On some reliability estimation problems in random and partition testing

Abstract

Random testing is receiving increasing attention in recent years. Aside from its relative simplicity and low cost, studies have shown that random testing is an effective testing strategy. An advantage of random testing is that the reliability of the program can be estimated from the test outcomes. The authors extend the Thayer-Lipow-Nelson reliability model to account for the cost of errors. They also compare random with partition testing by looking at upper confidence bounds for the cost weighted performance of the two strategies.<>