Part of a series on |
Software development |
---|
Software testing is the act of checking whether software satisfies expectations.
Software testing can provide objective, independent information about the quality of software and the risk of its failure to a user or sponsor. [1]
Software testing can determine the correctness of software for specific scenarios, but cannot determine correctness for all scenarios. [2] [3] It cannot find all bugs.
Based on the criteria for measuring correctness from an oracle, software testing employs principles and mechanisms that might recognize a problem. Examples of oracles include: specifications, contracts, [4] comparable products, past versions of the same product, inferences about intended or expected purpose, user or customer expectations, relevant standards, applicable laws.
Software testing is often dynamic in nature; running the software to verify actual output matches expected. It can also be static in nature; reviewing code and its associated documentation.
Software testing is often used to answer the question: Does the software do what it is supposed to do and what it needs to do?
Information learned from software testing may be used to improve the process by which software is developed. [5] : 41–43
Software testing should follow a "pyramid" approach wherein most of your tests should be unit tests, followed by integration tests and finally end to end (e2e) tests should have the lowest proportion. [6] [7] [8]
A study conducted by NIST in 2002 reports that software bugs cost the U.S. economy $59.5 billion annually. More than a third of this cost could be avoided, if better software testing was performed. [9] [ dubious – discuss ]
Outsourcing software testing because of costs is very common, with China, the Philippines, and India being preferred destinations.[ citation needed ]
Glenford J. Myers initially introduced the separation of debugging from testing in 1979. [10] Although his attention was on breakage testing ("A successful test case is one that detects an as-yet undiscovered error." [10] : 16 ), it illustrated the desire of the software engineering community to separate fundamental development activities, such as debugging, from that of verification.
Software testing is typically goal driven.
Software testing typically includes handling software bugs – a defect in the code that causes an undesirable result. [11] : 31 Bugs generally slow testing progress and involve programmer assistance to debug and fix.
Not all defects cause a failure. For example, a defect in dead code will not be considered a failure.
A defect that does not cause failure at one point in time may later occur due to environmental changes. Examples of environment change include running on new computer hardware, changes in data, and interacting with different software. [12]
A single defect may result in multiple failure symptoms.
Software testing may involve a Requirements gap – omission from the design for a requirement. [5] : 426 Requirement gaps can often be non-functional requirements such as testability, scalability, maintainability, performance, and security.
A fundamental limitation of software testing is that testing under all combinations of inputs and preconditions (initial state) is not feasible, even with a simple product. [3] : 17–18 [13] Defects that manifest in unusual conditions are difficult to find in testing. Also, non-functional dimensions of quality (how it is supposed to be versus what it is supposed to do) – usability, scalability, performance, compatibility, and reliability – can be subjective; something that constitutes sufficient value to one person may not to another.
Although testing for every possible input is not feasible, testing can use combinatorics to maximize coverage while minimizing tests. [14]
Testing can be categorized many ways. [15]
Software testing can be categorized into levels based on how much of the software system is the focus of a test. [18] [19] [20] [21]
There are many approaches to software testing. Reviews, walkthroughs, or inspections are referred to as static testing, whereas executing programmed code with a given set of test cases is referred to as dynamic testing. [23] [24]
Static testing is often implicit, like proofreading, plus when programming tools/text editors check source code structure or compilers (pre-compilers) check syntax and data flow as static program analysis. Dynamic testing takes place when the program itself is run. Dynamic testing may begin before the program is 100% complete in order to test particular sections of code and are applied to discrete functions or modules. [23] [24] Typical techniques for these are either using stubs/drivers or execution from a debugger environment. [24]
Static testing involves verification, whereas dynamic testing also involves validation. [24]
Passive testing means verifying the system's behavior without any interaction with the software product. Contrary to active testing, testers do not provide any test data but look at system logs and traces. They mine for patterns and specific behavior in order to make some kind of decisions. [25] This is related to offline runtime verification and log analysis.
The type of testing strategy to be performed depends on whether the tests to be applied to the IUT should be decided before the testing plan starts to be executed (preset testing [28] ) or whether each input to be applied to the IUT can be dynamically dependent on the outputs obtained during the application of the previous tests (adaptive testing [29] [30] ).
Software testing can often be divided into white-box and black-box. These two approaches are used to describe the point of view that the tester takes when designing test cases. A hybrid approach called grey-box includes aspects of both boxes may also be applied to software testing methodology. [31] [32]
White-box testing (also known as clear box testing, glass box testing, transparent box testing, and structural testing) verifies the internal structures or workings of a program, as opposed to the functionality exposed to the end-user. In white-box testing, an internal perspective of the system (the source code), as well as programming skills, are used to design test cases. The tester chooses inputs to exercise paths through the code and determines the appropriate outputs. [31] [32] This is analogous to testing nodes in a circuit, e.g., in-circuit testing (ICT).
While white-box testing can be applied at the unit, integration, and system levels of the software testing process, it is usually done at the unit level. [33] It can test paths within a unit, paths between units during integration, and between subsystems during a system–level test. Though this method of test design can uncover many errors or problems, it might not detect unimplemented parts of the specification or missing requirements.
Techniques used in white-box testing include: [32] [34]
Code coverage tools can evaluate the completeness of a test suite that was created with any method, including black-box testing. This allows the software team to examine parts of a system that are rarely tested and ensures that the most important function points have been tested. [35] Code coverage as a software metric can be reported as a percentage for: [31] [35] [36]
100% statement coverage ensures that all code paths or branches (in terms of control flow) are executed at least once. This is helpful in ensuring correct functionality, but not sufficient since the same code may process different inputs correctly or incorrectly. [37]
Black-box testing (also known as functional testing) describes designing test cases without knowledge of the implementation, without reading the source code. The testers are only aware of what the software is supposed to do, not how it does it. [38] Black-box testing methods include: equivalence partitioning, boundary value analysis, all-pairs testing, state transition tables, decision table testing, fuzz testing, model-based testing, use case testing, exploratory testing, and specification-based testing. [31] [32] [36]
Specification-based testing aims to test the functionality of software according to the applicable requirements. [39] This level of testing usually requires thorough test cases to be provided to the tester, who then can simply verify that for a given input, the output value (or behavior), either "is" or "is not" the same as the expected value specified in the test case. Test cases are built around specifications and requirements, i.e., what the application is supposed to do. It uses external descriptions of the software, including specifications, requirements, and designs to derive test cases. These tests can be functional or non-functional, though usually functional. Specification-based testing may be necessary to assure correct functionality, but it is insufficient to guard against complex or high-risk situations. [40]
Black box testing can be used to any level of testing although usually not at the unit level. [33]
Component interface testing
Component interface testing is a variation of black-box testing, with the focus on the data values beyond just the related actions of a subsystem component. [41] The practice of component interface testing can be used to check the handling of data passed between various units, or subsystem components, beyond full integration testing between those units. [42] [43] The data being passed can be considered as "message packets" and the range or data types can be checked, for data generated from one unit, and tested for validity before being passed into another unit. One option for interface testing is to keep a separate log file of data items being passed, often with a timestamp logged to allow analysis of thousands of cases of data passed between units for days or weeks. Tests can include checking the handling of some extreme data values while other interface variables are passed as normal values. [42] Unusual data values in an interface can help explain unexpected performance in the next unit.
The aim of visual testing is to provide developers with the ability to examine what was happening at the point of software failure by presenting the data in such a way that the developer can easily find the information he or she requires, and the information is expressed clearly. [44] [45]
At the core of visual testing is the idea that showing someone a problem (or a test failure), rather than just describing it, greatly increases clarity and understanding. Visual testing, therefore, requires the recording of the entire test process – capturing everything that occurs on the test system in video format. Output videos are supplemented by real-time tester input via picture-in-a-picture webcam and audio commentary from microphones.
Visual testing provides a number of advantages. The quality of communication is increased drastically because testers can show the problem (and the events leading up to it) to the developer as opposed to just describing it and the need to replicate test failures will cease to exist in many cases. The developer will have all the evidence he or she requires of a test failure and can instead focus on the cause of the fault and how it should be fixed.
Ad hoc testing and exploratory testing are important methodologies for checking software integrity, because they require less preparation time to implement, while the important bugs can be found quickly. [46] In ad hoc testing, where testing takes place in an improvised impromptu way, the ability of the tester(s) to base testing off documented methods and then improvise variations of those tests can result in more rigorous examination of defect fixes. [46] However, unless strict documentation of the procedures are maintained, one of the limits of ad hoc testing is lack of repeatability. [46]
Grey-box testing (American spelling: gray-box testing) involves using knowledge of internal data structures and algorithms for purposes of designing tests while executing those tests at the user, or black-box level. The tester will often have access to both "the source code and the executable binary." [47] Grey-box testing may also include reverse engineering (using dynamic code analysis) to determine, for instance, boundary values or error messages. [47] Manipulating input data and formatting output do not qualify as grey-box, as the input and output are clearly outside of the "black box" that we are calling the system under test. This distinction is particularly important when conducting integration testing between two modules of code written by two different developers, where only the interfaces are exposed for the test.
By knowing the underlying concepts of how the software works, the tester makes better-informed testing choices while testing the software from outside. Typically, a grey-box tester will be permitted to set up an isolated testing environment with activities such as seeding a database. The tester can observe the state of the product being tested after performing certain actions such as executing SQL statements against the database and then executing queries to ensure that the expected changes have been reflected. Grey-box testing implements intelligent test scenarios, based on limited information. This will particularly apply to data type handling, exception handling, and so on. [48]
With the concept of grey-box testing, this "arbitrary distinction" between black- and white-box testing has faded somewhat. [33]
Most software systems have installation procedures that are needed before they can be used for their main purpose. Testing these procedures to achieve an installed software system that may be used is known as installation testing. [49] : 139 These procedures may involve full or partial upgrades, and install/uninstall processes.
A common cause of software failure (real or perceived) is a lack of its compatibility with other application software, operating systems (or operating system versions, old or new), or target environments that differ greatly from the original (such as a terminal or GUI application intended to be run on the desktop now being required to become a Web application, which must render in a Web browser). For example, in the case of a lack of backward compatibility, this can occur because the programmers develop and test software only on the latest version of the target environment, which not all users may be running. This results in the unintended consequence that the latest work may not function on earlier versions of the target environment, or on older hardware that earlier versions of the target environment were capable of using. Sometimes such issues can be fixed by proactively abstracting operating system functionality into a separate program module or library.
Sanity testing determines whether it is reasonable to proceed with further testing.
Smoke testing consists of minimal attempts to operate the software, designed to determine whether there are any basic problems that will prevent it from working at all. Such tests can be used as build verification test.
Regression testing focuses on finding defects after a major code change has occurred. Specifically, it seeks to uncover software regressions, as degraded or lost features, including old bugs that have come back. Such regressions occur whenever software functionality that was previously working correctly, stops working as intended. Typically, regressions occur as an unintended consequence of program changes, when the newly developed part of the software collides with the previously existing code. Regression testing is typically the largest test effort in commercial software development, [50] due to checking numerous details in prior software features, and even new software can be developed while using some old test cases to test parts of the new design to ensure prior functionality is still supported.
Common methods of regression testing include re-running previous sets of test cases and checking whether previously fixed faults have re-emerged. The depth of testing depends on the phase in the release process and the risk of the added features. They can either be complete, for changes added late in the release or deemed to be risky, or be very shallow, consisting of positive tests on each feature, if the changes are early in the release or deemed to be of low risk.
Acceptance testing is system-level testing to ensure the software meets customer expectations. [51] [52] [53] [54]
Acceptance testing may be performed as part of the hand-off process between any two phases of development.[ citation needed ]
Tests are frequently grouped into these levels by where they are performed in the software development process, or by the level of specificity of the test. [54]
Sometimes, UAT is performed by the customer, in their environment and on their own hardware.
OAT is used to conduct operational readiness (pre-release) of a product, service or system as part of a quality management system. OAT is a common type of non-functional software testing, used mainly in software development and software maintenance projects. This type of testing focuses on the operational readiness of the system to be supported, or to become part of the production environment. Hence, it is also known as operational readiness testing (ORT) or Operations readiness and assurance (OR&A) testing. Functional testing within OAT is limited to those tests that are required to verify the non-functional aspects of the system.
In addition, the software testing should ensure that the portability of the system, as well as working as expected, does not also damage or partially corrupt its operating environment or cause other processes within that environment to become inoperative. [55]
Contractual acceptance testing is performed based on the contract's acceptance criteria defined during the agreement of the contract, while regulatory acceptance testing is performed based on the relevant regulations to the software product. Both of these two tests can be performed by users or independent testers. Regulation acceptance testing sometimes involves the regulatory agencies auditing the test results. [54]
Alpha testing is simulated or actual operational testing by potential users/customers or an independent test team at the developers' site. Alpha testing is often employed for off-the-shelf software as a form of internal acceptance testing before the software goes to beta testing. [56]
Beta testing comes after alpha testing and can be considered a form of external user acceptance testing. Versions of the software, known as beta versions, are released to a limited audience outside of the programming team known as beta testers. The software is released to groups of people so that further testing can ensure the product has few faults or bugs. Beta versions can be made available to the open public to increase the feedback field to a maximal number of future users and to deliver value earlier, for an extended or even indefinite period of time (perpetual beta). [57]
Functional testing refers to activities that verify a specific action or function of the code. These are usually found in the code requirements documentation, although some development methodologies work from use cases or user stories. Functional tests tend to answer the question of "can the user do this" or "does this particular feature work."
Non-functional testing refers to aspects of the software that may not be related to a specific function or user action, such as scalability or other performance, behavior under certain constraints, or security. Testing will determine the breaking point, the point at which extremes of scalability or performance leads to unstable execution. Non-functional requirements tend to be those that reflect the quality of the product, particularly in the context of the suitability perspective of its users.
Continuous testing is the process of executing automated tests as part of the software delivery pipeline to obtain immediate feedback on the business risks associated with a software release candidate. [58] [59] Continuous testing includes the validation of both functional requirements and non-functional requirements; the scope of testing extends from validating bottom-up requirements or user stories to assessing the system requirements associated with overarching business goals. [60] [61]
Destructive testing attempts to cause the software or a sub-system to fail. It verifies that the software functions properly even when it receives invalid or unexpected inputs, thereby establishing the robustness of input validation and error-management routines.[ citation needed ] Software fault injection, in the form of fuzzing, is an example of failure testing. Various commercial non-functional testing tools are linked from the software fault injection page; there are also numerous open-source and free software tools available that perform destructive testing.
Performance testing is generally executed to determine how a system or sub-system performs in terms of responsiveness and stability under a particular workload. It can also serve to investigate, measure, validate or verify other quality attributes of the system, such as scalability, reliability and resource usage.
Load testing is primarily concerned with testing that the system can continue to operate under a specific load, whether that be large quantities of data or a large number of users. This is generally referred to as software scalability. The related load testing activity of when performed as a non-functional activity is often referred to as endurance testing. Volume testing is a way to test software functions even when certain components (for example a file or database) increase radically in size. Stress testing is a way to test reliability under unexpected or rare workloads. Stability testing (often referred to as load or endurance testing) checks to see if the software can continuously function well in or above an acceptable period.
There is little agreement on what the specific goals of performance testing are. The terms load testing, performance testing, scalability testing, and volume testing, are often used interchangeably.
Real-time software systems have strict timing constraints. To test if timing constraints are met, real-time testing is used.
Usability testing is to check if the user interface is easy to use and understand. It is concerned mainly with the use of the application. This is not a kind of testing that can be automated; actual human users are needed, being monitored by skilled UI designers.
Accessibility testing is done to ensure that the software is accessible to persons with disabilities. Some of the common web accessibility tests are
Common Standards for compliance
Security testing is essential for software that processes confidential data to prevent system intrusion by hackers.
The International Organization for Standardization (ISO) defines this as a "type of testing conducted to evaluate the degree to which a test item, and associated data and information, are protected so that unauthorised persons or systems cannot use, read or modify them, and authorized persons or systems are not denied access to them." [62]
Testing for internationalization and localization validates that the software can be used with different languages and geographic regions. The process of pseudolocalization is used to test the ability of an application to be translated to another language, and make it easier to identify when the localization process may introduce new bugs into the product.
Globalization testing verifies that the software is adapted for a new culture (such as different currencies or time zones). [63]
Actual translation to human languages must be tested, too. Possible localization and globalization failures include:
Development Testing is a software development process that involves the synchronized application of a broad spectrum of defect prevention and detection strategies in order to reduce software development risks, time, and costs. It is performed by the software developer or engineer during the construction phase of the software development lifecycle. Development Testing aims to eliminate construction errors before code is promoted to other testing; this strategy is intended to increase the quality of the resulting software as well as the efficiency of the overall development process.
Depending on the organization's expectations for software development, Development Testing might include static code analysis, data flow analysis, metrics analysis, peer code reviews, unit testing, code coverage analysis, traceability, and other software testing practices.
A/B testing is a method of running a controlled experiment to determine if a proposed change is more effective than the current approach. Customers are routed to either a current version (control) of a feature, or to a modified version (treatment) and data is collected to determine which version is better at achieving the desired outcome.
Concurrent or concurrency testing assesses the behaviour and performance of software and systems that use concurrent computing, generally under normal usage conditions. Typical problems this type of testing will expose are deadlocks, race conditions and problems with shared memory/resource handling.
In software testing, conformance testing verifies that a product performs according to its specified standards. Compilers, for instance, are extensively tested to determine whether they meet the recognized standard for that language.
Creating a display expected output, whether as data comparison of text or screenshots of the UI, [3] : 195 is sometimes called snapshot testing or Golden Master Testing unlike many other forms of testing, this cannot detect failures automatically and instead requires that a human evaluate the output for inconsistencies.
Property testing is a testing technique where, instead of asserting that specific inputs produce specific expected outputs, the practitioner randomly generates many inputs, runs the program on all of them, and asserts the truth of some "property" that should be true for every pair of input and output. For example, every output from a serialization function should be accepted by the corresponding deserialization function, and every output from a sort function should be a monotonically increasing list containing exactly the same elements as its input.
Property testing libraries allow the user to control the strategy by which random inputs are constructed, to ensure coverage of degenerate cases, or inputs featuring specific patterns that are needed to fully exercise aspects of the implementation under test.
Property testing is also sometimes known as "generative testing" or "QuickCheck testing" since it was introduced and popularized by the Haskell library QuickCheck. [64]
Metamorphic testing (MT) is a property-based software testing technique, which can be an effective approach for addressing the test oracle problem and test case generation problem. The test oracle problem is the difficulty of determining the expected outcomes of selected test cases or to determine whether the actual outputs agree with the expected outcomes.
VCR testing, also known as "playback testing" or "record/replay" testing, is a testing technique for increasing the reliability and speed of regression tests that involve a component that is slow or unreliable to communicate with, often a third-party API outside of the tester's control. It involves making a recording ("cassette") of the system's interactions with the external component, and then replaying the recorded interactions as a substitute for communicating with the external system on subsequent runs of the test.
The technique was popularized in web development by the Ruby library vcr.
In an organization, testers may be in a separate team from the rest of the software development team or they may be integrated into one team. Software testing can also be performed by non-dedicated software testers.
In the 1980s, the term software tester started to be used to denote a separate profession.
Notable software testing roles and titles include: [65] test manager, test lead, test analyst, test designer, tester, automation developer, and test administrator. [66]
Organizations that develop software, perform testing differently, but there are common patterns. [2]
In waterfall development, testing is generally performed after the code is completed, but before the product is shipped to the customer. [67] This practice often results in the testing phase being used as a project buffer to compensate for project delays, thereby compromising the time devoted to testing. [10] : 145–146
Some contend that the waterfall process allows for testing to start when the development project starts and to be a continuous process until the project finishes. [68]
Agile software development commonly involves testing while the code is being written and organizing teams with both programmers and testers and with team members performing both programming and testing.
One agile practice, test-driven software development (TDD), is a way of unit testing such that unit-level testing is performed while writing the product code. [69] Test code is updated as new features are added and failure conditions are discovered (bugs fixed). Commonly, the unit test code is maintained with the project code, integrated in the build process, and run on each build and as part of regression testing. Goals of this continuous integration is to support development and reduce defects. [70] [69]
Even in organizations that separate teams by programming and testing functions, many often have the programmers perform unit testing. [71]
The sample below is common for waterfall development. The same activities are commonly found in other development models, but might be described differently.
Software testing is used in association with verification and validation: [72]
The terms verification and validation are commonly used interchangeably in the industry; it is also common to see these two terms defined with contradictory definitions. According to the IEEE Standard Glossary of Software Engineering Terminology: [11] : 80–81
And, according to the ISO 9000 standard:
The contradiction is caused by the use of the concepts of requirements and specified requirements but with different meanings.
In the case of IEEE standards, the specified requirements, mentioned in the definition of validation, are the set of problems, needs and wants of the stakeholders that the software must solve and satisfy. Such requirements are documented in a Software Requirements Specification (SRS). And, the products mentioned in the definition of verification, are the output artifacts of every phase of the software development process. These products are, in fact, specifications such as Architectural Design Specification, Detailed Design Specification, etc. The SRS is also a specification, but it cannot be verified (at least not in the sense used here, more on this subject below).
But, for the ISO 9000, the specified requirements are the set of specifications, as just mentioned above, that must be verified. A specification, as previously explained, is the product of a software development process phase that receives another specification as input. A specification is verified successfully when it correctly implements its input specification. All the specifications can be verified except the SRS because it is the first one (it can be validated, though). Examples: The Design Specification must implement the SRS; and, the Construction phase artifacts must implement the Design Specification.
So, when these words are defined in common terms, the apparent contradiction disappears.
Both the SRS and the software must be validated. The SRS can be validated statically by consulting with the stakeholders. Nevertheless, running some partial implementation of the software or a prototype of any kind (dynamic testing) and obtaining positive feedback from them, can further increase the certainty that the SRS is correctly formulated. On the other hand, the software, as a final and running product (not its artifacts and documents, including the source code) must be validated dynamically with the stakeholders by executing the software and having them to try it.
Some might argue that, for SRS, the input is the words of stakeholders and, therefore, SRS validation is the same as SRS verification. Thinking this way is not advisable as it only causes more confusion. It is better to think of verification as a process involving a formal and technical input document.
In some organizations, software testing is part of a software quality assurance (SQA) process. [3] : 347 In SQA, software process specialists and auditors are concerned with the software development process rather than just the artifacts such as documentation, code and systems. They examine and change the software engineering process itself to reduce the number of faults that end up in the delivered software: the so-called defect rate. What constitutes an acceptable defect rate depends on the nature of the software; a flight simulator video game would have much higher defect tolerance than software for an actual airplane. Although there are close links with SQA, testing departments often exist independently, and there may be no SQA function in some companies.[ citation needed ]
Software testing is an activity to investigate software under test in order to provide quality-related information to stakeholders. By contrast, QA (quality assurance) is the implementation of policies and procedures intended to prevent defects from reaching customers.
Quality measures include such topics as correctness, completeness, security and ISO/IEC 9126 requirements such as capability, reliability, efficiency, portability, maintainability, compatibility, and usability.
There are a number of frequently used software metrics, or measures, which are used to assist in determining the state of the software or the adequacy of the testing.
A software testing process can produce several artifacts. The actual artifacts produced are a factor of the software development model used, stakeholder and organisational needs.
A test plan is a document detailing the approach that will be taken for intended test activities. The plan may include aspects such as objectives, scope, processes and procedures, personnel requirements, and contingency plans. [51] The test plan could come in the form of a single plan that includes all test types (like an acceptance or system test plan) and planning considerations, or it may be issued as a master test plan that provides an overview of more than one detailed test plan (a plan of a plan). [51] A test plan can be, in some cases, part of a wide "test strategy" which documents overall testing approaches, which may itself be a master test plan or even a separate artifact.
A test case normally consists of a unique identifier, requirement references from a design specification, preconditions, events, a series of steps (also known as actions) to follow, input, output, expected result, and the actual result. Clinically defined, a test case is an input and an expected result. [74] This can be as terse as "for condition x your derived result is y", although normally test cases describe in more detail the input scenario and what results might be expected. It can occasionally be a series of steps (but often steps are contained in a separate test procedure that can be exercised against multiple test cases, as a matter of economy) but with one expected result or expected outcome. The optional fields are a test case ID, test step, or order of execution number, related requirement(s), depth, test category, author, and check boxes for whether the test is automatable and has been automated. Larger test cases may also contain prerequisite states or steps, and descriptions. A test case should also contain a place for the actual result. These steps can be stored in a word processor document, spreadsheet, database, or other common repositories. In a database system, you may also be able to see past test results, who generated the results, and what system configuration was used to generate those results. These past results would usually be stored in a separate table.
A test script is a procedure or programming code that replicates user actions. Initially, the term was derived from the product of work created by automated regression test tools. A test case will be a baseline to create test scripts using a tool or a program.
In most cases, multiple sets of values or data are used to test the same functionality of a particular feature. All the test values and changeable environmental components are collected in separate files and stored as test data. It is also useful to provide this data to the client and with the product or a project. There are techniques to generate Test data.
The software, tools, samples of data input and output, and configurations are all referred to collectively as a test harness.
A test run is a collection of test cases or test suites that the user is executing and comparing the expected with the actual results. Once complete, a report or all executed tests may be generated.
Several certification programs exist to support the professional aspirations of software testers and quality assurance specialists. A few practitioners argue that the testing field is not ready for certification, as mentioned in the controversy section.
Some of the major software testing controversies include:
It is commonly believed that the earlier a defect is found, the cheaper it is to fix it. The following table shows the cost of fixing the defect depending on the stage it was found. [84] For example, if a problem in the requirements is found only post-release, then it would cost 10–100 times more to fix than if it had already been found by the requirements review. With the advent of modern continuous deployment practices and cloud-based services, the cost of re-deployment and maintenance may lessen over time.
Cost to fix a defect Time detected Requirements Architecture Construction System test Post-release Time introduced Requirements 1× 3× 5–10× 10× 10–100× Architecture – 1× 10× 15× 25–100× Construction – – 1× 10× 10–25×
The data from which this table is extrapolated is scant. Laurent Bossavit says in his analysis:
The "smaller projects" curve turns out to be from only two teams of first-year students, a sample size so small that extrapolating to "smaller projects in general" is totally indefensible. The GTE study does not explain its data, other than to say it came from two projects, one large and one small. The paper cited for the Bell Labs "Safeguard" project specifically disclaims having collected the fine-grained data that Boehm's data points suggest. The IBM study (Fagan's paper) contains claims that seem to contradict Boehm's graph and no numerical results that clearly correspond to his data points.
Boehm doesn't even cite a paper for the TRW data, except when writing for "Making Software" in 2010, and there he cited the original 1976 article. There exists a large study conducted at TRW at the right time for Boehm to cite it, but that paper doesn't contain the sort of data that would support Boehm's claims. [85]
In engineering and its various subdisciplines, acceptance testing is a test conducted to determine if the requirements of a specification or contract are met. It may involve chemical tests, physical tests, or performance tests.
Unit testing, a.k.a. component or module testing, is a form of software testing by which isolated source code is tested to validate expected behavior.
Black-box testing, sometimes referred to as specification-based testing, is a method of software testing that examines the functionality of an application without peering into its internal structures or workings. This method of test can be applied virtually to every level of software testing: unit, integration, system and acceptance. Black-box testing is also used as a method in penetration testing, where an ethical hacker simulates an external hacking or cyber warfare attack with no knowledge of the system being attacked.
In engineering, a requirement is a condition that must be satisfied for the output of a work effort to be acceptable. It is an explicit, objective, clear and often quantitative description of a condition to be satisfied by a material, design, product, or service.
In software project management, software testing, and software engineering, verification and validation is the process of checking that a software engineer system meets specifications and requirements so that it fulfills its intended purpose. It may also be referred to as software quality control. It is normally the responsibility of software testers as part of the software development lifecycle. In simple terms, software verification is: "Assuming we should build X, does our software achieve its goals without any bugs or gaps?" On the other hand, software validation is: "Was X what we should have built? Does X meet the high-level requirements?"
White-box testing is a method of software testing that tests internal structures or workings of an application, as opposed to its functionality. In white-box testing, an internal perspective of the system is used to design test cases. The tester chooses inputs to exercise paths through the code and determine the expected outputs. This is analogous to testing nodes in a circuit, e.g. in-circuit testing (ICT). White-box testing can be applied at the unit, integration and system levels of the software testing process. Although traditional testers tended to think of white-box testing as being done at the unit level, it is used for integration and system testing more frequently today. It can test paths within a unit, paths between units during integration, and between subsystems during a system–level test. Though this method of test design can uncover many errors or problems, it has the potential to miss unimplemented parts of the specification or missing requirements. Where white-box testing is design-driven, that is, driven exclusively by agreed specifications of how each component of software is required to behave, white-box test techniques can accomplish assessment for unimplemented or missing requirements.
In software testing, test automation is the use of software separate from the software being tested to control the execution of tests and the comparison of actual outcomes with predicted outcomes. Test automation can automate some repetitive but necessary tasks in a formalized testing process already in place, or perform additional testing that would be difficult to do manually. Test automation is critical for continuous delivery and continuous testing.
A Fagan inspection is a process of trying to find defects in documents during various phases of the software development process. It is named after Michael Fagan, who is credited with the invention of formal software inspections.
In software engineering, a test case is a specification of the inputs, execution conditions, testing procedure, and expected results that define a single test to be executed to achieve a particular software testing objective, such as to exercise a particular program path or to verify compliance with a specific requirement. Test cases underlie testing that is methodical rather than haphazard. A battery of test cases can be built to produce the desired coverage of the software being tested. Formally defined test cases allow the same tests to be run repeatedly against successive versions of the software, allowing for effective and consistent regression testing.
A test plan is a document detailing the objectives, resources, and processes for a specific test session for a software or hardware product. The plan typically contains a detailed understanding of the eventual workflow.
Software assurance (SwA) is a critical process in software development that ensures the reliability, safety, and security of software products. It involves a variety of activities, including requirements analysis, design reviews, code inspections, testing, and formal verification. One crucial component of software assurance is secure coding practices, which follow industry-accepted standards and best practices, such as those outlined by the Software Engineering Institute (SEI) in their CERT Secure Coding Standards (SCS).
In software development, functional testing is a form of software system testing that verifies whether software matches its design.
Test data plays a crucial role in software development by providing inputs that are used to verify the correctness, performance, and reliability of software systems. Test data encompasses various types, such as positive and negative scenarios, edge cases, and realistic user scenarios, and it aims to exercise different aspects of the software to uncover bugs and validate its behavior. By designing and executing test cases with appropriate test data, developers can identify and rectify defects, improve the quality of the software, and ensure it meets the specified requirements. Moreover, test data can also be used for regression testing to validate that new code changes or enhancements do not introduce any unintended side effects or break existing functionalities. Overall, the effective utilization of test data in software development significantly contributes to the production of reliable and robust software systems.
A functional specification in systems engineering and software development is a document that specifies the functions that a system or component must perform.
Manual testing is the process of manually testing software for defects. It requires a tester to play the role of an end user where by they use most of the application's features to ensure correct behaviour. To guarantee completeness of testing, the tester often follows a written test plan that leads them through a set of important test cases.
In software development, the V-model represents a development process that may be considered an extension of the waterfall model and is an example of the more general V-model. Instead of moving down linearly, the process steps are bent upwards after the coding phase, to form the typical V shape. The V-Model demonstrates the relationships between each phase of the development life cycle and its associated phase of testing. The horizontal and vertical axes represent time or project completeness (left-to-right) and level of abstraction, respectively.
API testing is a type of software testing that involves testing application programming interfaces (APIs) directly and as part of integration testing to determine if they meet expectations for functionality, reliability, performance, and security. Since APIs lack a GUI, API testing is performed at the message layer. API testing is now considered critical for automating testing because APIs serve as the primary interface to application logic and because GUI tests are difficult to maintain with the short release cycles and frequent changes commonly used with Agile software development and DevOps.
Gray-box testing is a combination of white-box testing and black-box testing. The aim of this testing is to search for the defects, if any, due to improper structure or improper usage of applications.
Acceptance test–driven development (ATDD) is a development methodology based on communication between the business customers, the developers, and the testers. ATDD encompasses many of the same practices as specification by example (SBE), behavior-driven development (BDD), example-driven development (EDD), and support-driven development also called story test–driven development (SDD). All these processes aid developers and testers in understanding the customer's needs prior to implementation and allow customers to be able to converse in their own domain language.
This article discusses a set of tactics useful in software testing. It is intended as a comprehensive list of tactical approaches to software quality assurance and general application of the test method.
intf(intx){returnx*x-6*x+8;}
consists of only one statement. All tests against a specification f(x)>=0
will succeed, except if x=3
happens to be chosen.