This book presents a new paradigm of software testing by emphasizing the role of critical thinking, system thinking and rationality as the most important skills for the tester. It thus approaches software testing from a different perspective than in past literature, as the vast majority of books describe testing in the context of specific tools, automation, documentation, particular test design techniques or test management. In addition, the book proposes a novel meta-approach for designing effective test strategies, which is based on recent advances in psychology, economics, system sciences and logic. Chapter 1 starts by introducing the fundamental ideas underlying software testing. Chapter 2 then describes meta-strategies in software testing, i.e. general approaches that can be adapted to many different situations that a software tester encounters. Next, Chapter 3 presents the concept of Thinking-Driven Testing (TDT). This approach utilizes the concepts discussed in the two previous chapters and introduces the main ideas that underlie a reasonable and optimal approach to software testing. Chapter 4 builds on this basis and proposes a specific approach to testing, called TQED, that makes it possible to increase creativity in the context of delivering effective, optimal test ideas. Chapter 5 provides an overview of different types of testing techniques in order to understand the fundamental concepts of test design, while Chapter 6 details various pitfalls a tester may encounter and that can originate from a wide range of testing process areas. Lastly, Chapter 7 puts all this into practice, as it contains several exercises that will help testers develop a number of crucial skills: logical thinking and reasoning, thinking out of the box, creativity, counting and estimating, and analytical thinking. By promoting critical, rational and creative thinking, this book invites readers to re-examine common assumptions regarding software testing and shows them how to become professional testers who bring added value to their company.

Softwaretests stellen eine kritische Phase in der Softwareentwicklung dar. Jetzt zeigt sich, ob das Programm die entsprechenden Anforderungen erfüllt und sich auch keine Programmierungsfehler eingeschlichen haben. Doch wie bei allen Phasen im Software-Entwicklungsprozess gibt es auch hier eine Reihe möglicher Fallstricke, die die Entdeckung von Programmfehlern vereiteln können. Deshalb brauchen Softwaretester ein Handbuch, das alle Tipps, Tricks und die häufigsten Fehlerquellen genau auflistet und erläutert, damit mögliche Testfehler von vornherein vermieden werden können. Ein solches Handbuch ersetzt gut und gerne jahr(zehnt)elange Erfahrung und erspart dem Tester frustrierende und langwierige Trial-und-Error-Prozeduren. Chem Kaner und James Bach sind zwei der international führenden Experten auf dem Gebiet des Software Testing. Sie schöpfen hier aus ihrer insgesamt 30-jährigen Erfahrung. Die einzelnen Lektionen sind nach Themenbereichen gegliedert, wie z.B. Testdesign, Test Management, Teststrategien und Fehleranalyse. Jede Lektion enthält eine Behauptung und eine Erklärung sowie ein Beispiel des entsprechenden Testproblems. "Lessons Learned in Software Testing" ist ein unverzichtbarer Begleiter für jeden Software Tester.

Quite simply, test-driven development is meant to eliminate fear in application development. While some fear is healthy (often viewed as a conscience that tells programmers to "be careful!"), the author believes that byproducts of fear include tentative, grumpy, and uncommunicative programmers who are unable to absorb constructive criticism. When programming teams buy into TDD, they immediately see positive results. They eliminate the fear involved in their jobs, and are better equipped to tackle the difficult challenges that face them. TDD eliminates tentative traits, it teaches programmers to communicate, and it encourages team members to seek out criticism However, even the author admits that grumpiness must be worked out individually! In short, the premise behind TDD is that code should be continually tested and refactored. Kent Beck teaches programmers by example, so they can painlessly and dramatically increase the quality of their work.

Property-based testing helps you create better, more solid tests with little code. By using the PropEr framework in both Erlang and Elixir, this book teaches you how to automatically generate test cases, test stateful programs, and change how you design your software for more principled and reliable approaches. You will be able to better explore the problem space, validate the assumptions you make when coming up with program behavior, and expose unexpected weaknesses in your design. PropEr will even show you how to reproduce the bugs it found. With this book, you will be writing efficient property-based tests in no time. Most tests only demonstrate that the code behaves how the developer expected it to behave, and therefore carry the same blind spots as their authors when special conditions or edge cases show up. Learn how to see things differently with property tests written in PropEr. Start with the basics of property tests, such as writing stateless properties, and using the default generators to generate test cases automatically. More importantly, learn how to think in properties. Improve your properties, write custom data generators, and discover what your code can or cannot do. Learn when to use property tests and when to stick with example tests with real-world sample projects. Explore various testing approaches to find the one that's best for your code. Shrink failing test cases to their simpler expression to highlight exactly what breaks in your code, and generate highly relevant data through targeted properties. Uncover the trickiest bugs you can think of with nearly no code at all with two special types of properties based on state transitions and finite state machines. Write Erlang and Elixir properties that generate the most effective tests you'll see, whether they are unit tests or complex integration and system tests. What You Need Basic knowledge of Erlang, optionally ElixirFor Erlang tests: Erlang/OTP >= 20.0, with Rebar >= 3.4.0For Elixir tests: Erlang/OTP >= 20.0, Elixir >= 1.5.0

"A great mix of theory and practical examples makes this a good read for both newcomers to JavaScript/TDD and seasoned JavaScripters wanting to add to their skill set."---Jacob Seidelin, freelance web developer, Nihilogic --Book Jacket.

By taking you through the development of a real web application from beginning to end, the second edition of this hands-on guide demonstrates the practical advantages of test-driven development (TDD) with Python. You’ll learn how to write and run tests before building each part of your app, and then develop the minimum amount of code required to pass those tests. The result? Clean code that works. In the process, you’ll learn the basics of Django, Selenium, Git, jQuery, and Mock, along with current web development techniques. If you’re ready to take your Python skills to the next level, this book—updated for Python 3.6—clearly demonstrates how TDD encourages simple designs and inspires confidence. Dive into the TDD workflow, including the unit test/code cycle and refactoring Use unit tests for classes and functions, and functional tests for user interactions within the browser Learn when and how to use mock objects, and the pros and cons of isolated vs. integrated tests Test and automate your deployments with a staging server Apply tests to the third-party plugins you integrate into your site Run tests automatically by using a Continuous Integration environment Use TDD to build a REST API with a front-end Ajax interface

An engaging introduction to data science that emphasizes critical thinking over statistical techniques An introduction to data science or statistics shouldn’t involve proving complex theorems or memorizing obscure terms and formulas, but that is exactly what most introductory quantitative textbooks emphasize. In contrast, Thinking Clearly with Data focuses, first and foremost, on critical thinking and conceptual understanding in order to teach students how to be better consumers and analysts of the kinds of quantitative information and arguments that they will encounter throughout their lives. Among much else, the book teaches how to assess whether an observed relationship in data reflects a genuine relationship in the world and, if so, whether it is causal; how to make the most informative comparisons for answering questions; what questions to ask others who are making arguments using quantitative evidence; which statistics are particularly informative or misleading; how quantitative evidence should and shouldn’t influence decision-making; and how to make better decisions by using moral values as well as data. Filled with real-world examples, the book shows how its thinking tools apply to problems in a wide variety of subjects, including elections, civil conflict, crime, terrorism, financial crises, health care, sports, music, and space travel. Above all else, Thinking Clearly with Data demonstrates why, despite the many benefits of our data-driven age, data can never be a substitute for thinking. An ideal textbook for introductory quantitative methods courses in data science, statistics, political science, economics, psychology, sociology, public policy, and other fields Introduces the basic toolkit of data analysis—including sampling, hypothesis testing, Bayesian inference, regression, experiments, instrumental variables, differences in differences, and regression discontinuity Uses real-world examples and data from a wide variety of subjects Includes practice questions and data exercises