Software testing checks whether a program implementation agrees with a program specification. Without a specification, there is nothing to test. Testing is a form of consistency checking between implementation and specification.
- Automated testing:
- Finds bugs more quickly
- No need to write tests
- if software changes, no need to maintain tests
- Manual testing:
- Efficient test suites
- Potentially better code coverage
- Black-box testing:
- Can work with code that cannot be modified
- Does not need to analyze or study code
- Code can be in any format
- White-box testing:
- Efficient test suite
- Better code coverage
- pre-condition - a predicate assumed to be true before a function executes
- post-condition - a predicate expected to be true after a function executes, whenever a pre-condition holds
Pre and post-conditions are most useful if they are executable and written in the same programming language as the program under test. These conditions are a special case of assertions. Pre and post-conditions don't have to be precise, otherwise they might become more complex than the program under test.
Summarily, we check to see if a pre-condition holds prior to executing a test If not, the test fails. Next we execute the function with the inputs defined by the pre-condition, checking to see if the post-condition is true based upon the output of the function. If we detect deviation from the post-condition, the test fails. Else, the test succeeds and we move onto the next test case.
Code coverage is a metric to quantify the extent to which a program's code is tested by a given test suite. Code coverage is quantified as a percentage of some aspect of the program executed in the tests. Some of the most popular types of code coverage can be found below:
- Function coverage - what percentage of functions were called?
- Statement coverage - what percentage of statements were executed?
- Branch coverage - what percentaged of branches were taken?
Mutation analysis is founded on the "competent programmer assumption" - the program is close to right to begin with and the existing bugs are minor. The key idea behind mutation analysis is to test mutants of the program to determine if the test suite is good. If the test suite is good, mutants should fail the tests because their code is incorrectly mutated. If a test suite is unsound, it will accept mutants - we must continue to add test cases to the test suite to distinguish mutants from the original program.