Unit testing frameworks

Noonan, Robert E.; Prosl, Richard H.

doi:10.1145/563517.563429

Cited by 5 publications

(2 citation statements)

References 2 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To help ensure the code quality of UrbanSim, we use unit tests [4,9,15] to automatically test Python classes (previously, Java classes) and their operations. The underlying assumption of existing unit test frameworks is that the unit under test has a deterministic behavior.…”

Section: Unit Testsmentioning

confidence: 99%

Automated testing of stochastic systems

Ševčíková

Borning

Socha

et al. 2006

Proceedings of the 2006 International Symposium on Software Testing and Analysis

View full text Add to dashboard Cite

Automated tests can play a key role in ensuring system quality in software development. However, significant problems arise in automating tests of stochastic algorithms. Normally, developers write tests that simply check whether the actual result is equal to the expected result (perhaps within some tolerance). But for stochastic algorithms, restricting ourselves in this way severely limits the kinds of tests we can write: either to trivial tests, or to fragile and hard-tounderstand tests that rely on a particular seed for a random number generator. A richer and more powerful set of tests is possible if we accommodate tests of statistical properties of the results of running an algorithm many times. The work described in this paper has been done in the context of a real-world application, a large-scale simulation of urban development designed to inform major decisions about land use and transportation. We describe our earlier experience with using automated testing for this system, in which we took a conventional approach, and the resulting difficulties. We then present a statistically based approach for testing stochastic algorithms based on hypothesis testing. Three different ways of constructing such tests are given, which cover the most commonly used distributions. We evaluate these tests in terms of frequency of failing when they should and when they should not, and conclude with guidelines and practical suggestions for implementing such unit tests for other stochastic applications.

show abstract

Section: Unit Testsmentioning

confidence: 99%

Automated testing of stochastic systems

Ševčíková

Borning

Socha

et al. 2006

Proceedings of the 2006 International Symposium on Software Testing and Analysis

View full text Add to dashboard Cite

show abstract

“…Such testing could be entirely batch using test scripts, interactive, or a mixture of the two. Assessment may incorporate other checks including: plagiarism detection [1], unit testing [5], test coverage, comment assessment, and code metrics.…”

mentioning

confidence: 99%

The back end of a grading system

Noonan

2006

Proceedings of the 37th SIGCSE Technical Symposium on Computer Science Education

Self Cite

View full text Add to dashboard Cite

show abstract

Oto, a generic and extensible tool for marking programming assignments

et al. 2007

View full text Add to dashboard Cite

Marking programming assignments in programming courses involves a lot of work: each program must be tested, the source code must be read and evaluated, etc. With the large classes encountered nowadays, the feedback provided to students through marking is thus rather limited, and often late. Tools providing support for marking programming assignments do exist, ranging from support for administrative aspects through automation of program testing or support for source code evaluation based on metrics. In this paper, we introduce a tool, called Oto, that provides support for submission and marking of assignments. Oto aims at reducing the workload associated with the marking task. Oto also aims at providing timely feedback to the students, including feedback before the final submission. Furthermore, the tool has been designed to be generic and extensible, so that the marking process for a specific assignment can easily be customized and the tool can be extended with various marking components (modules) that allows it to deal with various aspects of marking (testing, style, structure, etc.) and with programs written in various programming languages. Copyright © 2007 John Wiley & Sons, Ltd.

show abstract

Unit testing frameworks

Cited by 5 publications

References 2 publications

Automated testing of stochastic systems

Automated testing of stochastic systems

The back end of a grading system

Oto, a generic and extensible tool for marking programming assignments

Contact Info

Product

Resources

About