This testing is typically done by the software testing engineer in conjunction with the configuration manager. Implementation testing is usually defined as testing which places a compiled version of code into the testing or pre-production environment, from which it may or may not progress into production. This generally takes place outside of the software development environment to limit code corruption from other future or past releases (or from the use of the wrong version of dependencies such as shared libraries) which may reside on the development environment.
The simplest installation approach is to run an install program, sometimes called package software. This package software typically uses a setup program which acts as a multi-configuration wrapper and which may allow the software to be installed on a variety of machine and/or operating environments. Every possible configuration should receive an appropriate level of testing so that it can be released to customers with confidence.
In distributed systems, particularly where software is to be released into an already live target environment (such as an operational website) installation (or software deployment as it is sometimes called) can involve database schema changes as well as the installation of new software. Deployment plans in such circumstances may include back-out procedures whose use is intended to roll the target environment back if the deployment is unsuccessful. Ideally, the deployment plan itself should be tested in an environment that is a replica of the live environment. A factor that can increase the organizational requirements of such an exercise is the need to synchronize the data in the test deployment environment with that in the live environment with minimum disruption to live operation. This type of implementation may include testing of the processes which take place during the installation or upgrade of a multi-tier application. This type of testing is commonly compared to a dress rehearsal or may even be called a “dry run”.
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 was capable of using. Sometimes such issues can be fixed by proactively abstractingoperating 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. 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. Regression testing is typically the largest test effort in commercial software development, 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.
Acceptance testing can mean one of two things:
A smoke test is used as an acceptance test prior to introducing a new build to the main testing process, i.e. before integration or regression.
Acceptance testing performed by the customer, often in their lab environment on their own hardware, is known as user acceptance testing (UAT). Acceptance testing may be performed as part of the hand-off process between any two phases of development.
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.
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. The software is released to groups of people so that further testing can ensure the product has few faults or bugs. Sometimes, beta versions are made available to the open public to increase the feedback field to a maximal number of future users.
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.
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. 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 needed to check if the user interface is easy to use and understand. It is concerned mainly with the use of the application.
Accessibility testing may include compliance with standards such as:
Security testing is essential for software that processes confidential data to prevent system intrusion by hackers.
The general ability of software to be internationalized and localized can be automatically tested without actual translation, by using pseudolocalization. It will verify that the application still works, even after it has been translated into a new language or adapted for a new culture (such as different currencies or time zones).
Actual translation to human languages must be tested, too. Possible localization failures include:
Software is often localized by translating a list of strings out of context, and the translator may choose the wrong translation for an ambiguous source string.
Technical terminology may become inconsistent if the project is translated by several people without proper coordination or if the translator is imprudent.
Literal word-for-word translations may sound inappropriate, artificial or too technical in the target language.
Untranslated messages in the original language may be left hard coded in the source code.
Some messages may be created automatically at run time and the resulting string may be ungrammatical, functionally incorrect, misleading or confusing.
Software may use a keyboard shortcut which has no function on the source language's keyboard layout, but is used for typing characters in the layout of the target language.
Software may lack support for the character encoding of the target language.
Fonts and font sizes which are appropriate in the source language may be inappropriate in the target language; for example, CJK characters may become unreadable if the font is too small.
A string in the target language may be longer than the software can handle. This may make the string partly invisible to the user or cause the software to crash or malfunction.
Software may lack proper support for reading or writing bi-directional text.
Software may display images with text that was not localized.
Localized operating systems may have differently named system configuration files and environment variables and different formats for date and currency.
Development Testing is a software development process that involves 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. Rather than replace traditional QA focuses, it augments it. Development Testing aims to eliminate construction errors before code is promoted to QA; this strategy is intended to increase the quality of the resulting software as well as the efficiency of the overall development and QA 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 verification practices.
As the name implies, two versions (A and B) are compared, which are identical except for one variation that might affect a user's behavior. Version A might be the currently used version (control), while Version B is modified in some respect (treatment). For instance, on an e-commerce website the purchase funnel is typically a good candidate for A/B testing, as even marginal improvements in drop-off rates can represent a significant gain in sales. Significant improvements can sometimes be seen through testing elements like copy text, layouts, images and colors, but not always. The vastly larger group of statistics broadly referred to as multivariate or multinomial testing is similar to A/B testing, but may test more than two different versions at the same time and/or has more controls, etc. Simple A/B tests are not valid for observational, quasi-experimental or other non-experimental situations, as is common with survey data, offline data, and other, more complex phenomena.
Conformance testing or type testing is testing to determine whether a product or system conforms with the requirements of a specification, contract or regulation. It is often physical testing but may involve chemical testing or requirements for efficiency or interoperability. To aid in this, many test procedures and test setups have been developed, either by the standard's maintainers or external organizations, specifically for testing conformance to standards. Conformance testing is sometimes performed by external organizations, which is sometimes the standards body itself, to give greater assurance of compliance. Products tested in such a manner are then advertised as being certified by that external organization as complying with the technical standard. Service providers, equipment manufacturers, and equipment suppliers rely on this data to ensure Quality of Service (QoS) through this conformance process.