List of functional sight words

Functional Sight Words: Reading in Real Life

Functional Sight Words: Reading in Real Life

I am passionate about creating meaningful reading experiences in my student's lives. I teach middle school and it can be hard to find reading material that is age-appropriate for my emergent readers.

What is Reading in Real Life?

As a solution, I've worked many, many hours to create Reading in Real Life. Reading in Real Life is a functional sight words reading program that uses evidence-based instructional practices to teach students the functional words that they see in everyday life. This program is excellent for students with significant disabilities, such as Autism or Down syndrome, or students who are learning English as a second language. RIRL was designed for middle and high school classrooms but can be used with upper elementary students too.

What is included in each Reading in Real Life unit?

Each RIRL unit includes 20-40 themed sight words, broken up into sections in which 5 new words are introduced at a time. As students master the new words, they are added to their maintenance list. Once students master the included words, they can practice reading the words in a variety of different activities. Ideally, students should also have exposure to the words in the natural setting whenever possible. RIRL is unique because the focus isn't just on the student's ability to recognize the word, but there is a large focus on comprehension as well. What good is it to be able to read a word if we don't know what it means? I love that my students are able to read and understand words that they see all the time!

Each Reading in Real Life unit includes a detailed lesson plan, weekly outline, and data sheets. 

Each word/phrase that is taught includes a mini book that explains the sign, its meaning, and where you might see it. These mini books are my favorite part of the Signs Edition bundle! Each unit introduces 5 signs at a time. I like to introduce one a day for the week by reading the mini book that goes along with it and completing the Find It! worksheet. When you've introduced the 5 signs, there are several review worksheets.

How do I use Reading in Real Life in the classroom?

I like to use Reading in Real Life in small groups or one on one to target IEP goals and to supplement my main reading curriculum.

There are several RIRL products available for purchase at this time. You can click on each one to see a detailed description, word list, and preview.

Reading in Real Life: Signs Edition

Reading in Real Life: Signs edition teaches 101 of the most common environmental signs. This bundle is broken up into 4 units.

1) Warning & Safety Signs

2) Community Signs

3) Indoor & Lobby Signs

4) Directional Signs

  ►Reading in Real Life: Colors Edition

  ►Reading in Real Life: Grocery Edition

  ►Reading in Real Life: Cooking Edition

  ►Reading in Real Life: Restaurant Edition

High Frequency Sight Word Lists

The following are a few sight word lists that I use with some of my lower level students to get their reading engines humming before they start an extensive reading session.  There are 7 high frequency word lists in all, broken down into: 1) function words I 2) function words II 3) verbs (including auxiliaries) 4) verbs inflected for past tense (when applicable) 5) nouns & adjectives 6) mixed list I 7) mixed list II.  The words are all pulled from the first 200 most frequent words according to the New General Service List developed by  Browne, Culligan and Phillips and is used under a Creative Commons Attribution 3.0 Unported License.  The sight word lists are (mostly) in their frequency order.

For students who are just learning to read, I sometimes will have them follow along with their finger as I read the words out one at a time.  For students who are working on their letter-sound correspondence, I have them read a list or two out loud and keep track of their time.  For students who are getting a bit more comfortable with reading, but still struggle with issues of automaticity, I give them a specific time to shoot for (under 60 seconds at first).  I realise this might seem a little at odds with the whole idea of extensive reading, but I find that quickly improving students ability to read these high frequency words actually makes extensive reading a lot more pleasurable for my lower level learners. If you have any ideas for how to use sight word lists in your language classroom, I’d love to hear about them in the comments.

These word lists are also available in one spiffy PDF file right here: Sight Word Practice Lists PDF.

Function Words I

Function Words II

Verbs

Verbs, simple past sense

Nouns and adjectives

Mixed List I

Mixed list II

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Types - SwiftBook

There are two kinds of types in Swift: named types and compound types. A named type is a type that can be given a specific name when it is defined. Named types include classes, structures, enums, and protocols. For example, an instance of the user-defined class MyClass has the type MyClass. In addition to user-defined named types, the Swift standard library defines many commonly used named types, including those that are arrays, dictionaries, and optional values.

Data types that are generally considered basic or primitive in other languages, such as types that represent numbers, characters, and strings—actually named types—are defined and implemented in the Swift standard library using structs. Since they are named types, you can extend their behavior to suit the needs of your program using the extension declaration, which is covered in the Extensions chapter.

A composite type is a type without a name, and is self-defined in the Swift language. There are two compound types: function types and tuple types. A composite type can contain named types and other composite types. For example, the tuple type (Int, (Int, Int)) contains two elements: the first is the named type Int, and the second is the composite type (Int, Int).

This chapter discusses self-defined types in the Swift language and describes the behavior of inferred types in Swift.

Type grammar

 type → array-type type → dictionary-type type → function-type type → type-identifier type → tuple-type type → optional-type type → implicitly-unwrapped-optional-type type → protocol-composition-type type → metatype-type type → Any type → Self type → ( type ) 

Type annotation

Type annotation explicitly specifies the type of a variable or expression. Type annotations start with a colon (:) and end with the type name, as shown in the following example:

 let someTuple: (Double, Double) = (3.14159, 2. 71828) func someFunction(a: Int) { /* ... */ } 

In the first example, the expression someTuple is specified to be of the tuple type (Double, Double). In the second example, the a parameter of the someFunction function is assigned the type Int.

Type annotations may contain an optional list of type attributes before the type.

Grammar of the annotation type

 Type-Annotation → :  Attributes  OPT    OPT  Type 
 Type of type 
 
 Type. 
 
 For the most part, a type identifier directly refers to a named type with the same name as the identifier. For example, Int is a type identifier that directly refers to the named type Int, and a type identifier Dictionary directly refers to the named type Dictionary. 
 
 There are two cases in which a type identifier does not refer to a type with the same name. In the first case, the type identifier refers to an alias of a named or composite type. For example, in the example below, the use of Point in the type annotation refers to the tuple type (Int, Int). 
 
 typealias Point = (Int, Int) let origin: Point = (0, 0) 
 
 In the second case, the type identifier uses a dot (.) to denote named types declared in other modules or nested within other types. For example, the type identifier in the following code refers to the named type MyType declared in the ExampleModule. 
 
 var someValue: ExampleModule.MyType 
 
 Type identifier grammar 
 
 type-identifier → type-name generic-argument-clause  opt  | type-name generic-argument-clause  opt   .  type-identifier type-name → identifier 
 
 Tuple type 
 
 A tuple type is a comma-separated list of zero or more types enclosed in parentheses. 
 
 You can use a tuple type as the return type of a function. For the function to return a single tuple containing multiple values. You can also name the elements of the tuple type and use those names to denote the values ​​of the individual elements. The element name consists of an identifier immediately followed by a colon (:). An example that demonstrates both of these functions is in Function Parameters and Return Values. 
 
 If a tuple element has a name, then the name is part of the type: 
 
 var someTuple = (top: 10, bottom: 12) // someTuple is of type (top: Int, bottom: Int) someTuple = (top: 4, bottom: 42) // OK: names match someTuple = (9, 99) // OK: names are output someTuple = (left: 5, right: 5) // Error: names do not match 
 
 All tuple types contain two or more types, except for Void, which is a type alias for the empty tuple type, (). 
 
 Tuple type grammar 
 
 tuple-type →  (  tuple-type-body  opt   )  tuple-type-element-list → tuple-type-element | tuple-type-element  ,  tuple-type-element-list tuple-type-element → element-name , type-annotation , | type element-name → identifier 
 
 Function type 
 
 A function type is the type of a function, method, or closure and consists of a parameter and a return type separated by an arrow (->): 
 
 parameter type -> return type 
 
 Because  parameter type  and  return type  can be tuple types, function types support functions and methods that take multiple parameters and return multiple values. 
 
 A function type parameter () -> T (where T is an arbitrary type) can use the autoclosure attribute to implicitly create a closure for its calls. This provides a syntactically convenient way to defer expression evaluation, without having to write an explicit closure when calling the function. Read more about autoclosure in the section Autoclosures. 
 
 Function types can have a parameter with a variable number of arguments (variable). Syntactically, such a parameter consists of the base type name immediately followed by an ellipsis (...), as in Int... . A variant parameter is treated as an array containing elements of the base type. For example, the variable parameter Int... is treated as [Int]. Learn more about Variable Parameters. 
 
 To specify an In-Out parameter, prefix the parameter type with the inout keyword. You cannot designate a variadic parameter or return type with the inout keyword. In-Out parameters are discussed in more detail in the Through parameters section. 
 
 The argument names are not part of the corresponding function type: 
 
 func someFunction(left: Int, right: Int) {} func anotherFunction(left: Int, right: Int) {} func functionWithDifferentLabels(top: Int, bottom: Int) {} var f = someFunction // The type of f is (Int, Int) -> Void, not (left: Int, right: Int) -> Void. f = anotherFunction // OK f = functionWithDifferentLabels // OK func functionWithDifferentArgumentTypes(left: Int, right: String) {} f = functionWithDifferentArgumentTypes // Error func functionWithDifferentNumberOfArguments(left: Int, right: Int, top: Int) {} f = functionWithDifferentNumberOfArguments // Error 
 
 Because the Labels arguments are not part of the function type, you omit them when writing the function type. 
 
 var operation: (lhs: Int, rhs: Int) -> Int // Error var operation: (_ lhs: Int, _ rhs: Int) -> Int // OK var operation: (Int, Int) -> Int // OK 
 
 If a function type includes more than one arrow (->), the function types are grouped from right to left. For example, the function type Int -> Int -> Int is understood as Int -> (Int -> Int), that is, a function that takes an Int and returns another function that takes and returns an Int. 
 
 Function types that can throw an error should be marked with the throws keyword, and function types that can rethrow an error should be marked with the rethrows keyword. The throws keyword is part of the function type, and non-throwing functions are subclasses of throwing functions. As a result, you can use a non-generating function in the same place as a generating one. Throw and rethrow functions are described in "Thrower Functions and Methods" and "Rethrower Methods and Functions". 
 
 Restrictions for non-escaping closures 
 
 A parameter that is a non-collected function cannot be stored in a property, variable, or constant of type Any, as this may allow the value to be inferred. 
 
 A parameter that is not an escaping function cannot be passed as an argument to another parameter of an unassembled function. This limitation helps Swift perform more memory collision checks at compile time rather than at run time. For example: 
 
 let external: (() -> Void) -> Void = { _ in () } func takesTwoFunctions(first: (() -> Void) -> Void, second: (() -> Void) -> Void) { first { first {} } // Error second { second {} } // Error first { second {} } // Error second { first {} } // Error first { outer {} } // OK external { first {} } // OK } 
 
 In the code above, both parameters that take the values ​​TwoFunctions (first: second:) are functions. None of the parameters are marked as @escaping, so they are both not shown in the result. 
 
 The four function calls marked "Error" in the example above cause compiler errors. Because the first and second parameters are non-escaping functions, they cannot be passed as arguments to another parameter of a non-escaping function. In contrast, two function calls marked "OK" do not cause compiler errors. These function calls do not violate the constraint because outer is not one of the parameters of takeTwoFunctions(first: second : ). 
 
 If you need to avoid this limitation, mark one of the parameters as escaping, or temporarily convert one of the function parameters to an escaping function using the withoutActuallyEscaping(_:do:) function. For information on avoiding a memory access conflict, see Storage Security.   )  function-type-argument-list → function-type-argument | function-type-argument  ,  function-type-argument-list function-type-argument → attributes  opt   inout   opt  type | argument-label type-annotation argument-label → identifier 

Array types

The Swift language provides the following syntactic sugar for the Swift standard library type Array :

  [  type  ]  

In other words, the following two declarations are equivalent:

 let someArray: Array = ["Alex", "Brian", "Dave"] let someArray: [String] = ["Alex", "Brian", "Dave"] 

In both cases, the someArray constant is declared as an array of strings. Array elements can be accessed via indexing by specifying a valid index value in square brackets: someArray[0] refers to the element at index 0, "Alex".

You can create multidimensional arrays by layering pairs of square brackets, where the element's base type name is contained within the innermost pair of square brackets. For example, you can create a three-dimensional array of integers using three sets of square brackets:

 var array3D: [[[Int]]] = [[[1, 2], [3, 4]], [[5, 6], [7, 8]]] 

array, the leftmost subscript index refers to the element at that index in the bottommost array. The next subscript index on the right side refers to the element at that index in the nested array at the previous level. And so on. This means that in the example above, array3D[0] refers to [[1, 2], [3, 4]], array3D[0][1] refers to [3, 4], and array3D[0][ 1][1] refers to value 4.

For more information about the standard Array type of the Swift library, see Arrays.

Array type grammar

 array-type →  [  type  ]  

Dictionary type

The Swift language provides the following syntactic sugar for the Dictionary type of the Swift standard library: 90 typekey value: 90 typekey: ]

In other words, the following two declarations are equivalent:

 let someDictionary: [String: Int] = ["Alex": 31, "Paul": 39] let someDictionary: Dictionary = ["Alex": 31, "Paul": 39] 

In both cases, the someDictionary constant is declared as a dictionary with strings as keys and integers as values.

Dictionary values ​​can be accessed via indexing by specifying the corresponding key in square brackets: someDictionary["Alex"] refers to the value associated with the key "Alex". The subscript returns an optional value of the dictionary value type. If the specified key is not in the dictionary, the subscript returns nil.

The underlying key type of the dictionary must conform to the Hashable protocol of the Swift standard library.

See Dictionaries for details.

Dictionary-type grammar

  dictionary-type  → [  type  :  type  ] 

Optional type

The Swift language defines a postfix ? as syntactic sugar for the named type Optional defined in the Swift standard library. In other words, the following two declarations are equivalent:

 var optionalInteger: Int? var optionalInteger: Optional 

In both cases, the variable optionalInteger is declared to be of type optional Int. Note that no spaces should appear between the type name and ?.

The Optional type is an enumeration with two cases, None and Some(Wrapped), which are used to represent values ​​that may or may not be present. Any type can be explicitly declared (or implicitly converted) to be an optional type. If you do not provide an initial value when declaring an optional variable or property, its value is automatically set to nil.

If an instance of an optional type contains a value, you can access that value using the postfix operator !, as follows:

 optionalInteger = 42 optionalInteger! // 42 

Using the ! to extract an optional that has a value of nil results in a run-time error.

You can also use optional chaining and optional chaining to perform an operation in an optional expression. If the value is nil, the operation is not performed and therefore there will be no runtime error.

See Options for more information.

Optional type grammar

 optional-type → type  ? as syntactic sugar for the named type ImplicitlyUnwrappedOptional defined in the Swift standard library. In other words, the following two declarations are equivalent: 
 
 var implicitlyUnwrappedString: String! var explicitlyUnwrappedString: Optional 
 
 Note that no spaces should appear between the type name and !. 
 
 Because implicit extraction changes the meaning of a declaration that contains a type, optional types that are nested within a tuple or generic type, such as a dictionary or array element, cannot be designated as implicitly extracted. For example: 
 
 let tupleOfImplicitlyUnwrappedElements: (Int!, Int!) // Error let implicitlyUnwrappedTuple: (Int, Int)! // OK let arrayOfImplicitlyUnwrappedElements: [Int!] // Error let implicitlyUnwrappedArray: [Int]! // OK 
 
 Since implicitly extracted optionals are of the same type Optional, you can use implicitly extracted optionals in the same places in your code where you can use optionals. For example, you can assign the values ​​of implicitly retrieved optionals to variables, constants, and optional properties, and vice versa. 
 
 As with optionals, if you do not provide an initial value when declaring an implicitly unwrapped optional variable or property, its value is automatically set to nil. 
 
 Since the value of an implicitly extracted optional is automatically unboxed when you use it, there is no need to use the ! to expand it. However, if you try to use an implicitly unwrapped optional that has a value of nil, you will get a runtime error. 
 
 Use optional chaining to conditionally perform an operation on an implicitly unpacked optional expression. If the value is nil, the operation will not be performed and therefore there will be no runtime error. 
 
 See Implicitly Extracted Optionals for more information. 
 
 Implicitly-unwrapped-optional-type grammar 
 
 implicitly-unwrapped-optional-type→type  ! The protocol composition type can be used in an annotation type and in generic type parameters. 
 
 Protocol composition type is as follows: 
 
 Protocol 1 & Protocol 2 
 
 The protocol composition type allows you to specify a value whose type conforms to the requirements of multiple protocols without having to explicitly define a new, named protocol that inherits from each protocol that you want the type to conform to. For example, specifying the protocol composition type ProtocolA & ProtocolB & ProtocolC is just as efficient as defining a new protocol that inherits from ProtocolA, ProtocolB, and ProtocolC, but without the need for a new name. You can also use SuperClass & ProtocolA instead of defining a new protocol that is a subclass of SuperClass and conforms to ProtocolA. 
 
 Each element in the protocol composition list must be (this list can have only one class): 
 
 
 class name 
 
 protocol name 
 
 A type alias where the inner type is either a protocol composition, the protocol itself, or a class. 
 
 
 When a protocol composition contains type aliases, it is possible that the same protocol may appear more than once. In such cases, protocol repetitions are ignored. For example, the definition of PQR in the code below is similar to P&Q&R.0005 
 typealias PQ=P&Q typealias PQR = PQ & Q & R 
 
 Protocol composition type grammar 
 
 protocol-composition-type → protocol-identifier  &  protocol-composition-continuation protocol-composition-continuation → protocol-identifier | protocol-composition-type protocol-identifier → type-identifier 
 
 Metatype type 
 
 A metatype type refers to a type of any type, including class types, construct types, enumeration types, and protocol types. 
 
 The metatype of a class, structure, or enumeration type is the name of that type followed by .Type. The metatype of a protocol type is not a concrete type that corresponds to a protocol at run time - it is the name of that protocol followed by .Protocol. For example, the class type metatype of SomeClass is SomeClass.Type and the protocol metatype of SomeProtocol is SomeProtocol.Protocol. 
 
 You can use the self postfix expression to access a type as a value. For example, SomeClass.self returns SomeClass itself, not an instance of SomeClass. And SomeProtocol.self returns SomeProtocol itself, not an instance of the type that SomeProtocol matches at task time. You can use the type(of:) function with a type instance to access a dynamic type identification instance at runtime, as a value, as shown in the following example:0005 
 class SomeBaseClass { class func printClassName() { print("SomeBaseClass") } } class SomeSubClass: SomeBaseClass { override class func printClassName() { print("SomeSubClass") } } let someInstance: SomeBaseClass = SomeSubClass() // someInstance has a compile-time type of SomeBaseClass, // at runtime, the type of someInstance is SomeSubClass type(of: someInstance). printClassName() // Print "SomeSubClass" 
 
 For more information, see type (of: ) in the Swift standard library. 
 
 Use an initializer expression to create an instance of a type from the type value of this metatype. For instances of a class, the initializer that is called must be marked with the keyword required, or the entire class must be marked with the keyword final. 
 
 class AnotherSubClass: SomeBaseClass { let string: String required init(string: String) { self.string = string } override class func printClassName() { print("AnotherSubClass") } } let metatype: AnotherSubClass.Type = AnotherSubClass.self let anotherInstance = metatype.init(string: "some string") 
 
 Metatype grammar 
 
 metatype-type → type  .    Type   | type  .    Protocol   
 
 Type inheritance 
 
 Type inheritance is used to specify from which class a named type inherits and which protocols it conforms to. Type inheritance is also used to specify class requirements over a protocol. Type inheritance begins with a colon (:) followed by either class requirements or a list of type identifiers, or both. 
 
 Class types can inherit from one superclass and conform to any number of protocols. When defining a class, the name of the superclass must appear at the beginning of the list of type identifiers, followed by the protocols that the class must conform to. If a class does not inherit from another class, the list may start with the protocol instead. See Inheritance for details. 
 
 Other named types can only inherit or conform to the protocol list. Protocol types can inherit from any number of other protocols. When a protocol type inherits from other protocols, and requirements from all protocols are collected together, and any type that inherits from the current protocol must meet all of these requirements. As discussed earlier, you can include the class keyword as the first item in an inheritance type clause to mark a protocol declaration with a class requirement. 
 
 The type inheritance in an enum definition can be either a list of protocols, or in the case of an enum that assigns initial values ​​to its cases, there can be a single, named type that defines the type of those initial values. More Initial values. 
 
 Grammar of type inheritance 
 
 type-inheritance-clause →  :  class-requirement0033 :  type-inheritance-list type-inheritance-list → type-identifier | type-identifier  ,  type-inheritance-list class-requirement →   class   
 
 Type inference 
 
 Swift uses type inference extensively, which allows you to omit the type or part of the type of many variables and expressions in your code. For example, instead of writing var x: Int = 0, you can write var x = 0, omitting the type entirely, the compiler correctly understands that x is an Int value. Also, you can omit part of the type when the full type can be inferred from context. For example, when you write let dict: Dictionary = ["A": 1], the compiler infers that dict is of type Dictionary. 
 
 In both examples above, type information is passed from the leaves of the expression tree to its root. That is, for the type x in var x: Int = 0, the type 0 is checked first, and then this information is passed to the root (variable x). 
 
 In Swift, type information can also flow in the opposite direction: from the root to the leaves. In the following example, the explicit annotation type (:Float) on the constant eFloat causes the numeric constant 2.71828 to have the inferred type Float instead of Double. 
 
 let e = 2.71828 // The inferred type of e is Double. let eFloat: Float = 2.71828 // The inferred type of eFloat is Float. 
 
 Type inference in Swift works at the level of a single expression or statement. This means that all the information needed to infer a missing type or part of a type in an expression must be available from the type checking of the expression or one of its subexpressions. 
 
 
 
 If you find a mistake, please highlight the text and press  Ctrl+Enter  . 
 
 Types of Software Testing - Complete List 
 
 Types of Testing 
 
 In this section, we will describe the different types of software testing. Different types of software testing are conducted to achieve different goals when testing a software application. You can also read about the different software testing methods that can be associated with different types of software testing. Our   Software Testing courses in Minsk will help you become an expert in this field. 
 
 
 Ad-hoc testing 
 
 
 
 This type of software testing is informal and unstructured and can be performed by any interested person, without reference to any test scripts or test documents. 
 
 Ad-hoc tester has a good understanding of the application's workflows while trying to find defects and crack the software. Special checks are designed to detect defects that were not found in existing test cases. 
 
 Acceptance testing 
 
 
 
 Acceptance testing is a formal type of software testing that is performed by the end user when the developers have provided the requested services. The purpose of this testing is to verify that the software meets the customer's business requirements and the requirements presented earlier. Acceptance testing is usually documented at the beginning of work (in agile) and helps testers and developers to improve their knowledge and skills in this area. 
 
 
 What is acceptance testing in Agile? 
 
 Accessibility testing 
 
 In accessibility testing, the purpose of testing is to determine whether the content of a website can be easily accessed by people with disabilities. Includes various checks such as color and contrast check (for people with color blindness), font size for the visually impaired, clear and concise text that is easy to read and understand. 
 
 Agile testing 
 
 
 
 Agile Testing is a type of software testing that takes into account the agile approach and methods of software development. In an Agile development environment, testing is an integral part of software development and is done in parallel with coding. Agile testing allows you to incrementally write code and test it. 
 
 API testing 
 
 API testing is a type of testing that is similar to unit testing. Each of the APIs is tested against the API specification. API testing is mostly done by a team of testers. Requires an understanding of both API functionality and good programming skills. 
 
 Automated Testing 
 
 This is a testing approach that uses test tools and/or programming to run test cases using software or specially designed test utilities. Most automated tools are recording and playback tools, but there are tools that require extensive scripting or programming to automate test scripts. 
 
 Pair testing 
 
 In other words, “pair testing” is black box testing and a testing method in which a pair of inputs are tested for each input, which helps to test the operation of the software as expected with all possible combinations of inputs. 
 
 Beta testing 
 
 This is a formal type of software testing that is performed by end users before software is released or distributed to users. Successful completion of beta testing signifies the user's acceptance of the software. 
 
 Black Box Testing 
 
 
 
 Black box testing is a type of software testing where testers are not required to know the coding or internal structure of the software. The "black box" testing method is based on testing the software with different inputs and comparing the results with the expected ones. 
 
 Backward compatibility testing 
 
 A type of software testing that is performed to verify that a newer version of software can successfully run on top of a previous version of software and that the new version of software works well with the table structure, data structures, and files created by the previous one. software version. 
 
 Boundary value testing 
 
 Boundary value testing is a type of testing based on the concept of "error aggregation at boundaries". Testing is carried out by a method of thorough testing of defects in boundary values. If the field accepts a value from 1 to 100, then testing is performed for the values ​​0, 1, 2, 99, 100, and 101. 
 
 
 
 Big bang testing method 
 
 This is one of the integration testing approaches. The big bang testing method is based on the fact that all or most of the modules are developed and then connected together. 
 
 Bottom-Up Integration Testing (Bottom-Up Testing) 
 
 Bottom-Up Integration Testing is an integration testing method in which testing starts with smaller parts or subsystems of a system, and ends with full coverage of the entire software system. Bottom-up integration testing starts with small pieces of software and eventually scales in terms of size, complexity, and completeness. 
 
 Branch test 
 
 Is a white box testing method for developing test scripts to test the code for each branch condition. Used during unit testing. 
 
 Browser Compatibility Testing 
 
 
 
 This is one of the subtypes of compatibility testing performed by the testing team. Browser compatibility testing is performed on web applications in combination with different browsers and operating systems. 
 
 Compatibility test 
 
 Compatibility testing is a type of test performed by a team of testers. Compatibility testing checks if the software can be run on different hardware, operating system, databases, web servers, application servers, hardware peripherals, emulators, different configurations, processor, different browsers and different browser versions, etc. 
 
 
 
 Component testing 
 
 This type of software testing is performed by developers. Component testing is done after unit testing is completed. Component testing involves testing a group of units as code together as a whole rather than testing individual functions and methods. 
 
 Condition Coverage Testing 
 
 Condition Coverage Testing is a testing technique used during unit testing where the developer tests all conditions such as if, if-else, case, etc. in the code unit being tested. 
 
 Dynamic testing 
 
 
 
 Testing can be done by static testing and dynamic testing. Dynamic testing is an approach to testing where testing can only be done when the code is checked out. 
 
 Solution coverage testing 
 
 This is a testing technique that is used in unit testing. The purpose of decision coverage testing is to implement and test every decision block in the code, for example. If, if-else, case. 
 
 End-to-End Testing 
 
 End-to-End Testing is performed by a team of testers and the focus is on testing end-to-end flows. Right from order creation to reporting or order creation to product return, etc. and verification. End-to-end testing is usually aimed at simulating real life scenarios and their implementation. End-to-end testing involves testing the flow of information between applications. 
 
 Exploratory testing 
 
 
 
 Exploratory testing is an informal form of testing done to study software while looking for bugs or application behaviors that don't seem obvious. Testing is usually done by testers, but can be done by other stakeholders as well as business analysts, developers, end users, etc. who are interested in learning about the features of the software while at the same time looking for bugs or behavior that doesn't seem obvious. 
 
 Equivalent splitting 
 
 Equivalent splitting is also called equivalence splitting. Classification is a software testing technique, not a type of testing in and of itself. Equivalent split testing is used in black box and gray box tests. Equivalent partitioning classifies the test data into equivalence classes as positive equivalence classes and negative equivalence classes, a classification that ensures that both positive and negative conditions are tested. 
 
 Functional testing 
 
 Functional testing is a formal type of testing performed by testers. Functional testing focuses on testing software based on the state document, cases, and requirements. Functional testing is a type of "black box" testing and does not require knowledge of the inner workings of the software, unlike "white box" testing. 
 
 Fuzz testing 
 
 Fuzz testing or fuzzing is a software testing technique that involves testing with unexpected or random inputs. The software is tested for bugs or error messages that appear due to data entry errors. 
 
 GUI Testing 
 
 
 
 This type of software testing focuses on testing the software's graphical user interface, which must meet the requirements specified in GUI layouts and detailed documents. For example, checking the length and capacity of the input fields specified in the form, the type of the input field provided. Some form fields may appear as a drop-down list or a set of radio buttons. Thus, GUI testing provides the GUI elements of the software in accordance with the approved GUI layouts, detailed design documents, and functional requirements. Most functional test automation tools work with GUI recording and playback capabilities. This speeds up script writing and increases script maintenance costs. 
 
 Glass box testing 
 
 Glass box testing is another name for white box testing. Glass box testing is a testing method that involves testing individual statements, functions, etc. Unit testing is one of the glass box testing methods. 
 
 Gorilla testing (chaotic testing) 
 
 This type of software testing is performed by a team of software testers. The goal of Gorilla Testing is to use one or more features fully or exhaustively if multiple people experience the same features. 
 
 Favorable Path Testing 
 
 Also known as Golden Path testing, this type of testing focuses on successfully passing tests that do not lead to errors. 
 
 Integration testing 
 
 
 
 Integration testing is one of the most common and important types of software testing. Once individual units or components have been verified as working by the developers, a test team will run tests that will test connectivity between those units/components or multiple devices/components. There are various approaches to integration testing, namely: top-down integration testing, bottom-up integration testing, and a combination of these two Sand witch tests. 
 
 Interface testing 
 
 Interface testing is required when software provides support for one or more interfaces, such as a "Graphical User Interface", "Command Line Interface", or "Application Programming Interface", to interact with its users or other software. Interfaces serve as a medium for software to accept input from the user and provide output to the user. The approach to interface testing depends on the type of interface being tested, such as GUI or API or CLI. 
 
 Internationalization Testing 
 
 Internationalization Testing is a type of testing that is performed by a team of software testers to check how well the software can support internationalization, i.e. using different languages, different character sets, double-byte characters, etc. For example: Gmail is a web application that people use to work with different languages, single or multi-byte character sets. 
 
 Keyword testing 
 
 Keyword-driven testing is more of an automated approach to software testing than a type of testing itself. Keyword based testing is known as action based testing or table based testing. 
 
 Load testing 
 
 
 
 Load testing is a type of non-functional testing. Load testing is carried out to check the behavior of the software under normal and over-peak load conditions. Load testing is usually performed using automated testing tools. Load testing is designed to find vulnerabilities or problems that prevent software from performing its tasks in accordance with its maximum workloads. 
 
 Localization testing 
 
 Localization testing is a type of software testing performed by software testers, in which the software is expected to adapt to a specific language, it must support a specific language, accept input in that specific locale, display a font, time , date, currency, etc. related to a particular language. For example, many web applications allow you to select a language such as English, French, German, or Japanese. Therefore, if the locale is defined or configured in the software configuration, the software is expected to work as expected with the given language/locale. 
 
 Negative testing 
 
 This kind of software testing approach that shows how software behaves when it is broken. In other words, it is a functional and non-functional test that is designed to break the software by entering incorrect data such as an incorrect date, time or string, or by uploading a binary file when a text file is supposed to be loaded, or by entering a huge text string for input fields, etc. This is also a positive test for a bug. 
 
 Non-functional test 
 
 Most software products are designed to meet functional and non-functional requirements. Non-functional requirements: performance, usability, localization, etc. There are many types of testing, such as compatibility testing, localization, usability testing, which are performed to test non-functional requirements. 
 
 Pair testing 
 
 
 
 is a software testing technique that can be performed by software testers, developers, or business analysts. As the name suggests, two people work together, one doing the testing and the other supervising and recording the test results. Pair testing can also be performed in a tester-developer combination, tester-business analyst, or analyst-business developer combination. Bringing testers and developers together in pair testing helps you find defects faster, determine the root cause, fix, and test the fix. 
 
 Performance testing 
 
 This is a type of software testing and part of the engineering activity that is performed to test certain software quality attributes such as stability, reliability, availability. Performance testing is performed by the development team. Unlike functional testing, performance testing is performed to test non-functional requirements. Benchmarking tests how well the software performs under expected and maximum workloads. There are various variants or sub-types of performance such as load testing, stress testing, volume testing, endurance testing, and configuration testing. 
 
 Security Testing 
 
 This is a type of security testing. Penetration testing is performed to test how protected software and its environment (hardware, operating system, and network) are attacked by an external or internal attacker. The intruder can be a human/hacker or malware. Pentest uses brute force or exploitation techniques to gain access to software or data or hardware in order to expose methods of theft, manipulation or corruption of data, software files or configuration. Security testing is a way of ethical hacking: an experienced security tester will use the same methods and tools as a hacker, but the tester's intention is to identify a vulnerability and fix it before a real hacker or malware exploits the vulnerability for their own purposes. 
 
 Regression testing 
 
 is a type of software testing that is performed by software testers as functional regression tests and by developers as unit regression tests. The purpose of regression tests is to identify defects that have been introduced to fix defects or introduce new features. Regression tests are ideal options for test automation. 
 
 Retest 
 
 
 
 This is a type of retest that is performed by software testers as part of a defect fix review. For example, a tester checks a defect fix. Once the tester verifies the defect fix as a success, the tester will then retest or verify the same feature by running the test cases that were previously unsuccessful. 
 
 Risk Based Testing 
 
 This is a type of software testing and a different approach to software testing. In risk-based testing, the requirements and functionality of the software under test are prioritized as critical, high, medium, and low. In this approach, all critical and high priority cases are tested, followed by medium ones. Low priority or low risk functionality is tested at the end or may not be tested at all, depending on the time frame. 
 
 Smoke testing 
 
 This is a type of testing that is performed by software testers to check whether a new build provided by the development team is sufficiently stable, i.e. whether the main functions work as expected for conducting further or detailed testing. Smoke testing is designed to detect "show stopper" defects that may prevent the application from being tested in detail. Smoke testing is also known as build verification testing. 
 
 Security testing 
 
 
 
 This is a type of software testing performed by a specialized group of software testers. The purpose of security testing is to ensure that software is protected from external or internal threats from humans and malware. Security testing basically checks how good the software authorization mechanism is, how strong the authentication is, how the software maintains data confidentiality, how the software maintains data integrity, what is the availability of the software in case of hackers and malware attacks on the software. Security testing requires good knowledge of applications, technologies, networks, security testing tools. With the proliferation of web applications, security testing has become more important than ever. 
 
 Health Testing 
 
 This is a type of testing that is performed mainly by testers, but also in some projects by developers. Health testing is a quick assessment of the software, environment, network, external systems, and checking the software environment for stability sufficient to start comprehensive testing. Performance tests are narrow and in most cases not documented. 
 
 
 
 Scalability test 
 
 Represents a non-functional test designed to test one of the software quality attributes, i.e. "Scalability". The scalability test is not focused on just one or a few features of the software, and not on the performance of the software as a whole. Scalability testing is usually done by the development team. The purpose of scalability testing is to test the software's ability to grow with more users, increase transactions, increase database size, etc. It is not necessary that software performance increase with increasing hardware configuration. Scalability tests help you figure out how much more workload the software can support as you expand your user base, transactions, storage, etc. 
 
 Stability test 
 
 Is a non-functional test designed to test one of the software quality attributes, i.e. "Stability". Stability testing focuses on testing stable software when it is subjected to loads at acceptable levels, peak loads, loads generated at peaks with a lot of data being processed. Scalability testing will include performing different kinds of performance tests such as load testing, stress testing, spike testing, endurance testing. 
 
 Static testing 
 
 
 
 is a form of testing that uses step-by-step guides to evaluate the correctness of results. In static testing, the program code is not executed, but revised for syntax, commenting, naming convention, function/method size, etc. Static testing usually has checklists against which results are judged. Static testing can be used to test requirements, designs, and test cases using approaches such as reviews or walkthroughs. 
 
 Stress Testing 
 
 This is a type of performance testing in which software is subjected to peak loads to see how the software will perform under peak load. Stress testing also checks the behavior of the software when there is a lack of resources such as processor, memory, network bandwidth, disk space, etc. Stress testing allows you to check such a quality attribute as reliability. 
 
 System test 
 
 Includes several types of software testing that will test the software as a whole (software, hardware and network) in accordance with the requirements for which it was created. Various kinds of tests are performed to complete system testing (GUI testing, functional testing, regression testing, smoke testing, load testing, stress testing, security testing, stress testing, ad-hoc testing, etc.). 
 
 Load Testing 
 
 This is a type of performance testing where software is subjected to stress for a significant period of time, endurance testing can continue for several days or even several weeks. Endurance testing is a type of testing that is carried out to identify bugs that degenerate the performance of the software with continued use. Endurance testing is widely applied to electronic devices that are expected to operate continuously for days or months or years without a reset. With the growing number of web applications, endurance testing has become very important, as the availability of web applications is critical to business support and success. 
 
 System Integration Testing 
 
 Known as SIT (shortly), it is a type of testing performed by a software test team. As the name suggests, system integration testing focuses on checking for errors related to integration between various applications, services, third-party applications, etc. SIT checks end-to-end scenarios that require interoperability software (Send or receive data) with other apps up, down, with third party apps. 
 
 Unit testing 
 
 
 
 This is a type of testing that is performed by software developers. Unit testing follows the white box testing method where the developer will test units of the source code like statements, branches, functions, methods, interface in OOP (Object Oriented Programming). Unit testing usually includes driver development. Unit tests are ideal options for automation. Automated tests can be run as unit regression tests for new versions or new versions of the software. There are many useful frameworks like Junit, Nunit, etc. that can make unit testing more efficient. 
 
 Usability testing 
 
 This is a type of software testing that is performed to understand how user friendly the software is. The purpose of usability testing is to allow end users to use the software, observe their behavior, emotional response (whether users liked the use of the software or emphasized its use, etc.) and collect their feedback on how the software can be more user friendly. 
 
 User Acceptance Testing 
 
 User Acceptance Testing is a must for any project. It is performed by the clients/end users of the software. Acceptance testing allows the customer's experts to test the software against real business scenarios or real life scenarios and verify that the software meets their business requirements. 
 
 Volume testing 
 
 This is a non-functional type of testing performed by a performance engineering team. Volume testing is one type of performance testing. Volume testing is performed to test the software for reliability when dealing with different sizes of data that are received and processed by the software. For example, if you are going to test Microsoft word, then the volume test would be to see if MS Word can open, save and work with files of different sizes (from 10 to 100 MB). 
 
 Vulnerability testing 
 
 
 
 Includes the identification of software, hardware or network vulnerabilities that can be exploited by hackers and other malware similar to viruses or worms. Vulnerability testing is key to ensuring software security and availability. With the rise of hackers and malware, vulnerability testing is critical to business success. 
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