STRATEGIES TO IMPROVE EFFECTIVENESS OF TEST AUTOMATION & ROI

In today’s era, most of the enterprises and QA managers are adoptingautomation testing to speed up the test time to market and therebyenhancing the software quality. Automated testing tools are capable ofexecuting the test cases, reporting the outcomes and comparison ofresults with the previous test runs. Tests that are once carried out withthese tools can be run repeatedly. But one thing to be considered is thatall the test automation projects do not deliver expected ROI and success.The reason could be utilization of wrong test practices. The testersimplement the test automation tools even if they are not aware of theright procedures which reduces the effectiveness of test automation.

A robust mobile test automation approach can help the companies to testquickly and effectively. At the same time, a poorly designed approach canseriously put a negative impact on the productivity and ROI. So, maximuminvestments can be made from test automation and also test automationeffectiveness, ROI can be increased if the following strategies are kept inmind from the very beginning:

SELECTION OF THE RIGHT TEST CASES TO

AUTOMATE

Mobile application testing involves the test cases that get repeatedacross different platforms, devices and networks. For successful testautomation, identification of the right test cases to automate isessential. Some of the ideal cases are:

i) Cross platform test cases

ii) Test cases that use large amount of input data

iii) Repetitive test cases

iv) Test cases that deal with complex business logic

v) Test cases that require multiple users

PRIORITIZATION OF THE TASKS

After the selection of the tests that are to be automated, you can go forthe prioritization and division of the tests. With the help of this, theoutcome can be estimated that one wishes to achieve through testautomation and accordingly the actions can be planned. You can setyour priorities in terms of the complication of the tasks. Then the taskscan be divided in an efficient manner in order to meet the specifiedtime limit. Every team member possess different skills and experience.The tests that are beneficial for automation should be identified first.

PREPARATION OF THE TEST CASES

Before stating test automation, you should create test scenarios andtest cases. This will let you know the execution time and defects inadvance. This will bring more scenarios into effect if you have missedand helps you understand the workflow of the application.

TEST PROCESS

Before jumping into test automation, the process of executionshould be prepared so that the suitable resources can be allocatedto discover probable risks before hand. Identifying the test processwill bring the best methods to perform the task effectively andefficiently.

CREATE STABLE TEST

The test scripts that are usually created get changed with respect to the UIchanges in terms of functional aspects. Due to this, such test scripts maynot work well for the successive versions of the application. Therefore,the tests should be created in a way that they remain unaffected by the UIchanges. It would eliminate the need for making frequent changes andkeep the automated tests work smoothly.

DO NOT AUTOMATE EVERYTHING

The automation testers often try to automate each and everythingfor more application coverage that results in millions of testcombinations. If all these test cases are to be executed, it wouldresult in increased efforts and costs. Sometimes, for certaincomplex scenarios, manual testing is required as automationtesting cannot bring out expected results in such cases.

REVIEW TESTS

The test data and test cases should be reviewed after certainintervals to keep a check on their validity for tests. Reviewing helpsto eliminate the old and outdated tests that are irrelevant to thecurrent test requirements which ultimately helps in reducing thecosts and efforts.

QUALITY OF TEST DATA

Test data quality plays a major role in the process of testautomation. For successful automation quality test data is of primeimportance. Quality data set refers to categorization of data setsinto valid data, invalid data or boundary condition etc. One needsto make sure that the data being used for testing is not obsoleteand is updated from time-to-time for accuracy.