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Monkey testing is an exploratory software testing technique where random inputs, actions, or events are applied to a system to observe how it behaves under unpredictable conditions. The goal is not to follow predefined test cases, but to uncover crashes, unhandled exceptions, or stability issues that structured testing might miss.
This approach is especially useful for identifying edge cases and robustness problems. By simulating erratic user behavior or unexpected system interactions, monkey testing helps reveal how well an application handles invalid inputs, sudden state changes, or unusual execution paths. It is commonly applied to user interfaces, mobile applications, and APIs where user behavior can be difficult to fully predict.
When combined with automation, monkey testing can be run repeatedly and at scale. Automated monkey testing tools generate large volumes of random events, increasing the likelihood of exposing rare or hard-to-reproduce issues. While it does not replace functional or regression testing, monkey testing complements them by strengthening overall system resilience.
By stressing an application in unpredictable ways, monkey testing helps teams build more robust software that can handle real-world usage scenarios with greater stability.
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