Jartege: A Tool for Random Generation of Unit Tests for Java Classes

Oriat, Catherine

doi:10.1007/11558569_18

Cited by 76 publications

(55 citation statements)

References 30 publications

(34 reference statements)

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“…Instead of deriving test cases from the UML activity diagram directly, we present an indirect approach which selects the test cases from the set of the randomly generated test case according to a given activity diagram. By using the method similar to [6], we first randomly generate abundant random test cases. Then, by running the program with these test cases, we can get the corresponding program execution traces.…”

Section: Introductionmentioning

confidence: 99%

Automatic test case generation for UML activity diagrams

Chen

Qiu

2006

Proceedings of the 2006 International Workshop on Automation of Software Test

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The test case generation from design specifications is an important work in testing phase. In this paper, we use UML activity diagrams as design specifications, and present an automatic test case generation approach. The approach first randomly generates abundant test cases for a JAVA program under testing. Then, by running the program with the generated test cases, we can get the corresponding program execution traces. Last, by comparing these traces with the given activity diagram according to the specific coverage criteria, we can get a reduced test case set which meets the test adequacy criteria. The approach can also be used to check the consistency between the program execution traces and the behavior of UML activity diagrams.

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Section: Introductionmentioning

confidence: 99%

Automatic test case generation for UML activity diagrams

Chen

Qiu

2006

Proceedings of the 2006 International Workshop on Automation of Software Test

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“…For evaluating the efficiency and effectiveness, we compared ADFD+ with Randoop, following the common practice of comparison of the new tool with a mature random testing tool [6]- [8]. Testing of several error-seeded one and two-dimensional numerical programs was carried out as per program code [4].…”

Section: Discussionmentioning

confidence: 99%

ADFD+: An Automatic Testing Technique for Finding and Presenting Failure Domains

Ahmad¹,

Manuel²

2014

LNSE

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“…A test method contains one tested method call, a sequence of constructor calls or method calls that set up the states of the input objects, and several assertions about the result of the tested method call [23]. To generate such JUnit test cases, ARTGen involves several steps:…”

Section: Art Test Case Generation Techniquementioning

confidence: 99%

A Divergence-Oriented Approach to Adaptive Random Testing of Java Programs

Lin

Tang

Chen

et al. 2009

2009 IEEE/ACM International Conference on Automated Software Engineering

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Abstract-Adaptive Random Testing (ART) is a testing technique which is based on an observation that a test input usually has the same potential as its neighbors in detection of a specific program defect. ART helps to improve the efficiency of random testing in that test inputs are selected evenly across the input spaces. However, the application of ART to objectoriented programs (e.g., C++ and Java) still faces a strong challenge in that the input spaces of object-oriented programs are usually high dimensional, and therefore an even distribution of test inputs in a space as such is difficult to achieve. In this paper, we propose a divergence-oriented approach to adaptive random testing of Java programs to address this challenge. The essential idea of this approach is to prepare for the tested program a pool of test inputs each of which is of significant difference from the others, and then to use the ART technique to select test inputs from the pool for the tested program. We also develop a tool called ARTGen to support this testing approach, and conduct experiment to test several popular opensource Java packages to assess the effectiveness of the approach. The experimental result shows that our approach can generate test cases with high quality.

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Jartege: A Tool for Random Generation of Unit Tests for Java Classes

Cited by 76 publications

References 30 publications

Automatic test case generation for UML activity diagrams

Automatic test case generation for UML activity diagrams

ADFD+: An Automatic Testing Technique for Finding and Presenting Failure Domains

A Divergence-Oriented Approach to Adaptive Random Testing of Java Programs

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