Journal ArticleDOI
An orchestrated survey of methodologies for automated software test case generation
Saswat Anand,Edmund K. Burke,Tsong Yueh Chen,John A. Clark,Myra B. Cohen,Wolfgang Grieskamp,Mark Harman,Mary Jean Harrold,Phil McMinn +8 more
TLDR
An orchestrated survey of the most prominent techniques for automatic generation of software test cases, reviewed in self-standing sections, aimed at giving an introductory, up-to-date and (relatively) short overview of research in automatic test case generation.About:
This article is published in Journal of Systems and Software.The article was published on 2013-08-01. It has received 599 citations till now. The article focuses on the topics: Software reliability testing & Test strategy.read more
Citations
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Proceedings ArticleDOI
EvoSE: evolutionary symbolic execution
TL;DR: Preliminary evaluation shows that EvoSE outperforms state-of-the-art SE search strategies when targeting specific code elements, and an evolutionary algorithm that searches the program control flow graph for symbolic paths that traverse the minimum number of unsatisfiable branch conditions.
Journal ArticleDOI
Toward testing from finite state machines with symbolic inputs and outputs
TL;DR: This paper addresses the issue of inclusion of assignments in the model complicates even output fault detection, as different assignments may produce the same output valuations for some input valuations, by using a transition cover composed of symbolic inputs on which the assignments produce different outputs.
Posted Content
How to Kill Symbolic Deobfuscation for Free; or Unleashing the Potential of Path-Oriented Protections
TL;DR: This work presents and studies a new class of anti-DSE protections coined as path-oriented protections targeting the weakest spot of DSE, namely path exploration, and demonstrates that these approaches critically counter symbolic deobfuscation while yielding only a very slight overhead.
Book ChapterDOI
Dependable Neural Networks for Safety Critical Tasks
TL;DR: In this article, the authors propose a metric, Machine Learning Dependability, that measures the network's probability of success in specified operating conditions which need not be the testing conditions. But these techniques fail to predict how a trained model will perform when the operating conditions differ from the test conditions.
Proceedings ArticleDOI
Generation of in-bounds inputs for arrays in memory-unsafe languages
TL;DR: A technique to generate in-bounds inputs for arrays used in memory-unsafe programming languages, such as C and C++ and how symbolic range analysis can be used to establish contracts between the arguments of a function and the arrays used within that function is presented.
References
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Book ChapterDOI
Z3: an efficient SMT solver
TL;DR: Z3 is a new and efficient SMT Solver freely available from Microsoft Research that is used in various software verification and analysis applications.
Book
Software Product Lines: Practices and Patterns
Paul Clements,Linda Northrop +1 more
TL;DR: The Three Essential Activities: Core Asset Development, Software Engineering Practice Areas, and Single-System Development with Reuse - All Three Together.
Proceedings ArticleDOI
KLEE: unassisted and automatic generation of high-coverage tests for complex systems programs
TL;DR: A new symbolic execution tool, KLEE, capable of automatically generating tests that achieve high coverage on a diverse set of complex and environmentally-intensive programs, and significantly beat the coverage of the developers' own hand-written test suite is presented.