Last week, I had the opportunity to develop a new feature. It was specifically designed for cleaning up items data as their data count is erroneous due to the experiment and error logic across the application. Addressing these issues was crucial for resolving bugs in future fixes. The new feature I worked on aimed to rectify these data discrepancies. When a user clicks a designated button, the feature automatically cleans up the data.
I began by outlining the necessary tasks in Trello and understanding the database’s data flow where the data originated, where it was headed, and which parts needed cleaning. I brainstormed and devised a theoretical framework for the cleanup process.
To kickstart the project, I created a new cleanup folder within the project feature directory and defined essential CQRS components in the command and commandHandler. I meticulously determined the placement of a new service and registered it accordingly. With the fundamental groundwork in place, I concentrated on the logic required to retrieve and recalculate the data before updating them. During this brainstorming phase, I also developed the basic page layout, aligning it with the structure of the main list page. My initial draft of the logic for the clean up service consisted of a list of items that users wanted to clean up, each item paired with its corresponding data.
At this point, Mr. Peter noticed my confusion and patiently explained the key aspects I needed to understand. He emphasized the importance of using a list of Barcodes from the UI. From these Barcodes, I had to calculate the correct data and compare them. If disparities were found, the newly calculated data should overwrite the inaccurate data. Unfortunately, my progress was cut short at the end of the week, and will continue working on this task in this coming week.