If the name Monkey testing floods your brain with inquisitiveness, then this article will be very helpful to you in calming all of it. We will be telling you all about this process, which aims at testing various software for finding any possible bug that can be there in them. The simple principle of this process is: do whatever you want to; automatically.
This testing is more sporadic and includes randomness in data entry. Sometimes it is also referred to as Fuzz testing. The content of this article will exhibit all the dynamics related to this software testing method. Let us get started.
What does Monkey testing mean?
This is a method used for testing software that involves a tester entering random entries into the application software without any predefined set of checks of system behavior and test cases. This entire purpose is done to find out any error/bug that might be existing in the software with the help of exploratory techniques. It is done to check the behavior of the software and if anything can cause it to crash and what.
Some of these dynamics will help you understand the working of this method better:
- The tester or the developer carrying out the operation is referred to as the Monkey.
- There are no established checks or rules to abide by while carrying out the programming. It is based on individual choice.
- This technique mostly works on automated mode, where it takes random inputs from any script/program that it is fed with.
- The method is best suited for stress/load testing if you want to test breaking the application by entering inputs non-stop or in bulk.
- When the Monkey uses the PC, he performs the task based on personal understanding.
- Some cases of Monkey testing apply to GUI testing or Unit testing as well.
How did Monkey testing originate?
The first use of the monkey tester technique was done on Mac in 1983 to check MacPaint and MacWrite. The initial Macintosh came with a memory of 128k bytes, which could only save 90k for the other applications after dedicating the required memory to the system files. MacPaint and MacWrite used off-screen buffers to operate, which were like three times greater than the size of the screen.
This generated the necessity to check run these two apps in fewer memory conditions and see if they crash. However, it wasn’t easy to re-generate the same conditions to rerun the crash check.
Now, a program called “The Monkey” was used by the team of Steve Capps to solve this issue. This program used random data that was entered into it for the MacPaint and MacWrite apps. A good thing about this program was that it could be operated concurrently or side by side to other operations on the PC took data and performed all the actions without disturbing any other ongoing operation.
The Monkey performed swifter than any regular user-based program. All this just felt like a monkey pressing the keys randomly and swirling the mouse around clicking anywhere on the screen.
The main purpose of the program was to generate a set percentage of window events, menu clicks, and commands, etc. amongst all the random entries so that the testing could be targeted as per the requirement. As the testing apparatus, the program proved very efficient. The drawings were produced very amazingly, but the writing was gibberish.
The program was performing well at crashing the target applications. However, the drawback was that once the major fault was fixed, the program couldn’t find the other minor faults or re-find the previous ones.
What is the need for this testing?
When you bring web app software into the world, you expose it to a vast number of users across categories. Some of the users are good, but you cannot wean out the possibility of the nasty ones. The nasty users are numerous, and they behave like the monkeys who play around with the software by entering bulky or random inputs for crashing the application.
This principle is followed here too. The testers behave like a monkey while thinking and follow the rule of randomness to test the safety of the application from the other nasty monkeys.
What are the benefits of Monkey testing?
Following this method gives the testers certain advantages over the other, which are:
- 1. This is the best technique to follow if you want to remain open to the idea of discovering new and unique bugs. The testers can use any set of experienced checks and scenarios for implementing the tests. This can lead them to find unique errors that nobody can even think about and which may cause an adverse impact.
- 2. This is a good method for testing the reliability and credibility of the software.
- 3. The method comes with easy execution as random data helps better is making out random tests, which are a simple way to check any system.
- 4. Usually, this test can be carried out with the help of the less-skilled testers, but that is not the case always.
- 5. The testing proves to be less costly with the inexpensive setup and execution demands.
- 6. Certain tools help Monkey testing to run automated, which works just fine.
- 7. Another great thing is this testing can be done for the desktop, mobile as well as all the web applications.
- 8. The pre-compiled and random data can be entered for testing to check for issues related to OWASP.
- 9. Database testing is also possible with this by making a transaction and registering random data and using random action. Then the tester can roll back to see if the database has crashed or any corruption inflicted.
What are the drawbacks associated with Monkey testing?
However, there are certain loopholes in the system which make it fall a step back, which are:
- 1. The major drawback is that whatever bug is produced once; it cannot be re-generated as the random data that is entered for the testing does not allow that.
- 2. Due to the randomness, the exact test operations are not put, which cuts on the accuracy of the test results.
- 3. We know that Monkey testing doesn’t necessarily require skilled monkeys, but to have uncompromisingly accurate results, one needs to deploy greater skilled technicians in the domain.
- 4. In the absence of any previous standard checks, the testing takes longer and consumes more time for the user. The results aren’t very satisfactory either as the bugs generated are very less in number as compared to the time taken.
- 5. Other than the bugs, the testing sometimes generates unexpected outputs, which are relatively difficult to analyze and consuming even more time.
What are the different types of Monkey testing?
There are different methods of implementing this testing, which calls for its division into three different categories. They are:
Dumb monkey test
Let’s start with looking at some of the characteristics of a dumb monkey tester
- The tester does not know anything about the concept of the application or the product.
- They don’t know if the inputs they are entering are even valid or not. They are also unknown to the functionality and UI.
- And they can also be referred to as the ‘ignorant monkeys.’
This testing requires the Test lead to assign a tester for testing the product without even having any knowledge about it. The tester tests the app intuitively by entering random input as per the appropriateness he feels. In a way, the tester is not at all tech-savvy but is just trying the application software.
The data which the tester enters might just not be valid. The behavior of the application is noted then if it’s performing as per the expectations. The advantage of the dumb monkey test is that the usage of naive testers keeps the output unexpected. The aware testers might just properly put the valid data, which may fail to test conditions other than the ones they know.
Smart monkey test
A smart monkey can be characterized as:
- The tester possesses good enough or brief knowledge about the product or the system application.
- They are aware of the functionality of the product. They know where the page will get redirected to and know all the buttons and menu.
- And they enter the valid data for performing the testing. They are apt players for carrying out bulky or stress testing.
- Their main focus is to work or break the app software.
- They report the bug if they come across any significant error.
Here the task manager puts a well-aware tester to work in crashing any application. They will make smart use of random invalid data to test the target application by performing random actions. This makes testing happen faster. It is ensured that the invalid data is handled properly, and the application runs rightly as expected invalid situations.
Brilliant monkey test
The brilliant monkeys are who have the following characteristics:
- The brilliant testers have a fair amount of knowledge about the way people can use a product.
- They know all dynamics of the user behavior and can also point out the possibility of any bug emerging.
Such well aware tester is appointed by the manager to carry out the operation. These perform better than the dumb ones anytime. The end-users from real life may prove more useful as they may be using a different set of data in various sequences. They use perspectives from the real domain to test the app. The tester may be deployed to work in the specific domain of his expertise.
How to analyze the results from Monkey testing?
The bugs that are generated require detailed analysis because reproducing the bugs is not easy, and the steps to do it are unknown sometimes. The apt time to use this test technique can be at the last stages of the entire operation of testing all the functionalities, and once the app is proved to be effective. If done at the beginning, there is a higher risk involved. Using a script or program that uses both valid as well as invalid random data inputs makes the analysis easier.
What are some other competent tests for Monkey testing?
This software tester is used for a module of any program which is tested repeatedly for ensuring its proper working and bug-free operation. Tests can be run for more than a hundred times through the module and that too in a similar way every time. This test isn’t either random or predefined. It can only be used for exclusive modules with some test checks.
Monkey testing is regarded as a sub-type of this testing. The tester who performs it is aware of the software, and it’s working. This testing is done without any prep and without taking any test case or SRS into consideration. The main purpose of this is to divide the application into sub-parts randomly and then check their operation if it crashes or not.
Are there any tools that help Monkey testing?
Yes, there are a number of tools that automatize Monkey testing and help it run efficiently. They generate random or pre-populated data and then insert them into the software. They also perform random actions and observe whatever the outcome be. These tools take some time to set up but once done; they perform testing very efficiently. This is the basic process to follow while using any such tool:
- The prime step, like for any general tool, is to register the software with the particular dedicated server.
- You must be ready with all the required references to build the test suite.
- Run the testing suit then.
- A log file of the test will be created with the name “Monkey test,” which will record all the test results generated.
- You need to remember that the testing will continue to run until the system reaches the crash point. It is here that the final action is reported and saved in the log file.
- The final step occurs when the concerned tester sees the final report for observation. This data can be saved for any future reference.
Monkey testing tools for Android
MonkeyRunner is a tool that can be used for testing any Android application. With the help of python programming, the tool can install and execute any program, send data, take screenshots, and save it on the PC. It is devised for functional and framework testing and can also do random tests.
Monkey UI/Application exerciser for Android
It is different from the tool and generates user and system events for any random pseudo stream. This exerciser runs on the inside of the emulator or the device in the ADB shell.
Monkey testing has yet not sunken well with the software industry as it’s a newcomer and still competing with the better and more cost-effective testing methods. It would be better to perform other tests and stabilize the application before resorting to Monkey testing. It is nonetheless advantageous for discovering new bugs and nastier situations and achiever better results. With better planning, it can give better results.