
Sandaru contributed to the GetCodifyAI/cut-dry-automation-framework and cut-dry-ui-automation-restaurant repositories by building and enhancing order management, catalog usability, and automated testing workflows. Using Java, Selenium, and XML, Sandaru implemented features such as catalog tagging, sorting, and offline order processing, while improving UI flows for order guides and customer orders. The work included expanding regression and validation test coverage, upgrading testing infrastructure, and refining error handling to reduce defects and improve data integrity. Sandaru’s approach emphasized robust automation and maintainable code, resulting in more reliable analytics, streamlined user experiences, and higher engineering confidence across both backend and UI modules.

January 2026 monthly summary: Significant progress across the cut-dry automation projects, delivering user- and data-critical improvements in catalog usability, order workflows, testing coverage, and offline/draft capabilities. Key features landed include catalog tagging and sorting enhancements with item editing, and Customer Orders UI improvements that display order references, ensure accurate item counts, handle empty states, and apply minimum order settings in customer profiles. The testing base was strengthened via infrastructure upgrades and broader coverage, including new XML config entries and targeted test cleanups. A new Drafts and Offline Ordering capability was added for order processing resilience, accompanied by regression tests. Order management and order guide received enhancements for quantity handling, no-confirm-submission flow, and maximum quantity validation, along with updated tests to ensure reliability. Focused data corrections for buyout products and improved workflows in standing orders finalize data integrity. These contributions collectively reduce user friction, improve data quality, and raise engineering confidence through better test coverage and robust automation. Top 5 achievements: - Catalog tagging and sorting enhancements deployed in cut-dry-automation-framework (tags: cashback, sale, new item; item name editing) — commits 8143774d..., 2bce03e3... - Customer Orders UI enhancements implemented (order reference display, item-count accuracy, empty states, profile min settings; related tests updated) — commits 664a95af..., 567984c2..., 00a79113... - Testing infrastructure upgrades and expanded coverage (XML config updates and test refactors across customer tests) — commits 80a26131..., 36672e53..., 869b07f6... - Drafts and Offline Ordering feature added with regression tests (offline mode and draft workflow) — commits 4a398369..., 3aa2487d8..., c129d5fd..., 28cc25e7... - Enhanced Order Management and Order Guide (quantity handling, no-confirm-submission flow, max quantity validation; test updates) — commits 76049f7e..., e6dcb312..., b4fa160e..., d5c66f22...
January 2026 monthly summary: Significant progress across the cut-dry automation projects, delivering user- and data-critical improvements in catalog usability, order workflows, testing coverage, and offline/draft capabilities. Key features landed include catalog tagging and sorting enhancements with item editing, and Customer Orders UI improvements that display order references, ensure accurate item counts, handle empty states, and apply minimum order settings in customer profiles. The testing base was strengthened via infrastructure upgrades and broader coverage, including new XML config entries and targeted test cleanups. A new Drafts and Offline Ordering capability was added for order processing resilience, accompanied by regression tests. Order management and order guide received enhancements for quantity handling, no-confirm-submission flow, and maximum quantity validation, along with updated tests to ensure reliability. Focused data corrections for buyout products and improved workflows in standing orders finalize data integrity. These contributions collectively reduce user friction, improve data quality, and raise engineering confidence through better test coverage and robust automation. Top 5 achievements: - Catalog tagging and sorting enhancements deployed in cut-dry-automation-framework (tags: cashback, sale, new item; item name editing) — commits 8143774d..., 2bce03e3... - Customer Orders UI enhancements implemented (order reference display, item-count accuracy, empty states, profile min settings; related tests updated) — commits 664a95af..., 567984c2..., 00a79113... - Testing infrastructure upgrades and expanded coverage (XML config updates and test refactors across customer tests) — commits 80a26131..., 36672e53..., 869b07f6... - Drafts and Offline Ordering feature added with regression tests (offline mode and draft workflow) — commits 4a398369..., 3aa2487d8..., c129d5fd..., 28cc25e7... - Enhanced Order Management and Order Guide (quantity handling, no-confirm-submission flow, max quantity validation; test updates) — commits 76049f7e..., e6dcb312..., b4fa160e..., d5c66f22...
December 2025 monthly summary for GetCodifyAI engineering team. Focused on delivering business value through UX improvements in the order flow, expanding automated testing coverage, and tightening validation to reduce defects post-release across two repositories: GetCodifyAI/cut-dry-ui-automation-restaurant and GetCodifyAI/cut-dry-automation-framework.
December 2025 monthly summary for GetCodifyAI engineering team. Focused on delivering business value through UX improvements in the order flow, expanding automated testing coverage, and tightening validation to reduce defects post-release across two repositories: GetCodifyAI/cut-dry-ui-automation-restaurant and GetCodifyAI/cut-dry-automation-framework.
November 2025 monthly summary: Delivered cross-repo enhancements to streamline order management and improve data integrity across GetCodifyAI’s automation framework and UI automation modules. Focused on standardizing quantity validation, enhancing user experience in standing orders and order guides, and strengthening error handling in list views, with tests and regression coverage. The work reduced quantity-related errors, improved UX consistency across Quick Add, modal interfaces, and simple list views, and enabled more reliable downstream analytics and order processing.
November 2025 monthly summary: Delivered cross-repo enhancements to streamline order management and improve data integrity across GetCodifyAI’s automation framework and UI automation modules. Focused on standardizing quantity validation, enhancing user experience in standing orders and order guides, and strengthening error handling in list views, with tests and regression coverage. The work reduced quantity-related errors, improved UX consistency across Quick Add, modal interfaces, and simple list views, and enabled more reliable downstream analytics and order processing.
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