Sanity check

From Wikipedia, the free encyclopedia
Jump to navigation Jump to search

A sanity test or sanity check is a basic test to quickly evaluate whether a claim or the result of a calculation can possibly be true. It is a simple check to see if the produced material is rational (that the material's creator was thinking rationally, applying sanity). The point of a sanity test is to rule out certain classes of obviously false results, not to catch every possible error. A rule-of-thumb or back-of-the-envelope calculation may be checked to perform the test. The advantage of a performing an initial sanity test is that of speedily evaluating basic function.

In arithmetic, for example, when multiplying by 9, using the divisibility rule for 9 to verify that the sum of digits of the result is divisible by 9 is a sanity test—it will not catch every multiplication error, however it's a quick and simple method to discover many possible errors.

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 part of the system or methodology works roughly as expected. This is often prior to a more exhaustive round of testing.

Mathematical[edit]

A sanity test can refer to various orders of magnitude and other simple rule-of-thumb devices applied to cross-check mathematical calculations. For example:

  • If one were to attempt to square 738 and calculated 54,464, a quick sanity check could show that this result cannot be true. Consider that 700 < 738, yet 7002 = 72 × 1002 = 490,000 > 54,464. Since squaring positive integers preserves their inequality, the result cannot be true, and so the calculated result is incorrect. The correct answer, 7382 = 544,644, is more than 10 times higher than 54,464.
  • In multiplication, 918 × 155 is not 142,135 since 918 is divisible by three but 142,135 is not (digits add up to 16, not a multiple of three). Also, the product must end in the same digit as the product of end-digits: 8 × 5 = 40, but 142,135 does not end in "0" like "40", while the correct answer does: 918 × 155 = 142,290. An even quicker check is that the product of even and odd numbers is even, whereas 142,135 is odd.

Physical[edit]

Software development[edit]

In software development, a sanity test (a form of software testing which offers "quick, broad, and shallow testing"[1]) evaluates the result of a subset of application functionality to determine whether it is possible and reasonable to proceed with further testing of the entire application.[2] Sanity tests may sometimes be used interchangeably with smoke tests[3] insofar as both terms denote tests which determine whether it is possible and reasonable to continue testing further. On the other hand, a distinction is sometimes made that a smoke test is a non-exhaustive test that ascertains whether the most crucial functions of a program work before proceeding with further testing whereas a sanity test refers to whether specific functionality such as a particular bug fix works as expected without testing the wider functionality of the software.[4] In other words, a sanity test determines whether the intended result of a code change works correctly while a smoke test ensures that nothing else important was broken in the process. Sanity testing and smoke testing avoid wasting time and effort by quickly determining whether an application is too flawed to merit more rigorous QA testing, but needs more developer debugging.

Groups of sanity tests are often bundled together for automated unit testing of functions, libraries, or applications prior to merging development code into a testing or trunk version control branch,[5] for automated building,[6] or for continuous integration and continuous deployment.[7]

Another common usage of sanity test is to denote checks which are performed within program code, usually on arguments to functions or returns therefrom, to see if the answers can be assumed to be correct. The more complicated the routine, the more important that its response be checked. The trivial case is checking to see whether the return value of a function indicated success or failure and to therefore cease further processing upon failure. This return value is actually often itself the result of a sanity check. For example, if the function attempted to open, write to, and close a file, a sanity check may be used to ensure that it did not fail on any of these actions—which is a sanity check often ignored by programmers.[8]

These kinds of sanity checks may be used during development for debugging purposes and also to aid in troubleshooting software runtime errors. For example, in a bank account management application, a sanity check will fail if a withdrawal requests more money than the total account balance rather than allowing the account to go negative (which wouldn't be sane). Another sanity test might be that deposits or purchases correspond to patterns established by historical data—for example, large purchase transactions or ATM withdrawals in foreign locations never before visited by the card holder may be flagged for confirmation.

Sanity checks are also performed upon installation of stable, production software code into a new computing environment to ensure that all dependencies are met, such as a compatible operating system and link libraries. When a computing environment has passed all of the sanity checks, it's known as a sane environment for the installation program to proceed with reasonable expectation of success.

A "Hello, World!" program is often used as a sanity test for a development environment in a similar fashion. Rather than a complicated script running a set of unit tests, if this simple program fails to compile or execute, it proves that the supporting environment likely has a configuration problem that will prevent any code from compiling or executing. But if "Hello world" executes, then any problems experienced with other programs likely can be attributed to errors in that application's code rather than the environment.

See also[edit]

References[edit]

  1. ^ Fecko, Mariusz A.; Lott, Christopher M. (October 2002). "Lessons learned from automating tests for an operations support system" (PDF). Software--Practice and Experience. 32 (15): 1485–1506. doi:10.1002/spe.491. Archived from the original (PDF) on 17 July 2003.
  2. ^ Sammi, Rabia; Masood, Iram; Jabeen, Shunaila (2011). Zain, Jasni Mohamad; Wan Mohd, Wan Maseri bt; El-Qawasmeh, Eyas (eds.). "A Framework to Assure the Quality of Sanity Check Process". Software Engineering and Computer Systems. Communications in Computer and Information Science. Berlin, Heidelberg: Springer. 181: 143–150. doi:10.1007/978-3-642-22203-0_13. ISBN 978-3-642-22203-0.
  3. ^ ISTQB® Glossary for the International Software Testing Qualification Board® software testing qualification scheme, ISTQB Glossary International Software Testing Qualification Board
  4. ^ https://www.ijert.org/research/software-testing-smoke-and-sanity-IJERTV2IS100323.pdf
  5. ^ http://webhotel4.ruc.dk/~nielsj/research/publications/freebsd.pdf
  6. ^ Hassan, A. E. and Zhang, K. 2006. Using Decision Trees to Predict the Certification Result of a Build. In Proceedings of the 21st IEEE/ACM international Conference on Automated Software Engineering (September 18 – 22, 2006). Automated Software Engineering. IEEE Computer Society, Washington, DC, 189–198.
  7. ^ http://jitm.ubalt.edu/XXIX-2/article4.pdf
  8. ^ Darwin, Ian F. (January 1991). Checking C programs with lint (1st ed., with minor revisions. ed.). Newton, Mass.: O'Reilly & Associates. p. 19. ISBN 0-937175-30-7. Retrieved 7 October 2014. A common programming habit is to ignore the return value from fprintf(stderr, ...