Pex–White Box Test Generation for .NET

Tillmann, Nikolai; Halleux, Jonathan de

doi:10.1007/978-3-540-79124-9_10

Cited by 585 publications

(637 citation statements)

References 17 publications

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“…The main component of our TCG framework is symbolic execution [12,17,19,20,23], whereby instead of on actual values, programs are executed on symbolic values, represented as constraint variables. The outcome is a set of equivalence classes of inputs, each of them consisting of the constraints that characterize a set of feasible concrete executions of a program that takes the same path and, optionally constraints, which characterize the output of the execution.…”

Section: Symbolic Executionmentioning

confidence: 99%

Test Case Generation of Actor Systems

Albert

Arenas

Gómez-Zamalloa

2015

Automated Technology for Verification and Analysis

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Abstract. Testing is a vital part of the software development process. It is even more so in the context of concurrent languages, since due to undesired task interleavings and to unexpected behaviours of the underlying task scheduler, errors can go easily undetected. Test case generation (TCG) is the process of automatically generating test inputs for interesting coverage criteria, which are then applied to the system under test. This paper presents a TCG framework for actor systems, which consists of three main elements, which are the original contributions of this work: (1) a symbolic execution calculus, which allows symbolically executing the program (i.e., executing the program for unknown input data), (2) improved techniques to avoid performing redundant computations during symbolic execution, (3) new termination and coverage criteria, which ensure the termination of symbolic execution and guarantee that the test cases provide the desired degree of code coverage. Finally, our framework has been implemented and evaluated within the aPET system.

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Section: Symbolic Executionmentioning

confidence: 99%

Test Case Generation of Actor Systems

Albert

Arenas

Gómez-Zamalloa

2015

Automated Technology for Verification and Analysis

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“…As this integration provided promising results, it should now be repeated with a state-of-art tool based on symbolic execution. Microsoft Pex [18] is a particularly appropriate candidate for integration with our work, as it is based as well on the Z3 solver. In addition, such an integration could enable a deeper comparison with the SynDB tool from [23], which is also based on Pex.…”

Section: Future Workmentioning

confidence: 99%

Relational symbolic execution of SQL code for unit testing of database programs

Marcozzi

Vanhoof

Hainaut

2015

Science of Computer Programming

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Symbolic execution is a technique enabling the automatic generation of test inputs that exercise a set of execution paths within a code unit to be tested. If the paths cover a sufficient part of the code under test, the test data offer a representative view of the actual behaviour of this code. This notably enables detecting errors and correcting faults. Relational databases are ubiquitous in software, but symbolic execution of code units that manipulate them remains a non-trivial problem, particularly because of the complex structure of such databases and the complex behaviour of SQL statements. Finding errors in such code units is yet critical, as it can avoid corrupting important data. In this work, we define a symbolic execution translating database manipulation code directly into constraints and integrate it with a more traditional symbolic execution of normal program code. The database tables are represented by relational symbols and the SQL statements by relational constraints over these symbols. An algorithm based on these principles is presented for the symbolic execution of simple Java methods that implement transactional use cases by reading and writing in a relational database, the latter subject to data integrity constraints. The algorithm is integrated in a test generation tool and experimented over sample code. The target language for the constraints produced by the tool is the SMT-Lib standard and the used solver is Microsoft Z3. The results show that the proposed approach enables generating meaningful test data, including valid database content, in reasonable time. In particular, the Z3 solver is shown to be more scalable than the Alloy solver, used in our previous work, for solving relational constraints.

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“…This idea has been implemented in tools like DART [10] and CUTE [21], and is also applied in Microsoft's parametrized unit testing tool PEX [24] or the object-oriented testing framework Symstra [30].…”

Section: Introductionmentioning

confidence: 99%

Evolutionary Generation of Whole Test Suites

Arcuri

2011

2011 11th International Conference on Quality Software

105

102

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Abstract-Recent advances in software testing allow automatic derivation of tests that reach almost any desired point in the source code. There is, however, a fundamental problem with the general idea of targeting one distinct test coverage goal at a time: Coverage goals are neither independent of each other, nor is test generation for any particular coverage goal guaranteed to succeed. We present EVOSUITE, a search-based approach that optimizes whole test suites towards satisfying a coverage criterion, rather than generating distinct test cases directed towards distinct coverage goals. Evaluated on five open source libraries and an industrial case study, we show that EVOSUITE achieves up to 18 times the coverage of a traditional approach targeting single branches, with up to 44% smaller test suites.

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Pex–White Box Test Generation for .NET

Cited by 585 publications

References 17 publications

Test Case Generation of Actor Systems

Test Case Generation of Actor Systems

Relational symbolic execution of SQL code for unit testing of database programs

Evolutionary Generation of Whole Test Suites

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