Atul Gupta is a software engineer with 9 years of experience building scalable Android and backend systems, currently working as a Platform Engineer at Dream11 after a multi-year tenure as a Computer Scientist at Adobe. He combines strong engineering fundamentals from IIT Kanpur with practical expertise in Kotlin, Java, React, and Express.js, and has led platform integrations and backend rewrites that improved performance and product metrics for millions of users. An active open-source contributor, Atul has materially improved popular Kotlin tools detekt and ktlint by adding new rules, fixing edge cases and reducing false positives—work that reflects a focus on code quality and developer ergonomics. He also brings cross-domain experience from device-level ad replacement at Samsung R&D to migrating large apps to MVVM and clean architecture, showing a knack for both low-level algorithms and scalable application design. Notably, he pairs product-minded engineering with a curiosity for exploring new open-source features and edge-case correctness.
9 years of coding experience
8 years of employment as a software developer
Indian Institute of Technology Kanpur
higher secondary, higher secondary at DAV Koyla Nagar
An anti-bikeshedding Kotlin linter with built-in formatter
Role in this project:
Back-end Developer
Contributions:69 reviews, 8 PRs, 109 comments in 7 months
Contributions summary:Atul primarily focused on enhancing the ktlint rule engine. Their contributions include fixing issues related to rule suppression, such as handling invalid rule IDs and adding a new rule for statement wrapping. They also addressed specific edge cases in the property naming rule and implemented a fix for multi-line if/else statements. These changes indicate a focus on improving the code quality and functionality of the Kotlin linter.
Contributions:261 reviews, 4 commits, 90 PRs in 13 days
Contributions summary:Atul primarily contributed to the `detekt/detekt` repository by implementing and refining static code analysis rules for Kotlin code. Their work involved adding new rules, such as `StringShouldBeRawString` and `CastNullableToNonNullableType`, improving existing rules like `UnnecessaryParentheses`, `ForEachOnRange`, and `UnusedImport` to enhance code quality. They also addressed bugs, fixed false positives, and added configurations to tailor the analysis rules, focusing on improving code style and identifying potential errors in Kotlin codebases.
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