Easy Guide to Writing Regression Scripts in 3 Steps
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Regression testing is used to verify that recent upgrades or changes in the code or functionality do not have a detrimental effect on the present functionality.
During this process, testers re-execute the full or partial test cases that have already been made available to the testing team. Following the execution of these test cases numerous times, the application or software is checked to ensure that it is functioning properly. The testing team uses a number of different test cases to verify the functionality of the software. These test cases are designed based on the various aspects of the software being tested.
When testing software, it is necessary to run test cases on both old and new versions of the software to ensure that both new and old features of the product are functioning properly. The goal of regression testing, which can be done manually or with the use of a tool, is to break the code.
Writing Regression Scripts #
Developing a reliable or resilient testing script is always a difficult undertaking, whether it is for regression testing or for penetration testing purposes. When it comes to testing, testers put in more effort, and sometimes firms want experienced personnel who are skilled in both testing and development, such as DevOps. Since regression testing can be performed manually or through the use of automated tools, scripting is extremely important in this situation. Automated regression testing is performed using automated tools or platforms. As a result, learning how to develop a solid test case script is critical.
Understanding the Requirements of the Processes #
The critical problem is determining which processes should be automated and which should not. Identification of needs is a difficult task because automating too many things or the wrong thing can cause the project cost to climb significantly.
To automate the process, it is necessary to understand what type of code needs to be tested, what types of inputs must be provided, and how the application should respond to each piece of input. Once you have determined the expected input, you can test the scripts before deploying them to the production environment. Understanding the requirement is a critical stage that must be completed before any other action can be taken.
In general, automation is desired to save money, but how much money is saved depends on the basic assessments performed by the organization and the resulting actions they take. Organizations must compute their “return on investment” to be able to calculate data in greater depth. Hence, there are different ways one can understand requirements.
Choosing Python Packages for Scripting #
The scripts for regression testing are largely written in Python, which has packages in various shapes and sizes. For the most part, we can use the built-in utilities for regression testing. Packages or modules such as test or test.test support, test.regrtest, and others can be used to create regression-testing scripts. Test.regrtest is the driving force behind the testing, whereas test.test support is a contributing factor to the testing.
Although, a module unittest has its own set of guidelines. DevOps or testers must adhere to them in order to ensure that the test driver understands which techniques are being used for testing purposes. There are a few rules to follow, such as the name of the module beginning with test_ and ending with the name of the module, and the names of the methods in the module beginning with test_ and ending with what is being tested.
Writing the Scripts to Test Functions #
When creating a script, the first tester imports the python package (in this case, unittest). It is necessary to write a regression test under the PyUnit framework, and if a new test case is developed, it is added to the unittest module. Despite the fact that this test package comprises only a few modules, those whose names begin with test_ can be used to create a testing suite for a certain functionality or module.
import unittest =
from test import test_support
After importing the modules and packages, testers must define the class that will be used in the test. Classes are basically templates for the functions that the tester wants to perform on the system. Inside the class, testers are responsible for defining functions. In addition to the main function, he declares two other functions, setUp() and tearDown(). However, these methods are only declared when they are required. This means that the setUp() function will be called before each test is prepared, and the tearDown() method will be called when each test is completed.
class MyTest1(unittest.TestCase):
def setUp(self):
def tearDown(self):
def test_feature_one(self):
Now, the tester must call the main function, which serves as the program’s starting point. Alternatively, it can execute automatically as soon as the program begins, and it can manage the test execution by calling the class from within the main method.
def test_main():
test_support.run_unittest(MyTest1)
if __name__ == '__main__':
test_main()
Whole script mentioned below:
import unittest
from test import test_support
class MyTest1(unittest.TestCase):
def setUp(self):
… code to execute in preparation for tests …
def tearDown(self):
… code to execute to clean up after tests …
def test_feature_one(self):
… testing code …
def test_main():
test_support.run_unittest(MyTest1)
if __name__ == '__main__':
test_main()
To develop a script, the tester must include comments, and each line that begins with the number # is referred to as a comment. Comments are required because they ensure that test methods are properly documented.
This script is executed by the test.regrtest program. Testers must check their scripts against all possible input while writing test scripts for automation. This allows them to determine how the script dealt with incorrect data. Attempting to walk through all of the potential code pathways tells the tester how many distinct paths are feasible for the existing script.
Example #
Let’s take an example factorial program to run regression testing.
I am sure you are familiar with factorial script. Let us check how regression testing works on it.
def fact( n ):
if ( n == 0 ):
return 1.0
return fact( n - 1)*n;
if __name__ == "__main__":
for i in range(0,10+1):
print("%d! = %g"%(i,fact(i)))0! = 1
To run the above script, the tester can use Python IDE. The output of the above program will look like:
1! = 1
2! = 2
3! = 6
4! = 24
5! = 120
6! = 720
7! = 5040
8! = 40320
9! = 362880
10! = 3.6288e+06
Now, to perform regression testing, the tester will write a script that will give negative numbers to the code, causing the program to throw errors in its results.
if __name__ == "__main__":
for i in range(0,10+1):
print("%d! = %g"%(i,fact(i)))0! = 1
fact( -5 )
After execution, the output of the above program will look like:
File "factorial_v1.py", line 11, in fact
return fact( n - 1)*n;
File "factorial_v1.py", line 11, in fact
return fact( n - 1)*n;
File "factorial_v1.py", line 11, in fact
return fact( n - 1)*n;
File "factorial_v1.py", line 11, in fact
return fact( n - 1)*n;
RuntimeError: maximum recursion depth exceeded
This is a sign of infinite recursion, which is not good for the performance of a program.
Conclusion #
Automated regression testing is very good as it increases efficiency and reduces manual effort. However, it is beneficial only when test scripts are being reused; otherwise, organizations will have to pay experienced testers to develop more test scripts, increasing costs. These test scripts should not be dependent on a specific environment. Hence, writing scripts for regression testing is important and provides an error-free environment to users.