Comprehensive list of different types of Testing and Test Jargons

31 March, 2014
Acceptance Testing: Testing conducted to enable a user/customer to determine whether to accept a software product. Normally performed to validate the software meets a set of agreed acceptance criteria.

Accessibility Testing: Verifying a product is accessible to the people having disabilities (deaf, blind, mentally disabled etc.).

Ad Hoc Testing: Similar to exploratory testing, but often taken to mean that the testers have significant understanding of the software before testing it.

Agile Testing: Testing practice for projects using agile methodologies, treating development as the customer of testing and emphasizing a test-first design paradigm.

Alpha testing: Testing of an application when development is nearing completion; minor design changes may still be made as a result of such testing. Typically done by end-users or others, not by programmers or testers.


Application Programming Interface (API): A formalized set of software calls and routines that can be referenced by an application program in order to access supporting system or network services.

Automated Software Quality (ASQ): The use of software tools, such as automated testing tools, to improve software quality.

Backus-Naur Form: A Meta language used to formally describe the syntax of a language.

Basic Block: A sequence of one or more consecutive, executable statements containing no branches.

Basis Path Testing: A white box test case design technique that uses the algorithmic flow of the program to design tests.

Basis Set: The set of tests derived using basis path testing.

Baseline: The point at which some deliverable produced during the software engineering process is put under formal change control.

Beta Testing: Testing when development and testing are essentially completed and final bugs and problems need to be found before final release. Typically done by end-users or others, not by programmers or testers.

Binary Portability Testing: Testing an executable application for portability across system platforms and environments, usually for conformation to an ABI specification.

Black Box Testing: Testing based on an analysis of the specification of a piece of software without reference to its internal workings. The goal is to test how well the component conforms to the published requirements for the component.

Bottom Up Testing: An approach to integration testing where the lowest level components are tested first, then used to facilitate the testing of higher level components. The process is repeated until the component at the top of the hierarchy is tested.

Boundary Testing: Test which focus on the boundary or limit conditions of the software being tested. (Some of these tests are stress tests).

Bug: A fault in a program which causes the program to perform in an unintended or unanticipated manner.

Boundary Value Analysis: BVA is similar to Equivalence Partitioning but focuses on "corner cases" or values that are usually out of range as defined by the specification. It means that if a function expects all values in range of negative 100 to positive 1000, test inputs would include negative 101 and positive 1001.

Branch Testing: Testing in which all branches in the program source code are tested at least once.

Breadth Testing: A test suite that exercises the full functionality of a product but does not test features in detail.

Capture/Replay Tool: A test tool that records test input as it is sent to the software under test. The input cases stored can then be used to reproduce the test at a later time. Most commonly applied to GUI test tools.

CMM: The Capability Maturity Model for Software (CMM or SW-CMM) is a model for judging the maturity of the software processes of an organization and for identifying the key practices that are required to increase the maturity of these processes.

Cause Effect Graph: A graphical representation of inputs and the associated outputs effects which can be used to design test cases.

Code Complete: Phase of development where functionality is implemented in entirety; bug fixes are all that are left. All functions found in the Functional Specifications have been implemented.

Code Coverage: An analysis method that determines which parts of the software have been executed (covered) by the test case suite and which parts have not been executed and therefore may require additional attention.

Code Inspection: A formal testing technique where the programmer reviews source code with a group who ask questions analyzing the program logic, analyzing the code with respect to a checklist of historically common programming errors, and analyzing its compliance with coding standards.

Code Walkthrough: A formal testing technique where source code is traced by a group with a small set of test cases, while the state of program variables is manually monitored, to analyze the programmer's logic and assumptions.

Compatibility Testing: Testing whether software is compatible with other elements of a system with which it should operate, e.g. browsers, Operating Systems, or hardware.

Component:A minimal software item for which a separate specification is available.

Component Testing: See Unit Testing.

Concurrency Testing: Multi-user testing geared towards determining the effects of accessing the same application code, module or database records. Identifies and measures the level of locking, deadlocking and use of single-threaded code and locking semaphores.

Conformance Testing: The process of testing that an implementation conforms to the specification on which it is based. Usually applied to testing conformance to a formal standard.

Context Driven Testing: The context-driven testing is flavor of Agile Testing that advocates continuous and creative evaluation of testing opportunities in light of the potential information revealed and the value of that information to the organization right now or it can be defined as testing driven by an understanding of the environment, culture, and intended use of software. For example, the testing approach for life-critical medical equipment software would be completely different than that for a low-cost computer game.

Conversion Testing: Testing of programs or procedures used to convert data from existing systems for use in replacement systems.

Data Flow Diagram: A modeling notation that represents a functional decomposition of a system.

Data Driven Testing: Testing in which the action of a test case is parameterized by externally defined data values, maintained as a file or spreadsheet. A common technique in Automated Testing.

Dependency Testing: Examines an application's requirements for pre-existing software, initial states and configuration in order to maintain proper functionality.

Depth Testing: A test that exercises a feature of a product in full detail.

Dynamic Testing: Testing software through executing it. See also Static Testing.

Emulator: A device, computer program, or system that accepts the same inputs and produces the same outputs as a given system.

Endurance Testing: Checks for memory leaks or other problems that may occur with prolonged execution.

End-to-End testing: Testing a complete application environment in a situation that mimics real-world use, such as interacting with a database, using network communications, or interacting with other hardware, applications, or systems if appropriate.

Equivalence Class: A portion of a component's input or output domains for which the component's behavior is assumed to be the same from the component's specification.

Equivalence Partitioning: A test case design technique for a component in which test cases are designed to execute representatives from equivalence classes.

Exhaustive Testing: Testing which covers all combinations of input values and preconditions for an element of the software under test.

Exploratory testing: Often taken to mean a creative, informal software test that is not based on formal test plans or test cases; testers may be learning the software as they test it.

Failover Tests: Failover Tests verify of redundancy mechanisms while under load. For example, such testing determines what will happen if multiple web servers are being used under peak anticipate load, and one of them dies. Does the load balancer react quickly enough? Can the other web servers handle the sudden dumping of extra load? This sort of testing allows technicians to address problems in advance, in the comfort of a testing situation, rather than in the heat of a production outage.

Functional Decomposition: A technique used during planning, analysis and design; creates a functional hierarchy for the software.

Functional Specification: A document that describes in detail the characteristics of the product with regard to its intended features.

Functional Testing: See also Black Box Testing.
  • Testing the features and operational behavior of a product to ensure they correspond to its specifications.
  • Testing that ignores the internal mechanism of a system or component and focuses solely on the outputs generated in response to selected inputs and execution conditions.

Glass Box Testing: A synonym for White Box Testing.

Gorilla Testing: Testing one particular module, functionality heavily.

Gray Box Testing: A combination of Black Box and White Box testing methodologies: testing a piece of software against its specification but using some knowledge of its internal workings.

High Order Tests: Black-box tests conducted once the software has been integrated.

Incremental Integration testing: Continuous testing of an application as new functionality is added; requires that various aspects of an application's functionality be independent enough to work separately before all parts of the program are completed, or that test drivers be developed as needed; done by programmers or by testers.

Inspection: A group review quality improvement process for written material. It consists of two aspects; product (document itself) improvement and process improvement (of both document production and inspection).

Integration Testing: Testing of combined parts of an application to determine if they function together correctly. Usually performed after unit and functional testing. This type of testing is especially relevant to client/server and distributed systems.

Installation Testing: Confirms that the application under test recovers from expected or unexpected events without loss of data or functionality. Events can include shortage of disk space, unexpected loss of communication, or power out conditions.

Load Testing: Load Tests are end to end performance tests under anticipated production load. The primary objective of this test is to determine the response times for various time critical transactions and business processes and that they are within documented expectations (or Service Level Agreements - SLAs). The test also measures the capability of the application to function correctly under load, by measuring transaction pass/fail/error rates.
This is a major test, requiring substantial input from the business, so that anticipated activity can be accurately simulated in a test situation. If the project has a pilot in production then logs from the pilot can be used to generate ‘usage profiles’ that can be used as part of the testing process, and can even be used to ‘drive’ large portions of the Load Test.
Load testing must be executed on “today’s” production size database, and optionally with a “projected” database. If some database tables will be much larger in some months time, then Load testing should also be conducted against a projected database. It is important that such tests are repeatable as they may need to be executed several times in the first year of wide scale deployment, to ensure that new releases and changes in database size do not push response times beyond prescribed SLAs.

Localization Testing: This term refers to making software specifically designed for a specific locality.

Loop Testing: A white box testing technique that exercises program loops.

Metric: A standard of measurement. Software metrics are the statistics describing the structure or content of a program. A metric should be a real objective measurement of something such as number of bugs per lines of code.

Monkey Testing: Testing a system or an Application on the fly, i.e. just few tests here and there to ensure the system or an application does not crash out.

Mutation testing: A method for determining if a set of test data or test cases is useful, by deliberately introducing various code changes ('bugs') and retesting with the original test data/cases to determine if the 'bugs' are detected. Proper implementation requires large computational resources.

Network Sensitivity Tests: Network sensitivity tests are tests that set up scenarios of varying types of network activity (traffic, error rates...), and then measure the impact of that traffic on various applications that are bandwidth dependant. Very 'chatty' applications can appear to be more prone to response time degradation under certain conditions than other applications that actually use more bandwidth. For example, some applications may degrade to unacceptable levels of response time when a certain pattern of network traffic uses 50% of available bandwidth, while other applications are virtually un-changed in response time even with 85% of available bandwidth consumed elsewhere.
This is a particularly important test for deployment of a time critical application over a WAN.

Negative Testing: Testing aimed at showing software does not work. Also known as "test to fail".

N+1 Testing: A variation of Regression Testing. Testing conducted with multiple cycles in which errors found in test cycle N are resolved and the solution is retested in test cycle N+1. The cycles are typically repeated until the solution reaches a steady state and there are no errors. See also Regression Testing.

Path Testing: Testing in which all paths in the program source code are tested at least once.

Performance Testing: Testing conducted to evaluate the compliance of a system or component with specified performance requirements. Often this is performed using an automated test tool to simulate large number of users. Also know as "Load Testing".
Performance Tests are tests that determine end to end timing (benchmarking) of various time critical business processes and transactions, while the system is under low load, but with a production sized database. This sets ‘best possible’ performance expectation under a given configuration of infrastructure. It also highlights very early in the testing process if changes need to be made before load testing should be undertaken. For example, a customer search may take 15 seconds in a full sized database if indexes had not been applied correctly, or if an SQL 'hint' was incorporated in a statement that had been optimized with a much smaller database. Such performance testing would highlight such a slow customer search transaction, which could be remediate prior to a full end to end load test.

Positive Testing: Testing aimed at showing software works. Also known as "test to pass".

Protocol Tests: Protocol tests involve the mechanisms used in an application, rather than the applications themselves. For example, a protocol test of a web server may will involve a number of HTTP interactions that would typically occur if a web browser were to interact with a web server - but the test would not be done using a web browser. LoadRunner is usually used to drive load into a system using VUGen at a protocol level, so that a small number of computers (Load Generators) can be used to simulate many thousands of users.

Quality Assurance: All those planned or systematic actions necessary to provide adequate confidence that a product or service is of the type and quality needed and expected by the customer.

Quality Audit: A systematic and independent examination to determine whether quality activities and related results comply with planned arrangements and whether these arrangements are implemented effectively and are suitable to achieve objectives.

Quality Circle: A group of individuals with related interests that meet at regular intervals to consider problems or other matters related to the quality of outputs of a process and to the correction of problems or to the improvement of quality.

Quality Control: The operational techniques and the activities used to fulfill and verify requirements of quality.

Quality Management: That aspect of the overall management function that determines and implements the quality policy.

Quality Policy: The overall intentions and direction of an organization as regards quality as formally expressed by top management.

Quality System: The organizational structure, responsibilities, procedures, processes, and resources for implementing quality management.

Race Condition: A cause of concurrency problems. Multiple accesses to a shared resource, at least one of which is a write, with no mechanism used by either to moderate simultaneous access.

Ramp Testing: Continuously raising an input signal until the system breaks down.

Recovery Testing: Confirms that the program recovers from expected or unexpected events without loss of data or functionality. Events can include shortage of disk space, unexpected loss of communication, or power out conditions.

Regression Testing: Retesting a previously tested program following modification to ensure that faults have not been introduced or uncovered as a result of the changes made.

Release Candidate: A pre-release version, which contains the desired functionality of the final version, but which needs to be tested for bugs (which ideally should be removed before the final version is released).

Sanity Testing: Brief test of major functional elements of a piece of software to determine if it’s basically operational. See also Smoke Testing.

Scalability Testing: Performance testing focused on ensuring the application under test gracefully handles increases in work load.

Security Testing: Testing which confirms that the program can restrict access to authorized personnel and that the authorized personnel can access the functions available to their security level.

Smoke Testing: Typically an initial testing effort to determine if a new software version is performing well enough to accept it for a major testing effort. For example, if the new software is crashing systems every 5 minutes, bogging down systems to a crawl, or corrupting databases, the software may not be in a 'sane' enough condition to warrant further testing in its current state.

Soak Testing: Soak testing is running a system at high levels of load for prolonged periods of time. A soak test would normally execute several times more transactions in an entire day (or night) than would be expected in a busy day, to identify and performance problems that appear after a large number of transactions have been executed. Also, due to memory leaks and other defects, it is possible that a system may ‘stop’ working after a certain number of transactions have been processed. It is important to identify such situations in a test environment.

Sociability (sensitivity) Tests: Sensitivity analysis testing can determine impact of activities in one system on another related system. Such testing involves a mathematical approach to determine the impact that one system will have on another system. For example, web enabling a customer 'order status' facility may impact on performance of telemarketing screens that interrogate the same tables in the same database. The issue of web enabling can be that it is more successful than anticipated and can result in many more enquiries than originally envisioned, which loads the IT systems with more work than had been planned.

Static Analysis: Analysis of a program carried out without executing the program.

Static Analyzer: A tool that carries out static analysis.

Static Testing: Analysis of a program carried out without executing the program.

Storage Testing: Testing that verifies the program under test stores data files in the correct directories and that it reserves sufficient space to prevent unexpected termination resulting from lack of space. This is external storage as opposed to internal storage.

Stress Testing: Stress Tests determine the load under which a system fails, and how it fails. This is in contrast to Load Testing, which attempts to simulate anticipated load. It is important to know in advance if a ‘stress’ situation will result in a catastrophic system failure, or if everything just “goes really slow”. There are various varieties of Stress Tests, including spike, stepped and gradual ramp-up tests. Catastrophic failures require restarting various infrastructures and contribute to downtime, a stress-full environment for support staff and managers, as well as possible financial losses. This test is one of the most fundamental load and performance tests.

Structural Testing: Testing based on an analysis of internal workings and structure of a piece of software. See also White Box Testing.

System Testing: Testing that attempts to discover defects that are properties of the entire system rather than of its individual components. It’s a black-box type testing that is based on overall requirements specifications; covers all combined parts of a system.

Testability: The degree to which a system or component facilitates the establishment of test criteria and the performance of tests to determine whether those criteria have been met.

Testing:
  • The process of exercising software to verify that it satisfies specified requirements and to detect errors.
  • The process of analyzing a software item to detect the differences between existing and required conditions (that is, bugs), and to evaluate the features of the software item.
  • The process of operating a system or component under specified conditions, observing or recording the results, and making an evaluation of some aspect of the system or component.

Test Bed: An execution environment configured for testing. May consist of specific hardware, OS, network topology, configuration of the product under test, other application or system software, etc. The Test Plan for a project should enumerate the test beds(s) to be used.

Test Case:
  • Test Case is a commonly used term for a specific test. This is usually the smallest unit of testing. A Test Case will consist of information such as requirements testing, test steps, verification steps, prerequisites, outputs, test environment, etc.
  • A set of inputs, execution preconditions, and expected outcomes developed for a particular objective, such as to exercise a particular program path or to verify compliance with a specific requirement.

Test Driven Development: Testing methodology associated with Agile Programming in which every chunk of code is covered by unit tests, which must all pass all the time, in an effort to eliminate unit-level and regression bugs during development. Practitioners of TDD write a lot of tests, i.e. an equal number of lines of test code to the size of the production code.

Test Driver: A program or test tool used to execute a tests. Also known as a Test Harness.

Test Environment: The hardware and software environment in which tests will be run, and any other software with which the software under test interacts when under test including stubs and test drivers.

Test First Design: Test-first design is one of the mandatory practices of Extreme Programming (XP).It requires that programmers do not write any production code until they have first written a unit test.

Test Harness: A program or test tool used to execute a test. Also known as a Test Driver.

Test Plan: A document describing the scope, approach, resources, and schedule of intended testing activities. It identifies test items, the features to be tested, the testing tasks, who will do each task, and any risks requiring contingency planning.

Test Procedure: A document providing detailed instructions for the execution of one or more test cases.

Test Script: Commonly used to refer to the instructions for a particular test that will be carried out by an automated test tool.

Test Specification: A document specifying the test approach for a software feature or combination or features and the inputs, predicted results and execution conditions for the associated tests.

Test Suite: A collection of tests used to validate the behavior of a product. The scope of a Test Suite varies from organization to organization. There may be several Test Suites for a particular product for example. In most cases however a Test Suite is a high level concept, grouping together hundreds or thousands of tests related by what they are intended to test.

Test Tools: Computer programs used in the testing of a system, a component of the system, or its documentation.

Thread Testing: A variation of top-down testing where the progressive integration of components follows the implementation of subsets of the requirements, as opposed to the integration of components by successively lower levels.

Thick Client Application Tests: A Thick Client (also referred to as a fat client) is a purpose built piece of software that has been developed to work as a client with a server. It often has substantial business logic embedded within it, beyond the simple validation that is able to be achieved through a web browser. A thick client is often able to be very efficient with the amount of data that is transferred between it and its server, but is also often sensitive to any poor communications links. Testing tools such as QTP are able to be used to drive a Thick Client, so that response time can be measured under a variety of circumstances within a testing regime.
Developing a load test based on thick client activity usually requires significantly more effort for the coding stage of testing, as VUGen must be used to simulate the protocol between the client and the server. That protocol may be database connection based, COM/DCOM based, a proprietary communications protocol or even a combination of protocols.

Thin Client Application Tests: An internet browser that is used to run an application is said to be a thin client. But even thin clients can consume substantial amounts of CPU time on the computer that they are running on. This is particularly the case with complex web pages that utilize many recently introduced features to liven up a web page. Rendering a page after hitting a SUBMIT button may take several seconds even though the server may have responded to the request in less than one second. Testing tools such as QTP are able to be used to drive a Thin Client, so that response time can be measured from a user’s perspective, rather than from a protocol level.

Top Down Testing: An approach to integration testing where the component at the top of the component hierarchy is tested first, with lower level components being simulated by stubs. Tested components are then used to test lower level components. The process is repeated until the lowest level components have been tested.

Traceability Matrix: A document showing the relationship between Test Requirements and Test Cases.

Tuning Cycle Tests: A series of test cycles can be executed with a primary purpose of identifying tuning opportunities. Tests can be refined and re-targeted 'on the fly' to allow technology support staff to make configuration changes so that the impact of those changes can be immediately measured.

Usability Testing: Testing the ease with which users can learn and use a product.

Use Case: The specification of tests that are conducted from the end-user perspective. Use cases tend to focus on operating software as an end-user would conduct their day-to-day activities.

User Acceptance Testing: A formal product evaluation performed by a customer as a condition of purchase.

Unit Testing: The most 'micro' scale of testing; to test particular functions or code modules. Typically done by the programmer and not by testers, as it requires detailed knowledge of the internal program design and code. Not always easily done unless the application has a well-designed architecture with tight code; may require developing test driver modules or test harnesses.

Validation: The process of evaluating software at the end of the software development process to ensure compliance with software requirements. The techniques for validation are testing, inspection and reviewing.

Verification: The process of determining whether or not the products of a given phase of the software development cycle meet the implementation steps and can be traced to the incoming objectives established during the previous phase. The techniques for verification are testing, inspection and reviewing.

Volume Testing: Testing which confirms that any values that may become large over time (such as accumulated counts, logs, and data files), can be accommodated by the program and will not cause the program to stop working or degrade its operation in any manner.
Volume Tests are often most appropriate to Messaging, Batch and Conversion processing type situations. In a Volume Test, there is often no such measure as Response time. Instead, there is usually a concept of Throughput.
A key to effective volume testing is the identification of the relevant capacity drivers. A capacity driver is something that directly impacts on the total processing capacity. For a messaging system, a capacity driver may well be the size of messages being processed. For batch processing, the type of records in the batch as well as the size of the database that the batch process interfaces with will have an impact on the number of batch records that can be processed per second.

Walkthrough: A review of requirements, designs or code characterized by the author of the material under review guiding the progression of the review.

White Box Testing: Testing based on an analysis of internal workings and structure of a piece of software. Includes techniques such as Branch Testing and Path Testing. Also known as Structural Testing and Glass Box Testing. Contrast with Black Box Testing.

Workflow Testing: Scripted end-to-end testing which duplicates specific workflows which are expected to be utilized by the end-user.

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