<p>The company’s ecosystem included a highly dynamic application and environment. Their application UI was based on Angular.js with a microservices back-end. An e-commerce application uploaded customer order files, produced a price quote, and handled invoices. They used Salesforce Data Cloud (SFDC) to review order details like shipping, billing, and handling payments. The company developed a custom back-end microservices application framework that moves customer orders through the actual product planning and production process. The image shown here illustrates the company environment.</p> <p>Prior to GSPANN's involvement, the company's development team pushed changes to its MES application modules directly to the live servers. Although a separate team handled the e-commerce and SFDC testing, there was no testing of any MES applications other than end-user acceptance testing (UAT). Since there was no formal end-to-end testing infrastructure in place, the company had no way to confirm the viability of an order from beginning to end. Even worse, no consistent documentation was available to help build the testing infrastructure.</p> <p>This approach was adequate when the company first started; however, its application production quality had declined as the business expanded. Various industry studies have shown that a bug caught in development takes significantly less time and resources to resolve compared with the amount of effort required to resolve a bug that has reached the user acceptance stage. Therefore, one of the primary objectives established by our QE team was to catch bugs early in the development process.</p> <p>Another challenge our team faced was inadequate test coverage. For instance, although the company allowed its customers to upload spreadsheet data in various formats such as Excel, CSV, TSV, or FASTA, they only performed testing for Excel. Significant gaps in test coverage were also present in the e-commerce application.</p> <p>To summarize, the company was looking for:</p> <ul> <li><strong>A solid end-to-end testing infrastructure:</strong> The company needed a testing platform to cover the front-end UI and back-end microservices. They also needed to develop Jira workflows from the ground up to build a wide-ranging test automation platform.</li> <li><strong>Comprehensive coverage:</strong> An industry-standard methodology to determine the combination of tests needed to be established along with a solid testing infrastructure to efficiently test all possible situations.</li> <li><strong>A way to catch bugs early in the development process:</strong> Initial analysis by our QE team found that 43% of the bugs originated in the development phase and 23% during integration QA testing. The remaining bugs were not discovered until they had reached UAT. Bugs need to be spotted much earlier in the development cycle to improve overall application development efficiency and quality.</li> <li><strong>The elimination of most manual processing:</strong> Both business units and the application production team performed a great deal of manual processing. This resulted in pausing of either order production or application development, which negatively impacted the company’s productivity. The company was looking for a way to automate these processes.</li> <li><strong>Lengthy delays in moving orders between stages:</strong> Each DNA synthesis product is unique and complicated to produce. In extreme cases, the company's business team had to directly call upon the application production team to move a customer order from one stage to the next. In one such example documented by our QE team, an order took three days merely to move from the supervisor to the planning stage! The company desperately needed a way to ensure that customer orders could efficiently move between stages.</li> </ul>