DART: directed automated random testing
Proceedings of the 2005 ACM SIGPLAN conference on Programming language design and implementation
Proceedings of the 10th European software engineering conference held jointly with 13th ACM SIGSOFT international symposium on Foundations of software engineering
CUTE: a concolic unit testing engine for C
Proceedings of the 10th European software engineering conference held jointly with 13th ACM SIGSOFT international symposium on Foundations of software engineering
Mock-object generation with behavior
ASE '06 Proceedings of the 21st IEEE/ACM International Conference on Automated Software Engineering
Pex: white box test generation for .NET
TAP'08 Proceedings of the 2nd international conference on Tests and proofs
Parameterized unit testing with Pex
TAP'08 Proceedings of the 2nd international conference on Tests and proofs
Precise identification of problems for structural test generation
Proceedings of the 33rd International Conference on Software Engineering
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Achieving high structural coverage is an important goal of software testing. Instead of manually producing test inputs that achieve high structural coverage, testers or developers can employ tools built based on automated test-generation approaches, such as Pex, to automatically generate such test inputs. Although these tools can easily generate test inputs that achieve high structural coverage for simple programs, when applied on complex programs in practice, these tools face various problems, such as the problems of dealing with method calls to external libraries or generating method-call sequences to produce desired object states. Since these tools are currently not powerful enough to deal with these various problems in testing complex programs, we propose cooperative developer testing, where developers provide guidance to help tools achieve higher structural coverage. In this demo, we present Covana, a tool that precisely identifies and reports problems that prevent Pex from achieving high structural coverage. Covana identifies problems primarily by determining whether branch statements containing not-covered branches have data dependencies on problem candidates.