From the Back Cover
"If you'd like a glimpse at how the next generation is going to program,this book is a good place to start."Gregory V. Wilson,Dr. Dobbs Journal (October 2004)Build YourOwn Automated Software Testing Tool
Whatever its claims,commercially available testing software is not automatic. Configuring it to testyour product is almost as time-consuming and error-prone as purely manualtesting.
There is an alternative that makes both engineering andeconomic sense: building your own, truly automatic tool. Inside, you’lllearn a repeatable, step-by-step approach, suitable for virtually any developmentenvironment. Code-intensive examples support the book’s instruction, whichincludes these key topics:
Effective Software TestAutomation
- Conducting active softwaretesting without capture/replay
- Generating a script to test all members of oneclass without reverse-engineering
- Using XML to store previously designedtesting cases
- Automatically generating testing data
- Combining Reflectionand CodeDom to write test scripts focused on high-risk areas
- Generating testscripts from external data sources
- Using real and complete objects forintegration testing
- Modifying your tool to test third-party softwarecomponents
- Testing your testing tool
goes well beyond the building of your own testing tool: it alsoprovides expert guidance on deploying it in ways that let you reap the greatestbenefits: earlier detection of coding errors, a smoother, swifter developmentprocess, and final software that is as bug-free as possible. Written forprogrammers, testers, designers, and managers, it will improve the way your team works and the quality of its products.
About the Author
Kanglin Li is a software engineer responsible for software development, testing, and deployment at Communication Data Services. He has developed applications in Basic, Pascal, C++, Java, Visual Basic, and C#. Li taught at North Carolina A&T State University as an assistant professor and is the author of 14 journal articles and technical papers. He has a B.S degree in Agronomy, an M.S. degree in computer science, and a Ph.D. degree in soil physics and statistics.