Enabling Real-Time Feedback in Software Engineering

Enrique Larios Vargas, Joseph Hejderup, Maria Kechagia, Magiel Bruntink, Georgios Gousios

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

9 Citations (Scopus)
348 Downloads (Pure)


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.
Original languageEnglish
Title of host publicationProceedings of the 40th International Conference on Software Engineering
Subtitle of host publicationNew Ideas and Emerging Results, ICSE-NIER 2018
Place of PublicationNew York, NY
PublisherAssociation for Computing Machinery (ACM)
Number of pages4
VolumePart F137347
ISBN (Electronic)978-1-4503-5662-6
Publication statusPublished - 2018
EventICSE 2018: 40th International Conference on Software Engineering - Gothenburg, Sweden
Duration: 27 May 20183 Jun 2018
Conference number: 40


ConferenceICSE 2018
Internet address


  • software analytics
  • streaming data
  • real-time feedback


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