Random testing is a fundamental testing technique. Recently, we have proposed how to improve the fault-detection capability of random testing by enforcing a more even, well-spread distribution of test cases over the input domain. Such an approach is named as adaptive random testing. In this seminar, we will cover: (1) the motivation; (2) failure pattern based testing; (3) various principles that could enforce an even spread of test cases, and the advantages and disadvantages of their corresponding ART implementations; (4) comparison of random testing and adaptive random testing with respect to various testing effectiveness measures; (5) applications of ART.