An Analysis of the Effects of Bad Smell-Driven Refactorings in Mobile Applications on Battery Usage

Rodríguez, Alejandro Damián; Mateos, Cristian; Zunino, Alejandro; Longo, Mathias

doi:10.4018/978-1-4666-9916-8.ch009

Cited by 7 publications

(7 citation statements)

References 20 publications

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“…We are also exploiting these ideas for mobile device programming. Preliminary works studied the rate at which micro-benchmarks versions deplete batteries [36] and the trade-off between code smell-free OO designs versus the inherent energy costs [37] in Java-based Android applications. The motivation of these works is that mobile devices can act as resource providers in edge environments to run scientific applications [20], so coding energy-aware tasks becomes crucial.…”

Section: Discussionmentioning

confidence: 99%

Reducing energy usage in resource-intensive Java-based scientific applications via micro-benchmark based code refactorings

et al. 2019

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In-silico research has grown considerably. Today's scientific code involves long-running computer simulations and hence powerful computing infrastructures are needed. Traditionally, research in high-performance computing has focused on executing code as fast as possible, while energy has been recently recognized as another goal to consider. Yet, energy-driven research has mostly focused on the hardware and middleware layers, but few efforts target the application level, where many energy-aware optimizations are possible. We revisit a catalog of Java primitives commonly used in OO scientific programming, or micro-benchmarks, to identify energy-friendly versions of the same primitive. We then apply the micro-benchmarks to classical scientific application kernels and machine learning algorithms for both single-thread and multi-thread implementations on a server. Energy usage reductions at the micro-benchmark level are substantial, while for applications obtained reductions range from 3.90% to 99.18%.

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Section: Discussionmentioning

confidence: 99%

Reducing energy usage in resource-intensive Java-based scientific applications via micro-benchmark based code refactorings

et al. 2019

Self Cite

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“…While code smells may be an indicator of poor programming practice in object-oriented programming, there is no evidence to suggest that the removal of all traditional code smells should result in a reduction in energy consumption. The opposite is sometimes true [16,18]. We hypothesise that the practices followed in typical object-oriented design, where clear structure, reusability of code, and long-term maintenance are key, results in greater redundancy and unnecessary energy consumption.…”

Section: Challengesmentioning

confidence: 97%

“…Rodriguez et al [18] also measured the impact of code smells on energy consumption, employing several mobile applications in their experiments. For each mobile application, they created one version where all code smells were removed and another version where smells were left and accessor methods were removed (to reduce energy consumption).…”

Section: Related Workmentioning

confidence: 99%

“…CPU Cycle Measurements [10], XEEMU [15]) sometimes used for embedded and mobile systems respectively. Physical tools are frequently deployed, with various types of low level measurement tools such as the TipPie Handyscope HS5 [12], MSoon power monitor [18], and National Instruments USB-6215 DAQ card [20] being used, while higher level tools such as the Voltcraft Energy Logger 4000 [16] and Watts Up Pro power meter [21] are also employed.…”

Section: Power Measurement Accuracymentioning

confidence: 99%

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Inheritance versus Delegation

Bree

Cinnéide

2020

Proceedings of the IEEE/ACM 42nd International Conference on Software Engineering Workshops

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Energy consumption of software is receiving more attention as concerns regarding climate change increase. One factor that significantly impacts how much energy is expended by a software application is the design of the software itself. Existing studies find few consistent results regarding the impact of common refactorings on energy consumption, nor do they define a concrete set of metrics that measure the energy efficiency of software. In this paper, we present the results of preliminary experiments that explore the Replace Inheritance with Delegation refactoring, and its inverse, to assess the impact these design-level refactorings have on energy consumption in the Java programming language. In the tested programs, inheritance proved to be more energy efficient than delegation, with a reduction in run time of 77% and a reduction in average power consumption of 4%. We subsequently propose a research plan to further explore this problem and observe a number of specific challenges in this area. The primary goals of this research are threefold: (i) to investigate how redundancy in an object-oriented design can contribute to unnecessary energy consumption, (ii) to determine how refactoring of the software can remove this redundancy, and (iii) to develop a general-purpose automated tool to perform this refactoring.

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“…However, in such application areas, runtime qualities, such as energy consumption, matter most. The trade-off between object-oriented design quality, as reflected in the number of smells and energy consumption has been the focus of the study by Rodriguez et al [51]. In particular, the authors studied on four mobile applications the energy impact of refactorings on Java source code and JDeodorant has been used to identify refactoring opportunities.…”

Section: Width Represents the Number Of Studies Height Represents Nummentioning

confidence: 99%

Ten years of JDeodorant: Lessons learned from the hunt for smells

Tsantalis

Chaikalis

Chatzigeorgiou

2018

2018 IEEE 25th International Conference on Software Analysis, Evolution and Reengineering (SANER)

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Deodorants are different from perfumes, because they are applied directly on body and by killing bacteria they reduce odours and offer a refreshing fragrance. That was our goal when we first thought about "bad smells" in code: to develop techniques for effectively identifying and removing (i.e., deodorizing) code smells from object-oriented software. JDeodorant encompasses a number of techniques for suggesting and automatically applying refactoring opportunities on Java source code, in a way that requires limited effort on behalf of the developer. In contrast to other approaches that rely on generic strategies that can be adapted to various smells, JDeodorant adopts ad-hoc strategies for each smell considering the particular characteristics of the underlying design or code problem. In this retrospective paper, we discuss the impact of JDeodorant over the last ten years and a number of tools and techniques that have been developed for a similar purpose which either compare their results with JDeodorant or have built on top of JDeodorant. Finally, we discuss the empirical findings from a number of studies that employed JDeodorant to extract their datasets.

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An Analysis of the Effects of Bad Smell-Driven Refactorings in Mobile Applications on Battery Usage

Cited by 7 publications

References 20 publications

Reducing energy usage in resource-intensive Java-based scientific applications via micro-benchmark based code refactorings

Reducing energy usage in resource-intensive Java-based scientific applications via micro-benchmark based code refactorings

Inheritance versus Delegation

Ten years of JDeodorant: Lessons learned from the hunt for smells

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