Even a smaller-scale Web site requires careful planning and execution of performance tests. Making the critical decisions in a timely manner and identifying the performance goals are still prerequisites to a successful test. However, smaller sites don't necessarily have the resources required to do large-scale testing, so compromises have to be made. This requires good test planning. The instructor explains the testing of a small site looking to grow, as well as the successes and pitfalls of achieving reasonable goals.

• Define the test objectives; what's reasonable?
• Plan the test then utilize tools, choices, and tradeoffs effectively
• Apply and understand the results

API testing is difficult, even with automated support. However, with traditional automated testing solutions, the cost to create and maintain a test suite can be more than the savings realized from automated test execution. By creating a model of the API to test and generating the test scripts automatically from the model, test automation becomes more cost-effective. Kirk Sayre describes how to create models of APIs; how to take the expected use of the API under test into account with Markov chains; how to augment the models with the information needed to generate automated test scripts; and how to use and interpret test results. You'll see concrete examples of automated model-based testing of APIs written in Java, PHP, and C.

• Create a model of an API for use in model-based testing
• The basics of testing using Markov chain usage models

Today's complex software systems access heterogeneous data from a variety of back-end databases. The intricate mix of client-server and Web-enabled database applications are extremely difficult to test productively. Testing at the data access layer is the point at which your application
communicates with the database. Tests at this level are vital to improve not only your overall test strategy, but also your product's quality. Mary Sweeney explains what you need to know to test the SQL database engine, stored procedures, and data views. Find out how to design effective automated tests that exercise the complete database layer of your applications. You'll learn about the most common and vexing defects related to SQL databases and the best tools available to support your testing efforts.

Testing is a never-ending series of trade-off decisions, what to test and what not to test; when to stop testing and release the product; how to budget your testing resources for automated vs. manual testing; how much code coverage is good enough; and much more. To make these difficult judgement calls, we often turn to the "best practices" recommended by testing experts and others who have encountered similar problems. The key to successful implementation is matching their "best practices" to your own context (team make-up, company culture, market
environment, etc.). Barry Preppernau shares his insights gathered from over 20 years of testing experience at Microsoft. You'll learn about the tools and processes that have been successful within Microsoft and ways for you to identify, adapt, and implement successful test improvement
initiatives within your organization.