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This book reviews recent advances in symbolic execution and its probabilistic variant and discusses how they can be used to ensure the safety and security of software systems. Symbolic execution is a systematic program analysis technique which explores multiple program behaviors all at once by collecting and solving symbolic constraints collected from the branching conditions in the program. The obtained solutions can be used as test inputs that execute feasible program paths. Symbolic execution has found many applications in various domains, such as security, smartphone applications, operating systems, databases, and more recently deep neural networks, uncovering subtle errors and unknown vulnerabilities. We review here the technique has also been extended to reason about algorithmic complexity and resource consumption.Furthermore, symbolic execution has been recently extended with probabilistic reasoning, allowing one to reason about quantitative properties of software systems. The approach computes the conditions to reach target program events of interest and uses model counting to quantify the fraction of the input domain satisfying these conditions thus computing the probability of event occurrence. This probabilistic information can be used for example to compute the reliability of an aircraft controller under different wind conditions (modeled probabilistically) or to quantify the leakage of sensitive data in a software system, using information theory metrics such as Shannon entropy.This book is intended for students and software engineers who are interested in advanced techniques for testing and verifying software systems.

This book summarizes the current hard problems in software testing as voiced by leading practitioners in the field. The problems were identified through a series of workshops, interviews, and surveys. Some of the problems are timeless, such as education and training, while others such as system security have recently emerged as increasingly important. The book also provides an overview of the current state of Testing as a Service (TaaS) based on an exploration of existing commercial offerings and a survey of academic research. TaaS is a relatively new development that offers software testers the elastic computing capabilities and generous storage capacity of the cloud on an as-needed basis. Some of the potential benefits of TaaS include automated provisioning of test execution environments and support for rapid feedback in agile development via continuous regression testing. The book includes a case study of a representative web application and three commercial TaaS tools to determine which hard problems in software testing are amenable to a TaaS solution. The findings suggest there remains a significant gap that must be addressed before TaaS can be fully embraced by the industry, particularly in the areas of tester education and training and a need for tools supporting more types of testing. The book includes a roadmap for enhancing TaaS to help bridge the gap between potential benefits and actual results. Table of Contents: Introduction / Hard Problems in Software Testing / Testing as a Service (TaaS) / Case Study and Gap Analysis / Summary / Appendix A: Hard Problems in Software Testing Survey / Appendix B: Google App Engine Code Examples / Appendix C: Sauce Labs Code Examples / References / Author Biographies

Smartphone users have come to expect high-quality apps. This has increased the importance of software testing in mobile software development. Unfortunately, testing apps-particularly the GUI-can be very time-consuming. Exercising every user interface element and verifying transitions between different views of the app under test quickly becomes problematic. For example, execution of iOS GUI test suites using Apple's UI Automation framework can take an hour or more if the app's interface is complicated. The longer it takes to run a test, the less frequently the test can be run, which in turn reduces software quality. This book describes how to accelerate the testing process for iOS apps using HadoopUnit, a distributed test execution environment that leverages the parallelism inherent in the Hadoop platform. HadoopUnit was previously used to run unit and system tests in the cloud. It has been modified to perform GUI testing of iOS apps on a small-scale cluster-a modest computing infrastructure available to almost every developer. Experimental results have shown that distributed test execution with HadoopUnit can significantly outperform the test execution on a single machine, even if the size of the cluster used for the execution is as small as two nodes. This means that the approach described in this book could be adopted without a huge investment in IT resources. HadoopUnit is a cost-effective solution for reducing lengthy test execution times of system-level GUI testing of iOS apps.

This book discusses how model-based approaches can improve the daily practice of software professionals. This is known as Model-Driven Software Engineering (MDSE) or, simply, Model-Driven Engineering (MDE).MDSE practices have proved to increase efficiency and effectiveness in software development, as demonstrated by various quantitative and qualitative studies. MDSE adoption in the software industry is foreseen to grow exponentially in the near future, e.g., due to the convergence of software development and business analysis.The aim of this book is to provide you with an agile and flexible tool to introduce you to the MDSE world, thus allowing you to quickly understand its basic principles and techniques and to choose the right set of MDSE instruments for your needs so that you can start to benefit from MDSE right away.The book is organized into two main parts.The first part discusses the foundations of MDSE in terms of basic concepts (i.e., models and transformations), driving principles, application scenarios, and current standards, like the well-known MDA initiative proposed by OMG (Object Management Group) as well as the practices on how to integrate MDSE in existing development processes.The second part deals with the technical aspects of MDSE, spanning from the basics on when and how to build a domain-specific modeling language, to the description of Model-to-Text and Model-to-Model transformations, and the tools that support the management of MDSE projects.The second edition of the book features:a set of completely new topics, including: full example of the creation of a new modeling language (IFML), discussion of modeling issues and approaches in specific domains, like business process modeling, user interaction modeling, and enterprise architecturecomplete revision of examples, figures, and text, for improving readability, understandability, and coherencebetter formulation of definitions, dependencies between concepts and ideasaddition of a complete index of book contentIn addition to the contents of the book, more resources are provided on the book's website http://www.mdse-book.com, including the examples presented in the book.

The cost of fixing software design flaws after the completion of a software product is so high that it is vital to come up with ways to detect software design flaws in the early stages of software development, for instance, during the software requirements, the analysis activity, or during software design, before coding starts. It is not uncommon that software requirements are ambiguous or contradict each other. Ambiguity is exacerbated by the fact that software requirements are typically written in a natural language, which is not tied to any formal semantics. A palliative to the ambiguity of software requirements is to restrict their syntax to boilerplates, textual templates with placeholders. However, as informal requirements do not enjoy any particular semantics, no essential properties about them (or about the system they attempt to describe) can be proven easily. Formal methods are an alternative to address this problem. They offer a range of mathematical techniques and mathematical tools to validate software requirements in the early stages of software development. This book is a living proof of the use of formal methods to develop software. The particular formalisms that we use are EVENT B and refinement calculus. In short: (i) software requirements as written as User Stories; (ii) they are ported to formal specifications; (iii) they are refined as desired; (iv) they are implemented in the form of a prototype; and finally (v) they are tested for inconsistencies. If some unit-test fails, then informal as well as formal specifications of the software system are revisited and evolved. This book presents a case study of software development of a chat system with EVENT B and a case study of formal proof of properties of a social network.