Dozens of criteria have been proposed to judge testing adequacy. Such criteria are important, as they guide automated generation efforts. Yet, the current use of such criteria in automated generation contrasts how such criteria are used by humans. For a human, coverage is part of a multifaceted combination of testing strategies. In automated generation, coverage is typically the goal, and a single fitness function is applied at one time. We propose that the key to improving the fault detection efficacy of search-based test generation approaches lies in a targeted, multifaceted approach pairing primary fitness functions that effectively explore the structure of the class under test with lightweight supporting fitness functions that target particular scenarios likely to trigger an observable failure.
This report summarizes our findings to date, details the hypothesis of primary and supporting fitness functions, and identifies outstanding research challenges related to multifaceted test suite generation. We hope to inspire new advances in search-based test generation that could benefit our software-powered society.
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Choosing the fitness function for the job: Automated generation of test suites that detect real faults
Search‐based unit test generation, if effective at fault detection, can lower the cost of testing. Such techniques rely on fitness functions to guide the search. Ultimately, such functions represent test goals that approximate—but do not ensure—fault detection. The need to rely on approximations leads to two questions—
- Award ID(s):
- 1657299
- NSF-PAR ID:
- 10461204
- Publisher / Repository:
- Wiley Blackwell (John Wiley & Sons)
- Date Published:
- Journal Name:
- Software Testing, Verification and Reliability
- Volume:
- 29
- Issue:
- 4-5
- ISSN:
- 0960-0833
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Summary Researchers and practitioners have designed and implemented various automated test case generators to support effective software testing. Such generators exist for various languages (e.g., Java, C#, or Python) and various platforms (e.g., desktop, web, or mobile applications). The generators exhibit varying effectiveness and efficiency, depending on the testing goals they aim to satisfy (e.g., unit‐testing of libraries versus system‐testing of entire applications) and the underlying techniques they implement. In this context, practitioners need to be able to compare different generators to identify the most suited one for their requirements, while researchers seek to identify future research directions. This can be achieved by systematically executing large‐scale evaluations of different generators. However, executing such empirical evaluations is not trivial and requires substantial effort to select appropriate benchmarks, setup the evaluation infrastructure, and collect and analyse the results. In this Software Note, we present our
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We recently proposed inline tests for validating individual program statements; they allow developers to provide test inputs, expected outputs, and test oracles immediately after a target statement. But, existing code can have many target statements. So, automatic generation of inline tests is an important next step towards increasing their adoption. We propose ExLi, the first technique for automatically generating inline tests. ExLi extracts inline tests from unit tests; it first records all variable values at a target statement while executing unit tests. Then, ExLi uses those values as test inputs and test oracles in an initial set of generated inline tests. Target statements that are executed many times could have redundant initial inline tests. So, ExLi uses a novel coverage-and-mutation based reduction process to remove redundant inline tests. We implement ExLi for Java and use it to generate inline tests for 718 target statements in 31 open-source programs. ExLi reduces 17,273 initially generated inline tests to 905 inline tests. The final set of generated inline tests kills up to 25.1% more mutants than developer written and automatically generated unit tests. That is, ExLi generates inline tests that can improve the fault-detection capability of the test suites from which they are extracted.more » « less
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We recently proposed inline tests for validating individual program statements; they allow developers to provide test inputs, expected outputs, and test oracles immediately after a target statement. But, existing code can have many target statements. So, automatic generation of inline tests is an important next step towards increasing their adoption. We propose ExLi, the first technique for automatically generating inline tests. ExLi extracts inline tests from unit tests; it first records all variable values at a target statement while executing unit tests. Then, ExLi uses those values as test inputs and test oracles in an initial set of generated inline tests. Target statements that are executed many times could have redundant initial inline tests. So, ExLi uses a novel coverage-then-mutants based reduction process to remove redundant inline tests. We implement ExLi for Java and use it to generate inline tests for 718 target statements in 31 open-source programs. ExLi reduces 17,273 initially generated inline tests to 905 inline tests. The final set of generated inline tests kills up to 25.1% more mutants on target statements than developer written and automatically generated unit tests. That is, ExLi generates inline tests that can improve the fault-detection capability of the test suites from which they are extracted.more » « less
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