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Enabling Real-Time Feedback in Software Engineering. / Larios Vargas, Enrique; Hejderup, Joseph; Kechagia, Maria; Bruntink, Magiel; Gousios, Georgios.

Proceedings of the 40th International Conference on Software Engineering: New Ideas and Emerging Results, ICSE-NIER 2018. Vol. Part F137347 New York, NY : Association for Computing Machinery (ACM), 2018. p. 21-24.

Research output: Scientific - peer-reviewConference contribution

Harvard

Larios Vargas, E, Hejderup, J, Kechagia, M, Bruntink, M & Gousios, G 2018, Enabling Real-Time Feedback in Software Engineering. in Proceedings of the 40th International Conference on Software Engineering: New Ideas and Emerging Results, ICSE-NIER 2018. vol. Part F137347, Association for Computing Machinery (ACM), New York, NY, pp. 21-24, ICSE 2018, Gothenburg, Sweden, 27/05/18. DOI: 10.1145/3183399.3183416

APA

Larios Vargas, E., Hejderup, J., Kechagia, M., Bruntink, M., & Gousios, G. (2018). Enabling Real-Time Feedback in Software Engineering. In Proceedings of the 40th International Conference on Software Engineering: New Ideas and Emerging Results, ICSE-NIER 2018 (Vol. Part F137347, pp. 21-24). New York, NY: Association for Computing Machinery (ACM). DOI: 10.1145/3183399.3183416

Vancouver

Larios Vargas E, Hejderup J, Kechagia M, Bruntink M, Gousios G. Enabling Real-Time Feedback in Software Engineering. In Proceedings of the 40th International Conference on Software Engineering: New Ideas and Emerging Results, ICSE-NIER 2018. Vol. Part F137347. New York, NY: Association for Computing Machinery (ACM). 2018. p. 21-24. Available from, DOI: 10.1145/3183399.3183416

Author

Larios Vargas, Enrique ; Hejderup, Joseph ; Kechagia, Maria ; Bruntink, Magiel ; Gousios, Georgios. / Enabling Real-Time Feedback in Software Engineering. Proceedings of the 40th International Conference on Software Engineering: New Ideas and Emerging Results, ICSE-NIER 2018. Vol. Part F137347 New York, NY : Association for Computing Machinery (ACM), 2018. pp. 21-24

BibTeX

@inbook{fecf62b6ed6d45948455bc7cc8850754,
title = "Enabling Real-Time Feedback in Software Engineering",
abstract = "Modern software projects consist of more than just code: teams follow development processes, the code runs on servers or mobile phones and produces run time logs and users talk about the software in forums like StackOverflow and Twitter and rate it on app stores. Insights stemming from the real-time analysis of combined software engineering data can help software practitioners to conduct faster decision-making. With the development of CodeFeedr, a Real-time Software Analytics Platform, we aim to make software analytics a core feedback loop for software engineering projects.CodeFeedr's vision entails: (1) The ability to unify archival and current software analytics data under a single query language, and (2) The feasibility to apply new techniques and methods for high-level aggregation and summarization of near real-time information on software development. In this paper, we outline three use cases where our platform is expected to have a significant impact on the quality and speed of decision making; dependency management, productivity analytics, and run-time error feedback.",
keywords = "software analytics, streaming data, real-time feedback",
author = "{Larios Vargas}, Enrique and Joseph Hejderup and Maria Kechagia and Magiel Bruntink and Georgios Gousios",
year = "2018",
doi = "10.1145/3183399.3183416",
volume = "Part F137347",
pages = "21--24",
booktitle = "Proceedings of the 40th International Conference on Software Engineering",
publisher = "Association for Computing Machinery (ACM)",
address = "United States",

}

RIS

TY - CHAP

T1 - Enabling Real-Time Feedback in Software Engineering

AU - Larios Vargas,Enrique

AU - Hejderup,Joseph

AU - Kechagia,Maria

AU - Bruntink,Magiel

AU - Gousios,Georgios

PY - 2018

Y1 - 2018

N2 - Modern software projects consist of more than just code: teams follow development processes, the code runs on servers or mobile phones and produces run time logs and users talk about the software in forums like StackOverflow and Twitter and rate it on app stores. Insights stemming from the real-time analysis of combined software engineering data can help software practitioners to conduct faster decision-making. With the development of CodeFeedr, a Real-time Software Analytics Platform, we aim to make software analytics a core feedback loop for software engineering projects.CodeFeedr's vision entails: (1) The ability to unify archival and current software analytics data under a single query language, and (2) The feasibility to apply new techniques and methods for high-level aggregation and summarization of near real-time information on software development. In this paper, we outline three use cases where our platform is expected to have a significant impact on the quality and speed of decision making; dependency management, productivity analytics, and run-time error feedback.

AB - Modern software projects consist of more than just code: teams follow development processes, the code runs on servers or mobile phones and produces run time logs and users talk about the software in forums like StackOverflow and Twitter and rate it on app stores. Insights stemming from the real-time analysis of combined software engineering data can help software practitioners to conduct faster decision-making. With the development of CodeFeedr, a Real-time Software Analytics Platform, we aim to make software analytics a core feedback loop for software engineering projects.CodeFeedr's vision entails: (1) The ability to unify archival and current software analytics data under a single query language, and (2) The feasibility to apply new techniques and methods for high-level aggregation and summarization of near real-time information on software development. In this paper, we outline three use cases where our platform is expected to have a significant impact on the quality and speed of decision making; dependency management, productivity analytics, and run-time error feedback.

KW - software analytics

KW - streaming data

KW - real-time feedback

UR - http://www.scopus.com/inward/record.url?scp=85049786658&partnerID=8YFLogxK

U2 - 10.1145/3183399.3183416

DO - 10.1145/3183399.3183416

M3 - Conference contribution

VL - Part F137347

SP - 21

EP - 24

BT - Proceedings of the 40th International Conference on Software Engineering

PB - Association for Computing Machinery (ACM)

ER -

ID: 38777494