A Framework for the Automatic Execution of Measurement-based Experiments on Android Devices

Ivano Malavolta; Eoin Martino Grua; Cheng Yu Lam; Randy De Vries; Franky Tan; Eric Zielinski; Michael Peters; Luuk Kaandorp

doi:10.1145/3417113.3422184

A Framework for the Automatic Execution of Measurement-based Experiments on Android Devices

Ivano Malavolta
, Eoin Martino Grua
, Cheng Yu Lam
, Randy De Vries
, Franky Tan
, Eric Zielinski
, Michael Peters
, Luuk Kaandorp

Research output: Chapter in Book / Report / Conference proceeding › Conference contribution › Academic › peer-review

Abstract

Conducting measurement-based experiments is fundamental for assessing the quality of Android apps in terms of, e.g., energy consumption, CPU, and memory usage. However, orchestrating such experiments is not trivial as it requires large boilerplate code, careful setup of measurement tools, and the adoption of various empirical best practices scattered across the literature. All together, those factors are slowing down the scientific advancement and harming experiments' replicability in the mobile software engineering area. In this paper we present Android Runner (AR), a framework for automatically executing measurement-based experiments on native and web apps running on Android devices. In AR, an experiment is defined once in a descriptive fashion, and then its execution is fully automatic, customizable, and replicable. AR is implemented in Python and it can be extended with third-party profilers. AR has been used in more than 25 scientific studies primarily targeting performance and energy efficiency.

Original language	English
Title of host publication	ASE 2020
Subtitle of host publication	Proceedings of the 35th IEEE/ACM International Conference on Automated Software Engineering Workshops
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	61-66
Number of pages	6
ISBN (Electronic)	9781450381284
DOIs	https://doi.org/10.1145/3417113.3422184
Publication status	Published - Sept 2020
Event	35th IEEE/ACM International Conference on Automated Software Engineering Workshops, ASEW 2020 - Melbourne, Australia Duration: 22 Sept 2020 → 25 Sept 2020

Publication series

Name	Proceedings - IEEE/ACM International Conference on Automated Software Engineering Workshops (ASEW)

Conference

Conference	35th IEEE/ACM International Conference on Automated Software Engineering Workshops, ASEW 2020
Country/Territory	Australia
City	Melbourne
Period	22/09/20 → 25/09/20

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

n/a

Access to Document

10.1145/3417113.3422184

Persistent URL (handle)

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Cite this

Malavolta, I., Grua, E. M., Lam, C. Y., De Vries, R., Tan, F., Zielinski, E., Peters, M., & Kaandorp, L. (2020). A Framework for the Automatic Execution of Measurement-based Experiments on Android Devices. In ASE 2020: Proceedings of the 35th IEEE/ACM International Conference on Automated Software Engineering Workshops (pp. 61-66). Article 9319292 (Proceedings - IEEE/ACM International Conference on Automated Software Engineering Workshops (ASEW)). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1145/3417113.3422184

Malavolta, Ivano ; Grua, Eoin Martino ; Lam, Cheng Yu et al. / A Framework for the Automatic Execution of Measurement-based Experiments on Android Devices. ASE 2020: Proceedings of the 35th IEEE/ACM International Conference on Automated Software Engineering Workshops. Institute of Electrical and Electronics Engineers Inc., 2020. pp. 61-66 (Proceedings - IEEE/ACM International Conference on Automated Software Engineering Workshops (ASEW)).

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title = "A Framework for the Automatic Execution of Measurement-based Experiments on Android Devices",

abstract = "Conducting measurement-based experiments is fundamental for assessing the quality of Android apps in terms of, e.g., energy consumption, CPU, and memory usage. However, orchestrating such experiments is not trivial as it requires large boilerplate code, careful setup of measurement tools, and the adoption of various empirical best practices scattered across the literature. All together, those factors are slowing down the scientific advancement and harming experiments' replicability in the mobile software engineering area. In this paper we present Android Runner (AR), a framework for automatically executing measurement-based experiments on native and web apps running on Android devices. In AR, an experiment is defined once in a descriptive fashion, and then its execution is fully automatic, customizable, and replicable. AR is implemented in Python and it can be extended with third-party profilers. AR has been used in more than 25 scientific studies primarily targeting performance and energy efficiency. ",

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month = sep,

doi = "10.1145/3417113.3422184",

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publisher = "Institute of Electrical and Electronics Engineers Inc.",

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Malavolta, I, Grua, EM, Lam, CY, De Vries, R, Tan, F, Zielinski, E, Peters, M & Kaandorp, L 2020, A Framework for the Automatic Execution of Measurement-based Experiments on Android Devices. in ASE 2020: Proceedings of the 35th IEEE/ACM International Conference on Automated Software Engineering Workshops., 9319292, Proceedings - IEEE/ACM International Conference on Automated Software Engineering Workshops (ASEW), Institute of Electrical and Electronics Engineers Inc., pp. 61-66, 35th IEEE/ACM International Conference on Automated Software Engineering Workshops, ASEW 2020, Melbourne, Australia, 22/09/20. https://doi.org/10.1145/3417113.3422184

A Framework for the Automatic Execution of Measurement-based Experiments on Android Devices. / Malavolta, Ivano; Grua, Eoin Martino; Lam, Cheng Yu et al.
ASE 2020: Proceedings of the 35th IEEE/ACM International Conference on Automated Software Engineering Workshops. Institute of Electrical and Electronics Engineers Inc., 2020. p. 61-66 9319292 (Proceedings - IEEE/ACM International Conference on Automated Software Engineering Workshops (ASEW)).

Research output: Chapter in Book / Report / Conference proceeding › Conference contribution › Academic › peer-review

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AU - Zielinski, Eric

AU - Peters, Michael

AU - Kaandorp, Luuk

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AB - Conducting measurement-based experiments is fundamental for assessing the quality of Android apps in terms of, e.g., energy consumption, CPU, and memory usage. However, orchestrating such experiments is not trivial as it requires large boilerplate code, careful setup of measurement tools, and the adoption of various empirical best practices scattered across the literature. All together, those factors are slowing down the scientific advancement and harming experiments' replicability in the mobile software engineering area. In this paper we present Android Runner (AR), a framework for automatically executing measurement-based experiments on native and web apps running on Android devices. In AR, an experiment is defined once in a descriptive fashion, and then its execution is fully automatic, customizable, and replicable. AR is implemented in Python and it can be extended with third-party profilers. AR has been used in more than 25 scientific studies primarily targeting performance and energy efficiency.

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ER -

Malavolta I, Grua EM, Lam CY, De Vries R, Tan F, Zielinski E et al. A Framework for the Automatic Execution of Measurement-based Experiments on Android Devices. In ASE 2020: Proceedings of the 35th IEEE/ACM International Conference on Automated Software Engineering Workshops. Institute of Electrical and Electronics Engineers Inc. 2020. p. 61-66. 9319292. (Proceedings - IEEE/ACM International Conference on Automated Software Engineering Workshops (ASEW)). doi: 10.1145/3417113.3422184

A Framework for the Automatic Execution of Measurement-based Experiments on Android Devices

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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