Energy Efficiency in Testing and Regression Testing -- A Comparison of DVFS Techniques

Kan, Edward Y. Y.

doi:10.1109/qsic.2013.21

Cited by 7 publications

(10 citation statements)

References 10 publications

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“…In addition to our own prior work, researchers have investigated techniques for detecting energy bugs (e.g., [21,28,29,31]) and for using expensive resources effectively (e.g., [15,27]). The most related of these techniques investigates using the dynamic voltage and frequency scaling (DVFS) capabilities of certain processors to reduce the energy consumption of regression tests [15].…”

Section: Related Workmentioning

confidence: 99%

“…The most related of these techniques investigates using the dynamic voltage and frequency scaling (DVFS) capabilities of certain processors to reduce the energy consumption of regression tests [15]. At a high-level, they are using DVFS to throttle the CPU to an appropriate level, as determined by analyzing previous executions of the regression tests.…”

Section: Related Workmentioning

confidence: 99%

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Integrated energy-directed test suite optimization

Jin

Sahin

et al. 2014

Proceedings of the 2014 International Symposium on Software Testing and Analysis

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In situ testing techniques have become an important means of ensuring the reliability of embedded systems after they are deployed in the field. However, these techniques do not help testers optimize the energy consumption of their in situ test suites, which can needlessly waste the limited battery power of these systems. In this work, we extend prior techniques for test suite minimization in such a way as to allow testers to generate energy-efficient, minimized test suites with only minimal modifications to their existing work flow. We perform an extensive empirical evaluation of our approach using the test suites provided for real world applications. The results of the evaluation show that our technique is effective at generating, in less than one second, test suites that consume up to 95% less energy while maintaining coverage of the testing requirements.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Integrated energy-directed test suite optimization

Jin

Sahin

et al. 2014

Proceedings of the 2014 International Symposium on Software Testing and Analysis

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show abstract

“…When sufficient performance data have been collected for the entire test suite and a more energy-efficient configuration is found, STDS updates the running best configuration (lines [11][12] for other devices executing in native mode.…”

Section: ) Single-step Top-down Search (Stds) Strategymentioning

confidence: 99%

“…Kan et al [11] also address energy efficiency in testing and regression testing. The work investigates general and appspecific processor frequency assignment algorithms and their effectiveness in testing and regression testing.…”

Section: Energy Optimization In Testingmentioning

confidence: 99%

CrowdAdaptor: A Crowd Sourcing Approach toward Adaptive Energy-Efficient Configurations of Virtual Machines Hosting Mobile Applications

Kan

Chan

Tse

2014

2014 IEEE 38th Annual Computer Software and Applications Conference

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Abstract-Applications written by end-user programmers are hardly energy-optimized by these programmers. The end users of such applications thus suffer significant energy issues. In this paper, we propose CrowdAdaptor, a novel approach toward locating energy-efficient configurations to execute the applications hosted in virtual machines on handheld devices. CrowdAdaptor innovatively makes use of the development artifacts (test cases) and the very large installation base of the same application to distribute the test executions and performance data collection of the whole test suites against many different virtual machine configurations among these installation bases. It synthesizes these data, continuously discovers better energy-efficient configurations, and makes them available to all the installations of the same applications. We report a multi-subject case study on the ability of the framework to discover energy-efficient configurations in three power models. The results show that CrowdAdaptor can achieve up to 50% of energy savings based on a conservative linear power model.

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“…The majority of existing work on energy testing has focused on minimizing test suites with respect to their energy consumption, investigating the adequacy of test suite for energy testing, finding energy bugs, and reducing the energy consumption of test suites. () To the best of our knowledge, none of the existing work focuses on identifying the amount of energy testing required for proposed changes.…”

Section: Introductionmentioning

confidence: 99%

Supporting software evolution through feedback on executing/skipping energy tests for proposed source code changes

Sahin

Pollock

Clause

2019

J Software Evolu Process

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With the increasing use of battery‐powered devices comes the need to test mobile applications for energy consumption and energy issues. Unfortunately, energy testing is expensive because it is a manual, labor‐intensive process that often requires multiple, separate, energy‐measuring devices to collect energy usage data. The high costs of energy testing can negatively affect the planning process of application evolution. For example, developers might be limited in the number of changes they can include in a release because they must conservatively plan to conduct energy testing after each change. In this paper, we present a new approach to provide developers with feedback on executing/skipping energy tests for proposed code changes. Our technique leverages change impact analysis and precomputed API energy usage information. More specifically, for a proposed change, the technique predicts whether energy testing will be required, and if so, which energy tests will need to be run. Such information may allow developers to avoid spending unnecessary time for energy testing and develop an effective application evolution timeline. To investigate the feasibility of our technique, we implemented a prototype for Android applications and conducted three case studies at different granularity levels on 10 Android applications.

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Energy Efficiency in Testing and Regression Testing -- A Comparison of DVFS Techniques

Cited by 7 publications

References 10 publications

Integrated energy-directed test suite optimization

Integrated energy-directed test suite optimization

CrowdAdaptor: A Crowd Sourcing Approach toward Adaptive Energy-Efficient Configurations of Virtual Machines Hosting Mobile Applications

Supporting software evolution through feedback on executing/skipping energy tests for proposed source code changes

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