Pex-White Box Test Generation for .NET
By Nikolai Tillmann, Jonathan de Halleux. On Tap, 2008
1,002 citations recorded by the source corpus.
Subfields: Information Systems, Software
View Paper: https://www.semanticscholar.org/paper/4f789439fe5a121e6f47453d8a95ec733baca537
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The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Information Systems
In Software
Citations in the corpus
- Higher Order Mutation Testing (2009, methodology): “DSE has been used in several coverage based testing tools, such as DART [111], CUTE [241] and Pex [261].”
- A survey of the use of crowdsourcing in software engineering (2017, background): “Chen and Kim [166] investigated object mutation and constraint solving issues, underlying existing test generation tools such as jCUTE [228], Randoop [229] and Pex [230].”
- cvc5: A Versatile and Industrial-Strength SMT Solver (2022, background): “…engines for a variety of applications, including software and hardware verification [19, 52, 60, 68, 82, 86], model checking [41, 42, 98], type checking, static analysis, security [10,62], automated test-case generation [40,135], synthesis [2,65], planning, scheduling, and optimization [127].”
- A Hitchhiker's guide to statistical tests for assessing randomized algorithms in software engineering (2014, background): “, Pex [113], Randoop [93] or E v Suite [40]).”
- FairFuzz: A Targeted Mutation Strategy for Increasing Greybox Fuzz Testing Coverage (2017, neutral): “concolic testing) techniques [5, 7, 13, 16, 21, 22, 36, 45, 47].”
- EvoSuite: automatic test suite generation for object-oriented software (2011, methodology): “A popular tool for unit testing C# code is Pex [12], which generates input values for parameterized test cases using dynamic symbolic execution.”
- Guided differential testing of certificate validation in SSL/TLS implementations (2015, methodology): “Dynamic symbolic execution techniques, such as DART [29], CUTE [43], and Pex [44], improve the effectiveness of symbolic execution and random testing by dynamically analyzing the program behaviors under random testing and automatically generating new test inputs to direct the execution along…”
- Fairness testing: testing software for discrimination (2017, methodology): “Automated testing research has produced tools to generate tests, including random testing, such as Randoop [63, 64], NightHawk [4], JCrasher [20], CarFast [65], and T3 [69]; search-based testing, such as EvoSuite [29], TestFul [9], and eToc [78]; dynamic symbolic execution tools, such as DSC [37], S”
- The Art, Science, and Engineering of Fuzzing: A Survey (2018, background): “2, we intentionally omit dynamic symbolic executors such as [92], [198], [63], [49], [218], [54] because their authors did not explicitly describe their work as a fuzzer.”