Jds.TestingUtils.Randomization 0.4.0-build-20220214-011232-sha-4d58823

Testing Utils: Randomization

This collection of randomization test utilities supports creating test arrangements.

How to Use

All examples below use the thread-safe, static Jds.TestingUtils.Randomization.Randomizer.Shared instance of IRandomizationSource, which generates random values using System.Random.Shared. This IRandomizationSource is advised for most tests.

If a different algorithm is needed, e.g., a cryptographically strong random number generator is required, consider creating a Jds.TestingUtils.Randomization.ArrangedRandomizationSource. It uses provided Func<IEnumerable<>> delegates to supply values when requested.

If a specific set of random-seeming data is needed, consider creating a Jds.TestingUtils.Randomization.DeterministicRandomizationSource. It uses provided IEnumerable<> sources to supply values when requested.

Add Jds.TestingUtils.Randomization NuGet Package and Add using

Add Jds.TestingUtils.Randomization NuGet package to the test project.

Add the extensions to your test files with the following using statement:

using Jds.TestingUtils.Randomization;

All examples below assume the following additional using statements:

using System;
using System.Collections.Generic;
using System.Linq;

Generate Pseudo-random Numbers

• IRandomizationSource.Boolean()
  • Gets a pseudo-random bool.
• IRandomizationSource.Byte()
  • Gets a pseudo-random byte, greater than or equal to byte.MinValue, and less than byte.MaxValue.
• IRandomizationSource.ByteInRange(byte minInclusive, byte maxExclusive)
  • Gets a pseudo-random byte, greater than or equal to minInclusive, and less than maxExclusive.
• IRandomizationSource.Double()
  • Gets a pseudo-random double, using IRandomizationSource.NextDouble. The value should be greater than or equal to 0.0, and less than 1.0.
• IRandomizationSource.Float()
  • Gets a pseudo-random float, using IRandomizationSource.NextFloat. The value should be greater than or equal to 0.0, and less than 1.0.
• IRandomizationSource.Int()
  • Gets a pseudo-random int, using IRandomizationSource.NextIntInRange. The value should be greater than or equal to int.MinValue, and less than int.MaxValue.
• IRandomizationSource.IntInRange(int minInclusive, int maxExclusive)
  • Gets a pseudo-random int, using IRandomizationSource.NextIntInRange. The value should be greater than or equal to minInclusive, and less than maxExclusive.
• IRandomizationSource.IntNegative()
  • Gets a pseudo-random int, using IRandomizationSource.NextIntInRange. The value should be greater than or equal to int.MinValue, and less than 0.
• IRandomizationSource.IntPositive()
  • Gets a pseudo-random int, using IRandomizationSource.NextIntInRange. The value should be greater than or equal to 0, and less than int.MaxValue.
• IRandomizationSource.Long()
  • Gets a pseudo-random long, using IRandomizationSource.NextLongInRange. The value should be greater than or equal to long.MinValue, and less than long.MaxValue.
• IRandomizationSource.LongInRange(long minInclusive, long maxExclusive)
  • Gets a pseudo-random long, using IRandomizationSource.NextLongInRange. The value should be greater than or equal to minInclusive, and less than maxExclusive.
• IRandomizationSource.LongNegative()
  • Gets a pseudo-random long, using IRandomizationSource.NextLongInRange. The value should be greater than or equal to long.MinValue, and less than 0.
• IRandomizationSource.LongPositive()
  • Gets a pseudo-random long, using IRandomizationSource.NextLongInRange. The value should be greater than or equal to 0, and less than long.MaxValue.

Select a Random Item or Enumeration Value

• IRandomizationSource.RandomEnumValue<TEnum>()
  • Selects a pseudo-random value from the enum of type specified (TEnum).
  • Example: Randomizer.Shared.RandomEnumValue<System.Net.HttpStatusCode>()
• IRandomizationSource.RandomListItem<T>(IReadOnlyList<T> items)
• IReadOnlyList<T>.GetRandomItem<T>()
  • Selects a pseudo-random item from provided items.
  • Example: Randomizer.Shared.RandomListItem(System.Linq.Enumerable.Range(1, 20).ToArray())

Select a Weighted Random Item or Dictionary Key

• IRandomizationSource.RandomListItem<T>(IReadOnlyList<(T Item, double Weight)> weightedItems)
• IRandomizationSource.RandomListItem<T>(IReadOnlyList<(T Item, int Weight)> weightedItems)
• IReadOnlyList<(T Key, double Weight)>.GetWeightedRandomItem<T>()
• IReadOnlyList<(T Key, int Weight)>.GetWeightedRandomItem<T>()
  • Selects a pseudo-random .Item from provided weightedItems; item selection is weighted based upon relative .Weight.
  • Example:

Randomizer.Shared.WeightedRandomListItem(
  new[] { ("Sure", 1000), ("Likely", 500), ("Possible", 200), ("Unlikely", 50), ("Rare", 5), ("Apocryphal", 1) }
);

• IRandomizationSource.GetWeightedRandomKey<T>(IReadOnlyDictionary<T, double> weightedKeys)
• IRandomizationSource.GetWeightedRandomKey<T>(IReadOnlyDictionary<T, int> weightedKeys)
• IReadOnlyDictionary<T, double>.GetWeightedRandomKey<T>()
• IReadOnlyDictionary<T, int>.GetWeightedRandomKey<T>()
  • Selects a pseudo-random .Key from provided weightedItems; item selection is weighted based upon relative .Value.
  • Example:

Randomizer.Shared.WeightedRandomKey(new Dictionary<string, double>
{
  { "North", 0.4 }, { "East", 0.1 }, { "West", 0.1 }, { "South", 0.4 }
});

Generate a Random String

• IRandomizationSource.RandomString(int length, IReadOnlyList<char> chars)
  • Generates a pseudo-random string of length characters, using provided chars. Random selections from chars are concatenated until reaching length characters.
• IRandomizationSource.RandomString(int length, IReadOnlyList<string> strings)
  • Generates a pseudo-random string of length characters, using provided strings. Random selections from strings are concatenated until reaching length characters. The result is truncated to length characters.
• IRandomizationSource.RandomStringLatin(int length, bool uppercase = false, bool alphanumeric = false)
  • Generates a pseudo-random string of length characters using ASCII Latin characters. Uses a - z by default. If uppercase, uses A - Z. If alphanumeric, also includes 0 - 9 with either casing.

Generate a Mail Address

• IRandomizationSource.MailAddress()
• IRandomizationSource.MailAddress(int length)
  • Generates a pseudo-random System.Net.Mail.MailAddress. The generated System.Net.Mail.MailAddress.User will be a dot-atom form of local-part (see RFC-2822 section 3.4.1). The generated System.Net.Mail.MailAddress.Host will be a domain (see RFC-1035 section 2.3.1).
• IRandomizationSource.MailAddressAddrSpec(int length)
• IRandomizationSource.MailAddressAddrSpec((int LocalPartLength, int DomainLength) componentLengths)
  • Generates a pseudo-random string according to addr-spec (see RFC-2822 section 3.4.1). The generated local-part will be of dot-atom form (see RFC-2822 section 3.4.1). The generated domain will be of dot-atom form (see RFC-2822 section 3.4.1), and its value will be generated as a RFC-1035 section 2.3.1 domain.

Generate a Domain

• IRandomizationSource.DomainName(int length)
• IRandomizationSource.DomainName(IReadOnlyList<int> domainLabelLengths)
  • Generates a pseudo-random string according to domain (see RFC-1035 section 2.3.1).

Generate a URL

• IRandomizationSource.RandomUrl(int hostLength, int pathLength = 0, int queryLength = 0, int fragmentLength = 0, string scheme = "https", int? port = null)
  • Generates a pseudo-random string URL according to RFC-3986 URI syntax. The host segment is generated using IRandomizationSource.DomainName(int length).

Generate a Sequence of Items from a Markov Chain Model

• IRandomizationSource.CreateMarkovGenerator(IReadOnlyCollection<IReadOnlyList<T>> sources, int chainLength = 1) where T : notnull, IEquatable<T>
  • Generates a Func<int, IReadOnlyList<T>> which accepts an int maxLength and uses a Markov Chain model, derived from sources, to generate sequences of T of up to length maxLength.
    • The chainLength determines how many T are grouped to determine Markov Chain probability.
• IRandomizationSource.CreateMarkovGenerator(IEnumerable<string> sources, int chainLength = 1)
  • Generates a Func<int, string> which accepts an int maxLength and uses a Markov Chain model, derived from sources, to generate strings of up to length maxLength.
    • The chainLength determines how many characters in each input string are grouped to determine Markov Chain probability.
  • Example uses: create a random word or name generator using a list of example words or names.
  • Example:

var exampleFruitNames = new[]
  {
    "apple", "apricot", "avocado", "banana", "blackberry", "blackcurrant", "blueberry", "boysenberry", "cantaloupe",
    "caper", "cherry", "cranberry", "elderberry", "fig", "gooseberry", "grape", "grapefruit", "guava", "jujube",
    "kiwi", "kumquat", "lemon", "lime", "lychee", "mango", "mulberry", "olive", "orange", "papaya", "pear",
    "persimmon", "pineapple", "plantain", "plum", "pomegranate", "raspberry", "starfruit", "strawberry", "tangerine",
    "watermelon"
  };

Func<int, string> fruitGenerator = Randomizer.Shared.CreateMarkovGenerator(sources: exampleFruitNames, chainLength: 2);

string generatedFruit = fruitGenerator(maxLength: 12);
string possiblyLongerGeneratedFruit = fruitGenerator(maxLength: 20);
string likelyShorterGeneratedFruit = fruitGenerator(maxLength: 6);

• IRandomizationSource.GenerateRandomMarkov<T>(IReadOnlyCollection<IReadOnlyList<T>> sources, int? maxLength = null, int chainLength = 1)
  • Generates a IReadOnlyList<T> based upon a Markov Chain model, derived from sources..
    • The chainLength determines how many items in each input IReadOnlyList<T> are grouped to determine Markov Chain probability.
  • Use IRandomizationSource.CreateMarkovGenerator() (above), instead of this function, unless only a single value is needed.
    • The resources needed to generate the Markov Chain model are non-trivial. This function creates a new model each time it is executed, consuming both computational and memory resources.
• IRandomizationSource.GenerateRandomMarkov(IEnumerable<string> sources, int? maxLength = null, int chainLength = 1)
  • Generates a string based upon a Markov Chain model, derived from sources..
    • The chainLength determines how many characters in each input string are grouped to determine Markov Chain probability.
  • Use IRandomizationSource.CreateMarkovGenerator() (above), instead of this function, unless only a single value is needed.
    • The resources needed to generate the Markov Chain model are non-trivial. This function creates a new model each time it is executed, consuming both computational and memory resources.
  • Example uses: create a random word or name generator using a list of example words or names.
  • Example:

var exampleFruitNames = new[]
  {
    "apple", "apricot", "avocado", "banana", "blackberry", "blackcurrant", "blueberry", "boysenberry", "cantaloupe",
    "caper", "cherry", "cranberry", "elderberry", "fig", "gooseberry", "grape", "grapefruit", "guava", "jujube",
    "kiwi", "kumquat", "lemon", "lime", "lychee", "mango", "mulberry", "olive", "orange", "papaya", "pear",
    "persimmon", "pineapple", "plantain", "plum", "pomegranate", "raspberry", "starfruit", "strawberry", "tangerine",
    "watermelon"
  };

string similarGeneratedFruit = Randomizer.Shared.GenerateRandomMarkov(sources: exampleFruitNames, maxLength: 12, chainLength: 2);
string slightlySimilarGeneratedFruit = Randomizer.Shared.GenerateRandomMarkov(sources: exampleFruitNames, maxLength: 20, chainLength: 1);
string verySimilarGeneratedFruit = Randomizer.Shared.GenerateRandomMarkov(sources: exampleFruitNames, maxLength: 15, chainLength: 3);