Azeem Irshad

Papers

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About

Azeem Irshad is a researcher whose work sits at the intersection of software engineering and mobile computing, with a particular focus on understanding and improving the quality of mobile applications. His research leverages user-generated data—such as app store reviews—to provide actionable insights for developers. In his highly cited 2021 paper, “Quality Prediction of Wearable Apps in the Google Play Store,” Irshad demonstrates how user reviews contain a wealth of knowledge that can be mined to predict quality issues and guide the development of higher-quality wearable applications. This work highlights his broader contribution: transforming unstructured user feedback into structured, data-driven decision-making tools for software teams. By showing that even brief reviews can reveal critical quality signals, Irshad empowers developers to build more reliable and user-centric apps. His research is particularly valuable in the rapidly growing domain of wearable technology, where user experience is paramount. With over 8 citations for this key paper, Irshad’s work is gaining recognition for its practical relevance, offering a clear path from user voice to software improvement.