How Mining ERP Processes Can Aid To Test Automation?
Enterprises that have already embraced Agile and DevOps ways of development need new approaches to test a new ecosystem of complex, highly interconnected, APIs and cloud-driven applications. Though test automation has helped a lot in speeding up the testing cycles, much more needs to be done. Identifying test scenarios, development of automation scripts and maintenance of the scripts still require human intervention. QA teams still write test scripts based on guesses of how end users are interacting with the application. Due to these reasons ensuring maximum coverage of the tests is still a bottleneck.
In this article, we’re proposing a “process-mining” based testing approach to address these challenges. With the help of process mining, user behaviour can be mined and can be used to execute and generate test cases as well as prioritizing them.
Key challenges in tradition test automation
· Test case writing based on guesswork
One of the biggest bottlenecks of traditional test automation is that testers are writing test cases based on how users are interacting with the application. Since digital transformation centres on customer experiences, testing teams are focusing on writing the test cases from a customer’s point of view. However, human inability to scan and identify patterns can lead to inadequate test coverage which can result in business disruption.
· Inadequate Test Prioritization
Another drawback with traditional test automation is that QA teams are not quite sure about the minimum number of test scripts to be run for a given code fix. Often, testers pick up smoke/regression test cases based on their experience, customer’s point of view or probably on guesswork. Thus, QA teams fail to identify tests that frequently fail. Rather than running test cases for most at-risk areas, QA teams spend time executing all the test cases, leaving behind the most critical ones.
Addressing Challenges in Traditional Test Automation with Process Mining
The overall testing effort and coverage can be improved by bringing in “Process Mining”. By mining data of critical business applications like ERP, CRM, HCM, and SCM, QA teams can easily get a detailed understanding of complex business processes. With this, they can easily address pain points in traditional test automation platform while improving test coverage, prioritizing test cases and reducing overall testing efforts.
The main idea behind using process mining is to discover, monitor and improve real processes using event logs. Critical business applications like ERP, CRM, SCM, and HCM support a wide variety of business processes. The event logs across these apps can be used to analyse the testing process. The testing processes can be improved by finding out answers of the following questions like
· How are the tests actually executed?
· How compliant are the actual test executions to the reference process?
· Where is the most time spent in the test process?
Since process mining captures the digital footprints from any number of systems throughout an organization, it will eliminate the need for hypotheses or guesswork.
· Process mining can be used to create rich dynamic visual representation of business processes.
· With this, one can visualize how transactions are executed in the test environment as well as in the production.
· The data across the test and production environment can be combined into a single database and can be analysed to highlight the discrepancies.
· QA engineers, subject matter experts and compliance analysts can use the mined data to identify the functional areas requiring more extensive test coverage.
· Another benefit of using this approach is that functional and non-functional testing libraries can be compared against each other in order to understand whether they cover the same transitions.
· Since Process Mining captures everything including date, time, user, activity and more, it can help QA teams to immediately understand the impacts of proposed process changes. Based on this, they can prioritize test cases.
Thus, transactional data can be used to visualize business processes as well as to obtain a direct representation of coverage. With Process Mining, QA teams will gain control over business processes and the need for hypotheses or guesswork while writing test cases gets eliminated. Instead, QA teams can create rich visual representation of business processes to get an unparalleled look into the functioning of business processes. Leveraging event logs, they can extract information to identify and close test coverage gaps.