Due to the increased emphasis on computer security, great advances have been made in static analyzer tools that can detect many code errors that often elude programmers, compilers, test suites, and visual reviews. Traditional tools such as "lint" detectors are plagued with high false positive rates. Gregory Pope discusses the steps his organization used to evaluate and select a static analyzer tool and pilot its implementation. He describes how they rolled out the tool to developers and how it is being used today. Greg shares the results they achieved on real code (C, C++, and Java) and the valuable code metrics they obtained as a byproduct of its use. Greg discusses the skills needed to use the tools, ways to interpret the results, and techniques they used for winning over developers.

• The features of static code analyzers
• Defects that can be found with these tools

You've made a commitment to automate unit testing as part of your development process or you are spending precious resources for automated functional testing at higher levels. You may be asking yourself: How good are those tests anyway? Are many tests checking the same thing while large parts of the code go completely untested? Are your tests triggering the exceptions that normally show up only in production? Are your automated tests adequately covering the code, the requirements-both, neither? Andrew discusses the truths and untruths about code coverage and looks at the tools available to gather and report coverage metrics in both the opensource and commercial worlds. He describes the different types of code coverage, their advantages and disadvantages, and how to interpret the results of coverage reports.

• The concept of mutation testing and how it fits into a code coverage strategy

High quality software should be measured by the value it delivers to customers, and high quality software process should be measured by the continual flow of customer value. Modern processes have taught us that managing flow is all about the constraints restricting that flow. Testing, rather than being thought of as a conduit in that flow, is often perceived as an obstacle. It doesn't help that most testers struggle to answer the questions that their managers ask: What has and hasn't been tested? What do we need to test next? Where do we need to shift resources? If it works in the lab, why isn’t it working on those production machines? Where do we need to fix the performance or security? The ability-or inability- to answer these questions can determine the success and budget of a test team as well as how it is valued by its organization.

Test-driven development (TDD) is a new approach for software construction in which developers write automated unit tests before writing the code. These automated tests are always rerun after any codes changes. Proponents assert that TDD delivers software that is easier to maintain and of higher quality than using traditional development approaches. Based on experiences gained from real-world projects employing TDD, Peter Zimmerer shares his view of TDD's advantages and disadvantages and how the TDD concept can be extended to all levels of testing. Learn how to use TDD practices that support preventive testing throughout development and result in new levels of cooperation between developers and testers. Take away practical approaches and hints for introducing and practicing test-driven development in your organization.