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Unit tests are widely used to check source code quality, but they can be too coarse-grained or ill-suited for testing individual program statements. We introduce inline tests to make it easier to check for faults in statements. We motivate inline tests through several language features and a common testing scenario in which inline tests could be beneficial. For example, inline tests can allow a developer to test a regular expression in place. We also define language-agnostic requirements for inline testing frameworks. Lastly, we implement I-Test, the first inline testing framework. I-Test works for Python and Java, and it satisfies most of the requirements. We evaluate I-Test on open-source projects by using it to test 144 statements in 31 Python programs and 37 Java programs. We also perform a user study. All nine user study participants say that inline tests are easy to write and that inline testing is beneficial. The cost of running inline tests is negligible, at 0.007x -- 0.014x, and our inline tests helped find two faults that have been fixed by the developers.
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This content will become publicly available on April 10, 2027
Block Tests
Inline tests validate single program statements and were shown to find single-statement bugs or kill mutants that unit tests miss. Inline tests complement unit tests by enabling testing at a finer program granularity level than methods. So, inline tests can more easily find faults in target statements that unit tests do not reach, or where errors do not propagate to unit tests’ oracles. But, the limitation to single statements means inline tests cannot validate data or control flow across code fragments—sequences of multiple statements in a method. We motivate the need for testing arbitrary fragments and propose block tests, which generalize inline tests and validate code fragments. To motivate, we discuss six software testing needs (e.g., due to increasing usage of lambdas in imperative code) for which unit tests are too coarse grained and inline tests are too fine grained. To bridge this gap, we propose syntax and semantics for specifying inputs, expected outputs, and scope of block tests. We also implement a block-test development kit (BDK) for writing and running block tests in Java. We evaluate block tests and BDK in two ways. First, we write 1,012 block tests for 346 fragments in 146 open-source projects. Developer written unit tests do not cover 58.7% of these fragments, and automated unit-test generation does not reach 46% of them even after 30.8 CPU days. But, each block test takes us 2.2 minutes to write and 0.9 seconds to run on average. Second, we use mutation testing to evaluate the fault-finding effectiveness of block tests in fragments that unit tests cover. Block tests kill 4,418 of 9,554 mutants that survived unit tests. These results provide initial but strong evidence on block tests’ feasibility and utility. We outline an agenda for future research on block testing.
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- PAR ID:
- 10677096
- Publisher / Repository:
- IEEE/ACM
- Date Published:
- Journal Name:
- Proceedings of the ACM on Programming Languages
- Volume:
- 10
- Issue:
- OOPSLA1
- ISSN:
- 2475-1421
- Page Range / eLocation ID:
- 2044 to 2072
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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