Mining Modern App Stores to Improve the Perceived Quality of Software Products

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Mobile applications (apps) are becoming an integral part of our daily activities. With the mobile market's highly competitive nature, app developers need to avoid deploying buggy releases and continuously deploy high-quality releases that satisfy user needs. Over the years, the growing mobile app market with millions of apps and billions of yearly downloads generates comprehensive data. Mining mobile app market data (e.g., analyzing user reviews) can help app developers improve their apps' perceived quality. Over the years, research has gained lots of focus to provide guidelines that help app developers build high-quality apps. However, the existing guidelines do not provide clear, automatic actionable advice for app developers to enhance their apps (e.g., an automatic approach for fixing the reported issues or implementing the requested features). Moreover, the existing guidelines do not consider the nature of the developed app. For example, the guidelines for designing a telecommunication app may not be suitable for designing games or financial apps. Therefore, my research program aims to close the existing research gap by applying data mining techniques to the emerging software repositories (i.e., app market data) to provide automatic and customizable guidance and approaches that help app developers improve the perceived quality of mobile apps. My program has two main research directions (RD). RD 1: Supporting rapid releases of high-quality mobile apps. My research aims to help app developers perform rapid releases (without impacting their apps' perceived quality) as follows. First, we will help app developers extract the most important features that need to be implemented by analyzing their competitor apps' reviews. After collecting the requirements, developers need to design their apps to facilitate the app's fairness access to all users. Recent studies show that mobile apps suffer from accessibilities issues in their design. Hence, my research program aims to help app developers design their apps for accessibility, allowing fair access to all users. Next, my research program aims to provide automatic recommendations to help app developers implement the requested features in the development phase. RD 2: Towards maintaining the quality of the deployed apps. To maintain the quality of the delivered mobile apps, after deploying the mobile app, my research aims to build approaches that predict any run-time issues (e.g., performance anomaly) and automatically recommend fixes to the reported bugs. Four MSc and five UG students will be trained on analyzing large-scale software engineering data and building tools that facilitate the rapid development of high-quality mobile apps. We will release all our approaches as open-source projects to help the research and the developer community leverage our work. My work will help app developers produce rapidly high-perceived quality, enabling the software market to grow in Canada.