Load testing
We have already seen load testing as part of the process of performance testing and tuning. In that context, it meant constantly increasing the load on the system via automated tools. For a Web application, the load is defined in terms of concurrent users or HTTP connections. In the testing literature, the term "load testing" is usually defined as the process of exercising the system under test by feeding it the largest tasks it can operate with. Load testing is sometimes called volume testing, or longevity/endurance testing.Examples of volume testing: * testing a word processor by editing a very large document * testing a printer by sending it a very large job * testing a mail server with thousands of users mailboxes * a specific case of volume testing is zero-volume testing, where the system is fed empty tasksExamples of longevity/endurance testing: * testing a client-server application by running the client in a loop against the server over an extended period of timeGoals of load testing: * expose bugs that do not surface in cursory testing, such as memory management bugs, memory leaks, buffer overflows, etc. * ensure that the application meets the performance baseline established during performance testing. This is done by running regression tests against the application at a specified maximum load. Although performance testing and load testing can seem similar, their goals are different. On one hand, performance testing uses load testing techniques and tools for measurement and benchmarking purposes and uses various load levels. On the other hand, load testing operates at a predefined load level, usually the highest load that the system can accept while still functioning properly. Note that load testing does not aim to break the system by overwhelming it, but instead tries to keep the system constantly humming like a well-oiled machine. In the context of load testing, I want to emphasize the extreme importance of having large datasets available for testing. In my experience, many important bugs simply do not surface unless you deal with very large entities such thousands of users in repositories such as LDAP/NIS/Active Directory, thousands of mail server mailboxes, multi-gigabyte tables in databases, deep file/directory hierarchies on file systems, etc. Testers obviously need automated tools to generate these large data sets, but fortunately any good scripting language worth its salt will do the job. |