Identification of mobile development issues using semantic topic modeling of Stack Overflow posts - Gurcan, Fatih (PeerJ. Computer science, 2023)
Increasing demands for mobile apps and services have recently led to an intensification of mobile development activities. With the proliferation of mobile development, there has been a major transformation in the architectures, paradigms, knowledge domains and skills of traditional software systems towards mobile development. Therefore, mobile developers experience a wide spectrum of issues specific to development processes of mobile apps and services. In this article, we conducted a semantic content analysis based on topic modeling using mobile-related questions on Stack Overflow, a popular Q&A site for developers. With the aim of providing an understanding of the issues and challenges faced by mobile developers, we used a semi-automated methodology based on latent Dirichlet allocation (LDA), a probabilistic and generative approach for topic modeling. Our findings revealed that mobile developers' questions focused on 36 topics in six main categories, including "Development", "UI settings", "Tools", "Data Management", "Multimedia", and "Mobile APIs". Besides, we investigated the temporal trends of the discovered issues and their relationships with mobile technologies. Our findings also revealed which issues are the most popular and which issues are the most difficult for mobile development. The methodology and findings of this study have valuable implications for mobile development stakeholders including tool builders, developers, researchers, and educators.