different from ES6 function*, so to slightly reduce confusion, we will take a declarative view.)

JSCheck provides a small library of specifiers that you can use in your claim. For example, jsc.integer(10) declares that a parameter should be an integer between 1 and 10. jsc.one_of(["Curly", "Larry", "Moe"]) declares that a parameter can be one of three strings. Some of the specifiers can be combined, so jsc.array(jsc.integer(10), jsc.character("a", "z")) declares that a parameter can be an array of 1 to 10 lowercase letters.

An array of specifiers can also contain constants (such as string, numbers, or objects), so you can pass anything you need to into the predicate. If you need to pass in a function, then you must wrap the function value with the jsc.literal specifier.

You can also create your own specifiers.

classifier

You can optionally pass a classifier function as part of the claim. The classifier will receive the same arguments as the predicate (excluding the verdict). A classifier can do two things:

  1. It can examine the arguments, and return a string that classifies the case. The string is descriptive. The report can include a summary showing the number of cases belonging to each classification. This can be used to identify the classes that are trivial or problematic, or to help analyze the results.
  2. Since the cases are being generated randomly, some cases might not be meaningful or useful. The classifier can have a case rejected by returning false. JSCheck will attempt to generate another case to replace it. It is recommended that the classifier reject fewer than 90% of the cases. If you are accepting less than 10% of the potential cases, then you should probably reformulate your claim or create a specialized specifier.

The JSCheck functions

A jsc object contains several functions.

Configuration:

The configuration functions set up the jsc object.

jsc.detail(level)

By setting the level of detail to a particular number, you can determine how much information is included in the report. The report will be delivered to the function designated with jsc.on_report. The default is 3.

  1. none: There will be no report.
  2. terse: There will be a minimal report, showing the pass score of each claim.
  3. failures: The individual cases that fail will be reported.
  4. qualification: The qualification summaries will be reported (default).
  5. verbose: All cases will be reported.

It returns the jsc object.

jsc.on_fail(function(object))

The on_fail function allows the registration of a callback function that will be given an object for each failed case. This can be used to begin deeper processing. The callback function will be passed an object containing these properties:

It returns the jsc object.

jsc.on_lost(function(object))

The on_lost function allows the registration of a callback function that will be given an object for each lost case. A case is considered lost if the predicate did not return a boolean verdict within the allotted milliseconds. The callback function will be passed an object containing these properties:

jsc.on_pass(function(object))

The on_pass function allows the registration of a callback function that will be given an object for each passing case. This can be used to trigger further tests or to begin deeper processing or reporting. The callback function will be passed an object containing these properties:

It returns the jsc object.

jsc.on_report(function(string))

The on_report function allows the registration of a callback function that will be given a string containing the results for each claim. The callback function could route the report to a console or a log or alert. The level of detail is set with jsc.detail.

It returns the jsc object.

jsc.on_result(function(object))

The on_result function allows the registration of a callback function that will be given an object summarizing the check. The callback function will be passed an object containing these properties:

jsc.reps(repetitions)

The reps function allows setting the number of repetitions per claim. The default is 100. The number of proposed cases could be as many as 10 times this number, to allow for rejection by your classifier function.

It returns the jsc object.

Specifiers:

A specifier is a function that returns a function that can generate values of a particular type. The specifiers are used in building the signature that is used to construct a claim.

jsc.any()

The any specifier returns any random JavaScript value. It is short for

jsc.one_of([
    jsc.integer(),
    jsc.number(),
    jsc.string(),
    jsc.one_of([
        true,
        Infinity,
        -Infinity,
        false,
        null,
        undefined,
        "",
        0,
        1,
        NaN
    ])
])

It can produce values such as

0.5166432844718089
"_g"
0
499
""
419
"N"

jsc.array()

The array specifier returns an array containing random stuff. It is short for jsc.array(jsc.integer(4), jsc.any()). So for example,

jsc.array()

can produce arrays such as

["enWsH$",null]
[false,"\\eXt]jBS"," W6"]
[7,"!jd"]
[11]
...

jsc.array(array)

The array specifier takes an array as a template. It will go through the array, expanding the specifiers it contains. So, for example,

jsc.array([
    jsc.integer(),
    jsc.number(100),
    jsc.string(8, jsc.character("A", "Z"))
])

can generate arrays like

[3,21.228644298389554,"TJFJPLQA"]
[5,57.05485427752137,"CWQDVXWY"]
[7,91.98980208020657,"QVMGNVXK"]
[11,87.07735128700733,"GXBSVLKJ"]
...

jsc.array(dimension, value)

The array specifier takes a number and a value, and produces an array using the number as the length of the array, populating the array with the value. So, for example,

jsc.array(3, jsc.integer(640))

can generate arrays like

[305,603,371]
[561,623,477]
[263,534,530]
[163,148,17]
...

jsc.boolean()

The boolean specifier will produce true and false with equal probability. It is shorthand for jsc.boolean(0.5).

jsc.boolean(bias)

The boolean specifier will produce true and false. If the bias is 0.50, it will produce them with equal probability. A lower bias will produce more falses, and a higher bias will produce more trues.

jsc.character()

The character specifier generates a character. It is short for jsc.character(32, 126). So, for example,

jsc.character()

can generate strings like

"*"
"a"
"J"
"0"
...

jsc.character(code)

The character specifier treats its argument as a char code, generating a character.

jsc.character(min_character, max_character)

The character specifier generates characters within a given range.

jsc.falsy()

The falsy specifier generates falsy values: false, null, undefined, "", 0, and NaN.

jsc.integer()

The integer specifier generates prime numbers. Sometimes when testing formulas, it is useful to plug prime numbers into the variables.

jsc.integer(i)

The integer specifier generates an integer between 1 and i.

jsc.integer(i, j)

The integer specifier generates an integer between i and j.

jsc.literal(value)

The literal specifier generates the value without interpreting it. For most values (strings, numbers, boolean, objects, arrays), the literal specifier is not needed. It is needed if you want to pass a function value to a predicate, because function values are assumed to be the products of specifiers.

jsc.number(x)

The number specifier produces random numbers between 0 and x.

jsc.number(x, y)

The number specifier produces random numbers between x and y.

jsc.object()

The object specifier produces random objects containing random keys and values. So for example.

jsc.object()

can generate objects like

{"adf*:J'mS%":""}
{"_S-":0.23757726117037237,"{U":3,"[":null,":vL|_":"Bl=2C"}
{"pV":0.8472617215011269,"3:":"xVvi`","jGB8y":5,"$<9BFhA":true}
{"1":7,"H@C>":0.01756326947361231}
...

jsc.object(n)

The object specifier makes an object containing n random keys and values.

jsc.object(object)

The object specifier takes an object as a template. It will go through the enumerable own properties of object, expanding the specifiers it contains. So, for example,

jsc.object({
    left: jsc.integer(640),
    top: jsc.integer(480),
    color: jsc.one_of(["black", "white", "red", "blue", "green", "gray"])
})

can generate objects like

{"left":104,"top":139,"color":"gray"}
{"left":62,"top":96,"color":"white"}
{"left":501,"top":164,"color":"white"}
{"left":584,"top":85,"color":"white"}
...

jsc.object(keys, values)

The object specifier takes an array of keys and produces an object using those keys. The values are taken from an array of values or a specifier. So for example,

jsc.object(
    jsc.array(jsc.integer(3, 8), jsc.string(4, jsc.character("a", "z"))),
    jsc.boolean()
)

can generate objects like

{"jodo":true,"zhzm":false,"rcqz":true}
{"odcr":true,"azax":true,"bnfx":true,"hmmc":false}
{"wjew":true,"kgqj":true,"abid":true,"cjva":false,"qsgj":true,"wtsu":true}
{"qtbo":false,"vqzc":false,"zpij":true,"ogss":false,"lxnp":false,"psso":true,"irha":true,"ghnj":true}
...

and

jsc.object(
    ["x", "y", "z"],
    [jsc.integer(320), jsc.integer(240), jsc.integer(100)]
)

can generate objects like

{"x":99,"y":51,"z":51}
{"x":114,"y":166,"z":82}
{"x":35,"y":124,"z":60}
{"x":13,"y":41,"z":63}
...

jsc.one_of(array)

The one_of specifier takes an array of specifiers, and selects values from the array with equal probability. So, for example

jsc.one_of([
    jsc.number(),
    jsc.boolean(),
    null
])

produces values like

0.09817210142500699
0.3351482313591987
null
false
...

jsc.one_of(array, weights)

The one_of specifier takes an array of specifiers and an array of weights. The weights are used to adjust the probabilities. So for example,

jsc.one_of(
   [1,2,3,4,5,6,7,8,9,10],
   [1,2,3,4,5,6,7,8,9,10]
)
produces values like
8
10
6
10
...

jsc.one_of(string)

The one_of specifier takes a string, and selects one of its characters. So for example,

jsc.string(8, jsc.one_of("abcdefgABCDEFG_$"))

produces values like

"cdgbdB_D"
"$fGE_BAB"
"gEFF_FAe"
"AebGbAbd"
...

jsc.sequence(array)

The sequence specifier takes an array of values, and produces them in sequence, repeating the sequence as needed. So for example,

jsc.sequence([1, 2])

produces values like

1
2
1
2
...

jsc.string()

The string specifier makes random ASCII strings. It is short for jsc.string(jsc.integer(10), jsc.character()). So for example,

jsc.string()

produces strings like

"hZO*3"
"m-W2@KL"
",P+po0#2 "
"tlt^[ ui`V"
...

jsc.string(value)

The string specifier generates the stringification of the value, using JSON.stringify. So for example,

jsc.string(jsc.integer(1000, 9999))

produces values like

"4791"
"9523"
"2774"
"4288"
...

jsc.string(number, value)

The string specifier generates strings by joining some number of values. So for example,

jsc.string(jsc.integer(1, 8), jsc.one_of("aeiou")))

produces values like

"ieauae"
"uo"
"iuieio"
"euu"
...

Any number of number value pairs can be provided, so

jsc.string(
    1, jsc.character("A", "Z"),
    4, jsc.character("a", "z"),
    6, jsc.character("1", "9"),
    1, jsc.one_of("!@#$%")
)

produces values like

"Zsopx171765#"
"Nfafw851294%"
"Gtyef393138%"
"Lrxav768561%"
...

Claim processing:

The jsc.claim function creates claims, and the jsc.check function tests the claims by generating the cases and producing the reports.

jsc.check(milliseconds)

Process all of the claims that have been constructed since the beginning.

If the milliseconds are specified, that determines the amount of time to wait before declaring that the unfinished cases are lost. The default is to wait forever.

It returns the jsc object.

jsc.check(group, milliseconds)

Process all of the claims of a specific group. The group name will have been given to jsc.group to associate a set of claims.

If the milliseconds are specified, that determines the amount of time to wait before declaring that the unfinished cases are lost. The default is to wait forever.

It returns the jsc object.

jsc.check(claim, milliseconds)

Process the specific claim function.

If the milliseconds are specified, that determines the amount of time to wait before declaring that the unfinished cases are lost. The default is to wait forever.

It returns the jsc object.

jsc.claim(name, predicate, signature, classifier)

The claim function takes a name, a predicate function, and a signature.

The predicate function should return verdict(true) if a case passes, and return verdict(false) if the case fails.

The signature is an array of specifiers. The signature looks like a type declaration for the predicate function.

It returns a function that can be processed by jsc.check.

jsc.claim(name, predicate, signature, classifier, dont)

The claim function takes a name, a predicate function, and an array of specifiers.

The predicate function should return verdict(true) if a case passes, and return verdict(false) if the case fails. It will take a list of arguments that is generated by the array of specifiers. The array of specifiers looks like a type declaration for the predicate function.

The signature is an array of specifiers. The signature looks like a type declaration for the predicate function.

The classifier function is called before each call of the predicate function. It gets a chance to determine if the random values in its arguments will be a reasonable case. It can return false if the case should be rejected and a new case generated to replace it. The classifier function can instead return a descriptive string that describes the case. These can be counted and displayed in the report.

If dont is true, then the claim will not be added to the current group, nor will it be added to the set of all claims.

It returns a function that can be processed by jsc.check.

jsc.group(name)

The group function is used to specify a group name that will be attached to all new claims. This makes it easy to process a group of claims together.

jsc.test(name, predicate, signature, classifier, milliseconds)

The test function calls the check function, passing the result of the claim function.

Writing specifiers

JSCheck provides a small set of specifiers that can be combined in many ways. For some purposes, you may need to create your own specifiers. It is easy to do. A specifier is a function that returns a function.

my_specifier = function specifier(param1, param2) {

// per claim processing happens in here

    return function generator() {

// per case processing happen in here

        return value;
    };
}

The generator function that is returned will be stored in the signature array, and will be called for each value that needs to be generated. It will have access to the specifier's parameters. Its arguments might be other specifiers, so if an argument is a function, use the result of calling the function.

intermediate_value = (typeof param1 === "function")
    ? param1()
    : param1;

Using JSCheck

Since JSCheck performs a useful specification and description function as well as a testing function, it is recommended (but not required) that claims be inserted into the relevant source code, and not in separate source files. JSDev can make this easy to manage, so that claims can be removed automatically from production code. All of the calls to jsc can be hidden in special comments, which are activated during development, and removed by minification in production.

Demonstration

One difficulty in demonstrating testing systems is that the exposition of the system to be tested is usually significantly more complex than the testing tool being demonstrated. So in this case, we will be testing a trivial function. We will make an incorrect claim. JSCheck will help us to find the error in the claim. It might seem counter productive to demonstrate bad claim making, but it turns out that it is as important to get the claims right as it is to get the program right.

We are going to test the le function.

function le(a, b) {
    return a <= b;
}

We will construct a claim. Our predicate simply returns the result of le. It takes two integers, one with a max of 10 and another with a max of 20. We will classify the cases by the relationship between the arguments.

import JSCheck from "./jscheck.js";
let jsc = JSCheck();
jsc.test(
    "Less than",
    function predicate(verdict, a, b) {
        return verdict(le(a, b));
    },
    [
        jsc.integer(10),
        jsc.integer(20)
    ],
    function classifier(a, b) {
        if (a < b) {
            return "lt";
        } else if (a === b) {
            return "eq";
        } else {
            return "gt";
        }
    }
);

But when we check the claim, many cases fail. The summary of the classification tells the story:

eq pass 7
gt pass 0 fail 22
lt pass 71

The predicate failed because 22 of the generated cases had an a that was larger than b. This is because jsc.integer(10) produces from the range 1 to 10, and jsc.integer(20) produces from the range 1 to 20. Sometimes the first value will be larger. This tells us that we should make the predicate more sophisticated, or we could have the classifier return false instead of "gt" to reject those cases.