Iridium Consulting’s ART methodology is fully implemented within its flagship software BackStage—a robust application framework for data transformation, validation, reconciliation, analytics, scripting, automation and testing. These capabilities of Backstage have proven to be efficient to implement automated test cases. “We have a powerful multi-threaded scheduler that allows executing the multiple steps of a test scenario—ingesting and transforming data, calculating intermediate results and comparing them with the reference, and finally deciding if it’s a pass or a fail on the testing front,” explains Chammaa. Chammaa also adds, “What differentiates BackStage from other products, is the innovative qualitative and quantitative model for deciding what to test, and this is what determines the success of a project”.
The outcome with our solutions is the highly optimized testing effort with unambiguous interpretation of results
To simplify the process, Iridium Consulting launched Backstage 2.6. The new version of Backstage drives organizations in thinking much more about what should be tested, what is the application about, what is critical to users, what changed and how to build an objective methodology that helps in deciding the area of testing and the availability of test cases to cover and mitigate the project risk.
One of the Iridium’s clients, a commercial bank wanted to upgrade their Murex software. The new version contained more than 4,000 code changes and 1,800 data-model changes. Iridium first deployed BackStage on the bank system, and later deployed the user interface on multiple desktop computers in different geographies. This enabled the bank’s technical and QA analysts working in diverse locations to access centralized data in real-time. Due to limited time and budget, Iridium implemented the ART methodology to map the functionalities and products handled by the software, and to assess the risk introduced by the new software. “The outcome with our solutions is the highly optimized testing effort with unambiguous interpretation of results,” says Chammaa.
At present, Iridium is investing heavily on analytics and machine learning to enhance the potential of its solution. In future, test cases will include more complex error and pattern detection algorithms, whereby stronger analytics are required to gain relevant insight from data for testing. “We will invest in implementing all sorts of clustering and classification techniques to make the products more relevant,” concludes Chammaa.