A Comparative Study of Android Performance Issues in Real-world Applications and Literature

TL;DR

This study conducts a large-scale, cross-source analysis of real-world Android performance concerns and contrasts them with a systematic literature review to quantify alignment gaps. By integrating Google Play reviews, Stack Overflow discussions, and GitHub issues/commits, the authors derive a unified seven-type performance taxonomy with 82 contributing factors and six common code patterns, then validate this taxonomy with practitioner input. The literature review reveals that only a minority of real-world factors (approximately 42.86%) are captured in academic work, with tools addressing around 36.59% of factors and datasets covering only 29.27%, underscoring significant gaps in detection, remediation, and benchmarking. The work highlights misalignment among researchers, developers, and users, and calls for broader focus on responsive and memory-related issues, more comprehensive tool support, and the urgent development of representative benchmark datasets to accelerate practical Android performance analysis.

Abstract

Performance issues in Android applications significantly undermine users' experience, engagement, and retention, which is a long-lasting research topic in academia. Unlike functionality issues, performance issues are more difficult to diagnose and resolve due to their complex root causes, which often emerge only under specific conditions or payloads. Although many efforts haven attempt to mitigate the impact of performance issues by developing methods to automatically identify and resolve them, it remains unclear if this objective has been fulfilled, and the existing approaches indeed targeted on the most critical performance issues encountered in real-world settings. To this end, we conducted a large-scale comparative study of Android performance issues in real-world applications and literature. Specifically, we started by investigating real-world performance issues, their underlying root causes (i.e., contributing factors), and common code patterns. We then took an additional step to empirically summarize existing approaches and datasets through a literature review, assessing how well academic research reflects the real-world challenges faced by developers and users. Our comparison results show a substantial divergence exists in the primary performance concerns of researchers, developers, and users. Among all the identified factors, 57.14% have not been examined in academic research, while a substantial 76.39% remain unaddressed by existing tools, and 66.67% lack corresponding datasets. This stark contrast underscores a substantial gap in our understanding and management of performance issues. Consequently, it is crucial for our community to intensify efforts to bridge these gaps and achieve comprehensive detection and resolution of performance issues.

Figures (5)

• Figure 1: The process of real-world data collection.
• Figure 2: Distribution of performance issues across various sources.
• Figure 3: Average concern scores for different categories of Android performance issues.
• Figure 4: The working process of our systematic literature review.
• Figure 5: Distribution of selected studies by venue type and performance issue.