This paper is concerned with performance debugging of multi-tier applications, such as commonly found in servers and dynamic-content web sites. Existing tools and techniques for profiling such applications are not general enough to track and profile transactions in a generic multi-tier application. We propose transactional profiling that provides a general solution to this problem. We provide novel algorithms and techniques to track and profile transactions that flow through shared memory, events, stages or via interprocess communication using messages. We also measure interference among concurrent transactions.

A new strategy for the generation of test vectors for testing large sequential machine has been proposed. The fault model assumed is the single state transition (SST) fault model where a fault corrupts the destination state of exactly one transition of the machine, the rest of the transitions being unaffected. The strategy takes into consideration the behaviour of the machine under test and generates a set of test vectors. The main contribution of this paper is that it creates an ordering of the test vectors generated, if these test vectors are applied in the same order during testing, it maximizes the fault coverage in the least possible time with high probability. Also this approach reduces the traversal space of the machine under test by eliminating a set of transitions where the chance of detecting an existing fault is poor. The approach also ensures that the test vectors are such that when applied for testing they do not result in the repeated traversal of the same part of the machine. This helps in reducing the time of testing without compromising the extent of fault coverage of the testing procedure.