LeakPred: An Approach for Identifying Components with Resource Leaks in Android Mobile Applications

Abstract

Context: Mobile devices contain some resources, for example, the camera, battery, and memory, that are allocated, used, and then deallocated by mobile applications. Whenever a resource is allocated and not correctly released, a defect called a resource leak occurs, which can cause crashes and slowdowns. Objective: In this study, we intended to demonstrate the usefulness of the LeakPred approach in terms of the number of components with resource leak problems identified in applications. Method: We compared the approach’s effectiveness with three state-of-the-art methods in identifying leaks in 15 Android applications. Result: LeakPred obtained the best median (85.37%) of components with identified leaks, the best coverage (96.15%) of the classes of leaks that could be identified in the applications, and an accuracy of 81.25%. The Android Lint method achieved the second best median (76.92%) and the highest accuracy (100%), but only covered 1.92% of the leak classes. Conclusions: LeakPred is effective in identifying leaky components in applications.

Keywords

• mobile apps
• resource leak
• tool evaluation
• database
• Android
• static analysis