Big Data systems-those in which data sets grow so large that they become awkward to work with using traditional tools-are a huge problem for testers. To address the Big Data problem, testers must throw the traditional approach of creating and executing fixed test cases out the window. Ken Johnston and Reena Agarwal share how testing is changing and adapting within Microsoft on the Bing search platform and elsewhere. There, they are implementing sophisticated analysis techniques to validate system output and measure data quality. Join this leading edge session to learn what Big Data is all about and the technologies driving these new systems. Explore examples from different industries-including Big Data testing within Microsoft and Bing-and explore the new skills you and your team will need to test in the era of Big Data.

Compared to traditional functional testing, security testing requires testers to develop the mindset of real attackers and pro-actively look for security vulnerabilities throughout the software development lifecycle. Using live demos, Frank Kim shows you how to think-and act-like a hacker. Rather than just talking about issues such as Cross Site Scripting (XSS), SQL Injection, and Cross Site Request Forgery (CSRF), Frank shows-live and in color-how hackers abuse potentially devastating defects by finding and exploiting vulnerabilities in a live web application. Find out how attackers approach the problem of gaining unauthorized access to systems. Discover the tools hackers have that you don't even know exist and how you can find critical security defects in your production apps. In this revealing session, you'll learn how to become a better tester and find serious security vulnerabilities in your systems before the bad guys do.

Test data generation is an important preparatory step in software testing. It calls for a tester’s creativity as much as test case design itself. Focusing on the type of testing to be performed and designing data to support it yields the greatest success in finding defects. For example, security testing largely requires negative test data to attempt to gain access to a system as a hacker would. Localization testing requires very specific test data in the areas of date, time, and currency. Rajini Padmanaban describes how test data generation is a reverse engineering process, where one first focuses on the end goal and then works back to determine what kind of data should be created. Rajini describes data sets for various types of testing, ideas to keep in mind in reusing test data, and sharing data across the product team to save time while not trespassing on the team’s creative thinking.

What can you do when test tools from proprietary vendors don’t seem to support your organization’s processes and open source tools are too narrowly focused? Best Buy, the world's largest electronics retailer, faced this very situation. With hundreds of agile development projects running concurrently, they needed an integrated test management and test execution tool set that would scale up easily. Frank Cohen describes how he helped Best Buy integrate open source functional and load test tools, vendor-supplied test management tools, and repository tools with their agile software development methodology. Now, with this integrated solution, business managers, testers, developers, and IT Ops managers click the “Start” button to perform a thorough set of automated tests, verify the results, and produce an informative dashboard of results.