EARMO: An Energy-Aware Refactoring Approach for Mobile Apps

Abstract

The energy consumption of mobile apps is a trending topic and researchers are actively investigating the role of coding practices on energy consumption. Recent studies suggest that design choices can conflict with energy consumption. Therefore, it is important to take into account energy consumption when evolving the design of a mobile app. In this paper, we analyze the impact of eight type of anti-patterns on a testbed of 20 android apps extracted from F-Droid. We propose EARMO, a novel anti-pattern correction approach that accounts for energy consumption when refactoring mobile anti-patterns. We evaluate EARMO using three multiobjective search-based algorithms. The obtained results show that EARMO can generate refactoring recommendations in less than a minute, and remove a median of 84% of anti-patterns. Moreover, EARMO extended the battery life of a mobile phone by up to 29 minutes when running in isolation a refactored multimedia app with default settings (no WiFi, no location services, and minimum screen brightness). Finally, we conducted a qualitative study with developers of our studied apps, to assess the refactoring recommendations made by EARMO. Developers found 68% of refactorings suggested by EARMO to be very relevant.

On the impact of code smells on the energy consumption of mobile applications

“…The unique investigation on the impact of three code smells on the performance of Android applications has been carried out by Hetch et al [36], who found some positive correlations between the studied smells and the decreasing performance in term of delayed frames and CPU usage. Finally, Morales et al [60] proposed EARMO, a refactoring tool that, besides code quality, takes into account the energy consumption when refactoring code smells detected in mobile apps. It is important to note that the authors mostly considered the code smells proposed by Fowler [10], while our work aims at understanding the impact of a large variety of Android-specific code smells on energy efficiency as well as the role of refactoring on the performance improvement of mobile apps.…”

“…In this paper, we provide a deeper investigation to determine (i) to what extent code smells affecting source code methods of mobile applications influence energy efficiency, and (ii) whether refactoring operations applied to remove them directly improves the energy efficiency of refactored methods. In particular, our investigation focuses on 9 method-level code smells specifically defined for mobile applications by Reimann et al [9] in the context of 60 Android apps belonging to the dataset provided by Choudhary et al [12]. To the best of our knowledge, this is up to date the largest study aimed at practically investigating the actual impact of these code smells on energy consumption and quantifying the extent to which refactoring code smells is beneficial for improving energy efficiency.…”

On the Survival of Android Code Smells in the Wild

“…In particular, Palomba et al [44] showed that methods that represent a co-occurrence of Internal Setter, Leaking Thread, Member Ignoring Method, and Slow Loop, consume 87 times more energy than other smelly methods. To cope with bad practices in mobile apps, a few works proposed refactoring solutions [33], [40]. Notably, Morales et al [40] proposed EARMO, an energy-aware refactoring approach for mobile apps.…”

“…To cope with bad practices in mobile apps, a few works proposed refactoring solutions [33], [40]. Notably, Morales et al [40] proposed EARMO, an energy-aware refactoring approach for mobile apps. By analysing 20 open-source apps, they showed that refactoring antipatterns can decrease significantly energy consumption.…”

Impact of programming languages on energy consumption for mobile devices

“…Many researchers are worried about where is the energy spent inside different applications and suggest their methods or tools for identifying "energy bugs" [14,15]. The existing papers describing the impact of design choices on the consumption of energy [16][17][18] evidence the need to further investigating this matter. In our research, we focus on studying the influence on it of the choice of programming languages.…”