Self-Reported Activities of Android Developers

Luca Pascarella; Franz-Xaver Geiger; Fabio Palomba; Dario Di Nucci; Ivano Malavolta; Alberto Bacchelli

doi:10.1145/3197231.3197251

Self-Reported Activities of Android Developers

Luca Pascarella, Franz-Xaver Geiger, Fabio Palomba, Dario Di Nucci, Ivano Malavolta, Alberto Bacchelli

Software Engineering

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

17 Citations (Scopus)

367 Downloads (Pure)

Abstract

To gain a deeper empirical understanding of how developers work on Android apps, we investigate self-reported activities of Android developers and to what extent these activities can be classified with machine learning techniques. To this aim, we firstly create a taxonomy of self-reported activities coming from the manual analysis of 5,000 commit messages from 8,280 Android apps. Then, we study the frequency of each category of self-reported activities identified in the taxonomy, and investigate the feasibility of an automated classification approach. Our findings can inform be used by both practitioners and researchers to take informed decisions or support other software engineering activities.

Original language	English
Title of host publication	5th IEEE/ACM International Conference on Mobile Software Engineering and Systems. ACM, New York, NY, to appear
Publisher	IEEE / ACM
Pages	144-155
ISBN (Electronic)	978-1-4503-5712-8
DOIs	https://doi.org/10.1145/3197231.3197251
Publication status	Published - 2018
Event	5th IEEE/ACM International Conference on Mobile Software Engineering and Systems - Gothenburg, Sweden Duration: 27 May 2018 → 28 May 2018 Conference number: 5

Conference

Conference	5th IEEE/ACM International Conference on Mobile Software Engineering and Systems
Abbreviated title	MOBILESoft 2018
Country/Territory	Sweden
City	Gothenburg
Period	27/05/18 → 28/05/18

Bibliographical note

Acknowledgments: European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 642954

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mobileSoft_2018Accepted author manuscript, 597 KB
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Cite this

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title = "Self-Reported Activities of Android Developers",

abstract = "To gain a deeper empirical understanding of how developers work on Android apps, we investigate self-reported activities of Android developers and to what extent these activities can be classified with machine learning techniques. To this aim, we firstly create a taxonomy of self-reported activities coming from the manual analysis of 5,000 commit messages from 8,280 Android apps. Then, we study the frequency of each category of self-reported activities identified in the taxonomy, and investigate the feasibility of an automated classification approach. Our findings can inform be used by both practitioners and researchers to take informed decisions or support other software engineering activities.",

author = "Luca Pascarella and Franz-Xaver Geiger and Fabio Palomba and {Di Nucci}, Dario and Ivano Malavolta and Alberto Bacchelli",

note = "Acknowledgments: European Union{\textquoteright}s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 642954; 5th IEEE/ACM International Conference on Mobile Software Engineering and Systems, MOBILESoft 2018 ; Conference date: 27-05-2018 Through 28-05-2018",

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doi = "10.1145/3197231.3197251",

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booktitle = "5th IEEE/ACM International Conference on Mobile Software Engineering and Systems. ACM, New York, NY, to appear",

publisher = "IEEE / ACM",

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Pascarella, L, Geiger, F-X, Palomba, F, Di Nucci, D, Malavolta, I & Bacchelli, A 2018, Self-Reported Activities of Android Developers. in 5th IEEE/ACM International Conference on Mobile Software Engineering and Systems. ACM, New York, NY, to appear. IEEE / ACM, pp. 144-155, 5th IEEE/ACM International Conference on Mobile Software Engineering and Systems, Gothenburg, Sweden, 27/05/18. https://doi.org/10.1145/3197231.3197251

Self-Reported Activities of Android Developers. / Pascarella, Luca; Geiger, Franz-Xaver; Palomba, Fabio et al.
5th IEEE/ACM International Conference on Mobile Software Engineering and Systems. ACM, New York, NY, to appear. IEEE / ACM, 2018. p. 144-155.

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

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T1 - Self-Reported Activities of Android Developers

AU - Pascarella, Luca

AU - Geiger, Franz-Xaver

AU - Palomba, Fabio

AU - Di Nucci, Dario

AU - Malavolta, Ivano

AU - Bacchelli, Alberto

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N2 - To gain a deeper empirical understanding of how developers work on Android apps, we investigate self-reported activities of Android developers and to what extent these activities can be classified with machine learning techniques. To this aim, we firstly create a taxonomy of self-reported activities coming from the manual analysis of 5,000 commit messages from 8,280 Android apps. Then, we study the frequency of each category of self-reported activities identified in the taxonomy, and investigate the feasibility of an automated classification approach. Our findings can inform be used by both practitioners and researchers to take informed decisions or support other software engineering activities.

AB - To gain a deeper empirical understanding of how developers work on Android apps, we investigate self-reported activities of Android developers and to what extent these activities can be classified with machine learning techniques. To this aim, we firstly create a taxonomy of self-reported activities coming from the manual analysis of 5,000 commit messages from 8,280 Android apps. Then, we study the frequency of each category of self-reported activities identified in the taxonomy, and investigate the feasibility of an automated classification approach. Our findings can inform be used by both practitioners and researchers to take informed decisions or support other software engineering activities.

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T2 - 5th IEEE/ACM International Conference on Mobile Software Engineering and Systems

Y2 - 27 May 2018 through 28 May 2018

ER -

Self-Reported Activities of Android Developers

Abstract

Conference

Bibliographical note

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