An Introduction to Gorilla and Monkey Testing

Testing plays a hugely important role in the software development lifecycle. It allows developers to improve upon quality, reliability and performance, and to ensure all functions perform as they should. A large part of testing involves finding defects or bugs, and this is where Gorilla and Monkey testing come into play. An application can have thousands of bugs in its system between initial programming and release, which need to be found and rectified. These types of extensive behaviour-based testing aim to break the application under test through extensive usage and repetition, and, in doing so, to unearth unknown bugs. Although many of us have heard of these terms being used, there is a fair amount of confusion regarding the uses and difference of each. In this article, we’ll explain what Gorilla and Monkey testing are, how they differ and the advantages they offer.


What is Gorilla Testing?

Gorilla testing involves testing a module of a piece of software and pushing it to its breaking point. The name comes from the heavy-handed nature of the testing, each piece of code is tested repeatedly until it fails or gives the incorrect result. Gorilla Testing doesn’t require any test cases or test data; random data is used to test the behavior of the system when valid and invalid data is entered. The aim is to know that each module has an acceptable tolerance level before it hits breaking point.

Due to the random nature of Gorilla testing and there being no particular test strategy, a tester without knowledge of the application workflow is able to carry out the testing. That said, developers will frequently join the testers to ensure the module has been tested thoroughly. Gorilla testing ensures that each unit is thoroughly checked, with the repetitive nature of the test challenging the robustness and capability of the software. After completing Gorilla testing, developers know that the software will be able to handle even the most erratic of users. Gorilla Testing is performed during the final stages of the software release cycle to ensure all facets of the application work within their expected range.


What is Monkey Testing?

Monkey testing is a technique where the tester provides random inputs to test an application or system. The aim of the technique is to check the behaviour of the application and to check whether the system will crash. Monkey testing verifies the stability and workability of the system upon receipt of random data. Although there is some uncertainty, it is believed that the name comes from the random nature of the data input, the infinite monkey theorem. The theory being that if a monkey hits the keys of a typewriter for an infinite amount of time it will eventually type a given text. In the world of testing, the theory is that, although the monkey may eventually hit a correct value, it will also enter any number of random inputs.

To undertake Monkey testing, users enter random strings or input values into text boxes to ensure the system can handle all the possible variants. Testing involves entering negative values, abnormally large inputs and unusual characters, and falls into three main categories:

  1. Dumb Monkey Testing – testers in this scenario have no knowledge of the application they are testing and don’t know whether their entries are valid or not.
  2. Smart Monkey Testing – testers have a reasonable idea of the application and a knowledge of valid and invalid inputs that they can use to try to break the system
  3. Brilliant Monkey Testing – testers understand how the users will use the product and can carry out the testing from their perspective.

Each of these types of Monkey testing allows developers to see how the application will behave when incorrect inputs are provided and to check that the appropriate validation message or system behaviour results. A further branch of Monkey testing is push button testing where testers will repeatedly click on links to check whether an application crashes. Monkey testing is often performed by Quality Assurance engineers to catch bugs which may have been missed during regression testing.


How do Gorilla and Monkey Testing Differ?

While the two types of testing may seem similar, they actually have very different purposes. Monkey testing involves randomly trying to crash the entire system to make sure that it won’t happen once it is released. Gorilla testing, on the other hand, repeatedly tests one specific module to ensure it works properly and that there are no bugs. Monkey testing is completely random and, depending on the category of testing, can be carried out by anyone. Gorilla testing, on the other hand, requires a lot more preparation. One module is manually tested repeatedly, often over a hundred times, with the code being run over and over again to push it to breaking point.


What are the advantages of Gorilla and Monkey Testing?

The advantages of Gorilla testing is that it ensures the end program has been checked module by module. Thanks to Gorilla testing the product is well tested from all angles, it will satisfy even the most errant user, and it ensures a positive response within its tolerance levels. Gorilla testing gives developers the knowledge that the application won’t start working incorrectly or slow down after a certain number of inputs.

Monkey testing allows developers to quickly see how a program will work in the real world. It is a likely event that incorrect values will be inputted into any program. Monkey testing is easy to execute, doesn’t require highly skilled people and, as it doesn’t require detailed planning, is less expensive than many testing techniques. Although not a guarantee, there is a chance of finding out of the box errors that were not picked up during the standard testing process.

The main disadvantage of both types of testing is that they are very time-consuming. Monkey testing can continue indefinitely until a bug is found, there is no guarantee that will happen, and bug pre-production can be tricky as testers are often unaware of the steps they took to create them. Unfortunately, there are no readily available tools to perform Gorilla testing, and its manual nature means that things can be overlooked.

It’s always a good idea to know how far software can be pushed before it breaks and Gorilla and Monkey testing are ideal ways to accomplish this. Both techniques give developers insight into an application’s breaking point and allow them the opportunity to fix any issues that are unacceptable within a system’s tolerances. At a late stage in the software testing cycle, after normal testing is complete, these techniques are capable of finding issues like software failure and memory leaks. Due to this, there are far fewer chances of customers encountering issues once the application is released into the market. It is advisable to test with both Monkey and Gorilla testing methods in addition to other more strict testing processes. A play of random strength is definitely a benefit to developers and end-users alike.

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