Data Analytics & Software Test Automation Synergy

Jun 21, 2022 | Blogs

Can Data Analytics Find Its Application In Software Test Automation?

 

The Ever-Evolving Testing Market

Currently, around the globe, the organizational processes have been evolving with the adoption of newer technologies and the addition of extended support with Artificial Intelligence and Machine Learning has indeed accelerated the software development in hybrid systems. The high performance, reliability, and quality of such systems need to be assured of quality and stability in the market, and that is where the Software Testing plays a vital role. With the automation of Test tools and processes, the results obtained are much faster and with fewer human errors. Many Testing processes/concepts are being out to use that could reduce the Tester’s efforts significantly. At present, the test scripts or test case generation could be carried out rapidly by just click of a button, driven by only backend code. Hence the focus of tester is leveraged from manually writing the test cases for an application to analysing how the test cases can be optimized and thereby providing more time for testers in dealing with requirements mapping with output test results. The testing environment has indeed levelled up and the present-day evolving technologies implementation has really put software testing at the core!

 

The Present State Of Data Analytics

Data Analytics, the most fundamental concept in the vast ocean study of Data Science, has found its place and demand in all the sectors of the global work process. Application of the data analytics concept has helped many industries to develop higher standards in work and have exponential progress. In today’s fast pace of technology evolution, it has been necessary to have data analysis in every stage to achieve high efficiency and clarity in data communication. The present global market involving the hybrid nature of system construction has been extensively finding dependency on having Data which is in a form that can help better progress. The data to be made available in an interpretable format which levels up competition in the market, makes Data analytics a key aspect, and this has been evidently and extensively found in the global IT domain. 

 

Does Data Analytics Have A Role In Software Testing?

In Software Testing, there is always scope for analysis either on the input side or at the output end. The test results generated after covering all the requirements and testing targets given by clients as well as developed by our testing tool itself will define the project success. But in this process, much analysis is required, and testers require certain support means that can provide an ease in their testing environment. The ease and convenience to the Tester can be provided by implementing certain means that could provide quick answers to Tester questions such as whether the given requirements make sense? Does generating extensive test cases required? Can it be optimized? Could some means provide insights on how to proceed further for a particular scenario or what kind of testing to consider? How to stop the appearance of the same type of bugs? Are there any means to develop a faster decision-making process? Can we have a better representation of outcomes to the Client?. .and thus, this is where Data Analytics is helpful. 

 

Requirement Of Analyzing the Data

The testing technology has also shown increased growth such that with just a click of a button, we can now generate hundreds of test cases in the least seconds possible. But this doesn’t mean we go on developing the test cases insensibly, as it is essential to optimize the test results and make it more accurate. Also, equally important is the right and accurate requirements that helps the testers in validating the process to map the test results generated against the clients test targets for further work process. To carry out all these stages of the workflow, it is crucial to have Data Analysis. As a result, Data Analytics has found its space in the testing domain, and an appreciable help has been provided for testers to undergo the right amount of testing with reduced time, cost, and effort.

 

How Does Conformiq Implement Data Analysis In Software Testing?

Conformiq leverages Creator, a Test Automation tool used for modelling the applications and generating test cases. Here, it is essential to have the test cases enclosing all the aspects of the application to which an end-user can reach out. Each element of application beginning with Start button to close button, the different areas the user can explore, all such possible areas must be covered in test cases generated. To carry out this task, the Conformiq Creator makes sure primarily, that the time for generating the test cases which covers all possible areas of application is least and testers get more time in analyzing the test cases. The analysis is carried out seamlessly in ‘Test Review’ perspective and this perspective defines the application of Data Analytics.

One of the important aspect of Data Analytics is Data visualization. In addition to analysing the data, it is also important to have proper visualization platform that encloses all the analysis part in a simple and easier way. Hence, the Conformiq Creator encloses a ‘Model Browser’ view that takes care of the visualization process, and thus lending a great help for testers as well as to clients in understanding the user’s coverage flow. This coverage flow view gives insight into the possible ways the user could use the application. With the help of this view, it is easier to interpret the discrepancies or issues the user could face when working on the application.

Data Analytics widely makes use of color-coding technique, and this had been an essential factor in the analysis process helping to interpret the data better and in making proper decisions. Conformiq Creator also makes use of this technique in its own way which helps the testers as well as the clients to interpret the application model better, to have verification of each step of test case generated and provides insights about optimization process.

Thus, the ‘Test Review’ perspective within Creator makes use of analytics concepts to undergo analysis on model, the test steps, the requirements, the test targets coverage and help tester to map client requirements and proceed accordingly, where they can either opt for re-modelling and regeneration of test cases or directly progress for test script generation in the format demanded by the users. In fact, the use of Model Based Testing immensely helps with an intuitive and user-friendly representation of application. The basic process of creating models of application with GUI elements itself provides a good representation of application data and this representation forms a significant aspect in Test review perspective making analysis process easier and simpler to both the testers and the users.

 

Conclusion

The field of Data Analytics has been fast growing. The way in which we make use of Data Analytics differ in each field of global market. The traditional way of using the data analysis that involves cleaning of data, organizing the data, formatting the data for business representations cannot be extended to all the working domains in the same way, although the concept of data cleaning, organizing, or formatting can be used in various ways and these concepts form the key elements of data analysis. The current market is trying to bring out the best results from this data analysis process, but still, how best this process can be incorporated and have a very simplified process is yet a futuristic scope. Data analytics and software testing complement each other for better development and upgradation in their respective fields. The data analysis helps the Tester in making faster decisions in the testing process for optimization and reduces both human effort and time. In a nutshell, wherever the analysis is required, and the necessity exists, in fact, even during the times where there is a need to make the entire analysis process itself better so that we progress in a better way, have a better testing environment, data analytics comes into play.