Smoke testing
In computer programming and software testing, smoke testing is a preliminary to further testing, which should reveal simple failures severe enough to reject a prospective software release. In this case, the smoke is metaphorical.
Smoke testing is done by developers before the build is released to the testers, or by testers before accepting a build for further testing. Microsoft claims[1] that after code reviews, smoke testing is the most cost effective method for identifying and fixing defects in software.
n software engineering, a smoke test generally consists of a collection of tests that can be applied to a newly created or repaired computer program. Sometimes the tests are performed by the automated system that builds the final software. In this sense a smoke test is the process of validating code changes before the changes are checked into the larger product’s official source code collection or the main branch of source code.
In software testing, a smoke test is a collection of written tests that are performed on a system prior to being accepted for further testing. This is also known as a build verification test. This is a "shallow and wide" approach to the application. The tester "touches" all areas of the application without getting too deep, looking for answers to basic questions like, "Can I launch the test item at all?", "Does it open to a window?", "Do the buttons on the window do things?".
The purpose is to determine whether or not the application is so badly broken that testing functionality in a more detailed way is unnecessary. These written tests can either be performed manually or using an automated tool. When automated tools are used, the tests are often initiated by the same process that generates the build itself.
This is sometimes referred to as "rattle" testing - as in "if I shake it does it rattle?". Steve McConnell gives some good advice for smoke testing software.
http://www.stevemcconnell.com/ieeesoftware/bp04.htm
Sanity testing
In computer science, a sanity test is a very brief run-through of the functionality of a computer program, system, calculation, or other analysis, to assure that the system or methodology works as expected, often prior to a more exhaustive round of testing.
In software development, the sanity test (a form of software testing which offers "quick, broad, and shallow testing"[1]) determines whether it is reasonable to proceed with further testing.
Software sanity tests are commonly conflated with smoke tests.A smoke test determines whether it is possible to continue testing, as opposed to whether it is reasonable.
A software smoke test determines whether the program launches and whether its interfaces are accessible and responsive (for example, the responsiveness of a web page or an input button). If the smoke test fails, it is impossible to conduct a sanity test. In contrast, the ideal sanity test exercises the smallest subset of application functions needed to determine whether the application logic is generally functional and correct (for example, an interest rate calculation for a financial application). If the sanity test fails, it is not reasonable to attempt more rigorous testing. Both sanity tests and smoke tests are ways to avoid wasting time and effort by quickly determining whether an application is too flawed to merit any rigorous testing. Many companies run sanity tests and unit tests on an automated build as part of their development process.
The Hello world program is often used as a sanity test for a development environment. If Hello World fails to compile or execute, the supporting environment likely has a configuration problem. If it works, the problem being diagnosed likely lies in the real application being diagnosed.
Wednesday, September 30, 2009
Black Box (Vs) White Box
An easy way to start up a debate in a software testing forum is to ask the difference between black box and white box testing. These terms are commonly used, yet everyone seems to have a different idea of what they mean.
Black box testing begins with a metaphor. Imagine you’re testing an electronics system. It’s housed in a black box with lights, switches, and dials on the outside. You must test it without opening it up, and you can’t see beyond its surface. You have to see if it works just by flipping switches (inputs) and seeing what happens to the lights and dials (outputs). This is black box testing. Black box software testing is doing the same thing, but with software. The actual meaning of the metaphor, however, depends on how you define the boundary of the box and what kind of access the “blackness” is blocking.
An opposite test approach would be to open up the electronics system, see how the circuits are wired, apply probes internally and maybe even disassemble parts of it. By analogy, this is called white box testing,
To help understand the different ways that software testing can be divided between black box and white box techniques, consider the Five-Fold Testing System. It lays out five dimensions that can be used for examining testing:
1. People(who does the testing)
2. Coverage (what gets tested)
3. Risks (why you are testing)
4. Activities(how you are testing)
5. Evaluation (how you know you’ve found a bug)
Let’s use this system to understand and clarify the characteristics of black box and white box testing.
People: Who does the testing?
Some people know how software works (developers) and others just use it (users). Accordingly, any testing by users or other non-developers is sometimes called “black box” testing. Developer testing is called “white box” testing. The distinction here is based on what the person knows or can understand.
Coverage: What is tested?
If we draw the box around the system as a whole, “black box” testing becomes another name for system testing. And testing the units inside the box becomes white box testing. This is one way to think about coverage. Another is to contrast testing that aims to cover all the requirements with testing that aims to cover all the code. These are the two most commonly used coverage criteria. Both are supported by extensive literature and commercial tools. Requirements-based testing could be called “black box” because it makes sure that all the customer requirements have been verified. Code-based testing is often called “white box” because it makes sure that all the code (the statements, paths, or decisions) is exercised.
Risks: Why are you testing?
Sometimes testing is targeted at particular risks. Boundary testing and other attack-based techniques are targeted at common coding errors. Effective security testing also requires a detailed understanding of the code and the system architecture. Thus, these techniques might be classified as “white box”. Another set of risks concerns whether the software will actually provide value to users. Usability testing focuses on this risk, and could be termed “black box.”
Activities: How do you test?
A common distinction is made between behavioral test design, which defines tests based on functional requirements, and structural test design, which defines tests based on the code itself. These are two design approaches. Since behavioral testing is based on external functional definition, it is often called “black box,” while structural testing—based on the code internals—is called “white box.” Indeed, this is probably the most commonly cited definition for black box and white box testing. Another activity-based distinction contrasts dynamic test execution with formal code inspection. In this case, the metaphor maps test execution (dynamic testing) with black box testing, and maps code inspection (static testing) with white box testing. We could also focus on the tools used. Some tool vendors refer to code-coverage tools as white box tools, and tools that facilitate applying inputs and capturing inputs—most notably GUI capture replay tools—as black box tools. Testing is then categorized based on the types of tools used.
Evaluation: How do you know if you’ve found a bug?
There are certain kinds of software faults that don’t always lead to obvious failures. They may be masked by fault tolerance or simply luck. Memory leaks and wild pointers are examples. Certain test techniques seek to make these kinds of problems more visible. Related techniques capture code history and stack information when faults occur, helping with diagnosis. Assertions are another technique for helping to make problems more visible. All of these techniques could be considered white box test techniques, since they use code instrumentation to make the internal workings of the software more visible. These contrast with black box techniques that simply look at the official outputs of a program.
White box testing is concerned only with testing the software product; it cannot guarantee that the complete specification has been implemented. Black box testing is concerned only with testing the specification; it cannot guarantee that all parts of the implementation have been tested. Thus black box testing is testing against the specification and will discover faults of omission, indicating that part of the specification has not been fulfilled. White box testing is testing against the implementation and will discover faults of commission, indicating that part of the implementation is faulty. In order to fully test a software product both black and white box testing are required.
White box testing is much more expensive than black box testing. It requires the source code to be produced before the tests can be planned and is much more laborious in the determination of suitable input data and the determination if the software is or is not correct. The advice given is to start test planning with a black box test approach as soon as the specification is available. White box planning should commence as soon as all black box tests have been successfully passed, with the production of flowgraphs and determination of paths. The paths should then be checked against the black box test plan and any additional required test runs determined and applied.
The consequences of test failure at this stage may be very expensive. A failure of a white box test may result in a change which requires all black boxes testing to be repeated and the re-determination of the white box paths
To conclude, apart from the above described analytical methods of both glass and black box testing, there are further constructive means to guarantee high quality software end products. Among the most important constructive means are the usage of object-oriented programming tools, the integration of CASE tools, rapid prototyping, and last but not least the involvement of users in both software development and testing procedures
Summary :
Black box testing can sometimes describe user-based testing (people); system or requirements-based testing (coverage); usability testing (risk); or behavioral testing or capture replay automation (activities). White box testing, on the other hand, can sometimes describe developer-based testing (people); unit or code-coverage testing (coverage); boundary or security testing (risks); structural testing, inspection or code-coverage automation (activities); or testing based on probes, assertions, and logs (evaluation).
Black box testing begins with a metaphor. Imagine you’re testing an electronics system. It’s housed in a black box with lights, switches, and dials on the outside. You must test it without opening it up, and you can’t see beyond its surface. You have to see if it works just by flipping switches (inputs) and seeing what happens to the lights and dials (outputs). This is black box testing. Black box software testing is doing the same thing, but with software. The actual meaning of the metaphor, however, depends on how you define the boundary of the box and what kind of access the “blackness” is blocking.
An opposite test approach would be to open up the electronics system, see how the circuits are wired, apply probes internally and maybe even disassemble parts of it. By analogy, this is called white box testing,
To help understand the different ways that software testing can be divided between black box and white box techniques, consider the Five-Fold Testing System. It lays out five dimensions that can be used for examining testing:
1. People(who does the testing)
2. Coverage (what gets tested)
3. Risks (why you are testing)
4. Activities(how you are testing)
5. Evaluation (how you know you’ve found a bug)
Let’s use this system to understand and clarify the characteristics of black box and white box testing.
People: Who does the testing?
Some people know how software works (developers) and others just use it (users). Accordingly, any testing by users or other non-developers is sometimes called “black box” testing. Developer testing is called “white box” testing. The distinction here is based on what the person knows or can understand.
Coverage: What is tested?
If we draw the box around the system as a whole, “black box” testing becomes another name for system testing. And testing the units inside the box becomes white box testing. This is one way to think about coverage. Another is to contrast testing that aims to cover all the requirements with testing that aims to cover all the code. These are the two most commonly used coverage criteria. Both are supported by extensive literature and commercial tools. Requirements-based testing could be called “black box” because it makes sure that all the customer requirements have been verified. Code-based testing is often called “white box” because it makes sure that all the code (the statements, paths, or decisions) is exercised.
Risks: Why are you testing?
Sometimes testing is targeted at particular risks. Boundary testing and other attack-based techniques are targeted at common coding errors. Effective security testing also requires a detailed understanding of the code and the system architecture. Thus, these techniques might be classified as “white box”. Another set of risks concerns whether the software will actually provide value to users. Usability testing focuses on this risk, and could be termed “black box.”
Activities: How do you test?
A common distinction is made between behavioral test design, which defines tests based on functional requirements, and structural test design, which defines tests based on the code itself. These are two design approaches. Since behavioral testing is based on external functional definition, it is often called “black box,” while structural testing—based on the code internals—is called “white box.” Indeed, this is probably the most commonly cited definition for black box and white box testing. Another activity-based distinction contrasts dynamic test execution with formal code inspection. In this case, the metaphor maps test execution (dynamic testing) with black box testing, and maps code inspection (static testing) with white box testing. We could also focus on the tools used. Some tool vendors refer to code-coverage tools as white box tools, and tools that facilitate applying inputs and capturing inputs—most notably GUI capture replay tools—as black box tools. Testing is then categorized based on the types of tools used.
Evaluation: How do you know if you’ve found a bug?
There are certain kinds of software faults that don’t always lead to obvious failures. They may be masked by fault tolerance or simply luck. Memory leaks and wild pointers are examples. Certain test techniques seek to make these kinds of problems more visible. Related techniques capture code history and stack information when faults occur, helping with diagnosis. Assertions are another technique for helping to make problems more visible. All of these techniques could be considered white box test techniques, since they use code instrumentation to make the internal workings of the software more visible. These contrast with black box techniques that simply look at the official outputs of a program.
White box testing is concerned only with testing the software product; it cannot guarantee that the complete specification has been implemented. Black box testing is concerned only with testing the specification; it cannot guarantee that all parts of the implementation have been tested. Thus black box testing is testing against the specification and will discover faults of omission, indicating that part of the specification has not been fulfilled. White box testing is testing against the implementation and will discover faults of commission, indicating that part of the implementation is faulty. In order to fully test a software product both black and white box testing are required.
White box testing is much more expensive than black box testing. It requires the source code to be produced before the tests can be planned and is much more laborious in the determination of suitable input data and the determination if the software is or is not correct. The advice given is to start test planning with a black box test approach as soon as the specification is available. White box planning should commence as soon as all black box tests have been successfully passed, with the production of flowgraphs and determination of paths. The paths should then be checked against the black box test plan and any additional required test runs determined and applied.
The consequences of test failure at this stage may be very expensive. A failure of a white box test may result in a change which requires all black boxes testing to be repeated and the re-determination of the white box paths
To conclude, apart from the above described analytical methods of both glass and black box testing, there are further constructive means to guarantee high quality software end products. Among the most important constructive means are the usage of object-oriented programming tools, the integration of CASE tools, rapid prototyping, and last but not least the involvement of users in both software development and testing procedures
Summary :
Black box testing can sometimes describe user-based testing (people); system or requirements-based testing (coverage); usability testing (risk); or behavioral testing or capture replay automation (activities). White box testing, on the other hand, can sometimes describe developer-based testing (people); unit or code-coverage testing (coverage); boundary or security testing (risks); structural testing, inspection or code-coverage automation (activities); or testing based on probes, assertions, and logs (evaluation).
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