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Journal ArticleDOI

An orchestrated survey of methodologies for automated software test case generation

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.

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Citations
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Proceedings ArticleDOI

DeepTest: automated testing of deep-neural-network-driven autonomous cars

TL;DR: DeepTest is a systematic testing tool for automatically detecting erroneous behaviors of DNN-driven vehicles that can potentially lead to fatal crashes and systematically explore different parts of the DNN logic by generating test inputs that maximize the numbers of activated neurons.
Journal ArticleDOI

A Survey on Metamorphic Testing

TL;DR: This article provides a comprehensive survey on metamorphic testing, which summarises the research results and application areas, and analyses common practice in empirical studies of metamorphIC testing as well as the main open challenges.
Book ChapterDOI

Mutation Testing Advances: An Analysis and Survey

TL;DR: This chapter presents a survey of recent advances, over the past decade, related to the fundamental problems of mutation testing and sets out the challenges and open problems for the future development of the method.
BookDOI

Deductive Software Verification - The KeY Book

TL;DR: This book is the definitive guide to KeY that lets you explore the full potential of deductive software verification in practice and contains the complete theory behind KeY for active researchers who want to understand it in depth or use it in their own work.
Proceedings ArticleDOI

Software testing: a research travelogue (2000–2014)

TL;DR: The goal of this paper is to provide an accounting of some of the most successful research performed in software testing since the year 2000, and to present what appear to be the most significant challenges and opportunities in this area.
References
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Book ChapterDOI

How to Overcome the Equivalent Mutant Problem and Achieve Tailored Selective Mutation Using Co-evolution

TL;DR: A new methodology based on co-evolutionary search techniques using Genetic Algorithms in order to address the problems of equivalent mutant detection and the large number of mutants produced is introduced.
Book

Formal Approaches to Software Testing

TL;DR: This book discusses Symbolic Test Generation, test development with Model Checking Techniques, and an Automata-Theoretic approach for Model-Checking Systems with Unspecified Components.
Proceedings ArticleDOI

A multi-objective approach to search-based test data generation

TL;DR: The results show that multi-objective evolutionary algorithms are suitable for this problem, and the way in which a Pareto optimal search can yield insights into the trade-offs between the two simultaneous objectives is illustrated.
Proceedings ArticleDOI

Strong higher order mutation-based test data generation

TL;DR: SHOM achieved higher strong mutation adequacy than two recent mutation-based test data generation approaches, killing between 8% and 38% of those mutants left unkilled by the best performing previous approach.
Proceedings ArticleDOI

Rex: Symbolic Regular Expression Explorer

TL;DR: A method and a tool, called Rex, for symbolically expressing and analyzing regular expression constraints, which is implemented using the SMT solver Z3 and provides experimental evaluation of Rex.