Conference Information
MSR 2021: Working Conference on Mining Software Repositories
https://conf.researchr.org/home/msr-2021
Submission Date:
2021-01-05
Notification Date:
2021-02-22
Conference Date:
2021-05-23
Location:
Madrid, Spain
Years:
18
CCF: c   CORE: a   QUALIS: b1   Viewed: 13419   Tracked: 33   Attend: 3

Conference Location
Call For Papers
The technical track of MSR 2021 solicits high-quality submissions on a wide range of topics related to artificial intelligence (AI), machine learning (ML), and data science (DS) in one or more of the following three main themes.

1. AI/ML/DS and SE

The analysis should aim to improve understanding of development processes and practices or aid in the development of new techniques or models to support software developers. This includes (but is not limited to) analysis or models for:

    commits,
    execution traces and logs,
    interaction data,
    code review data,
    natural language artifacts,
    software licenses and copyrights,
    app store data,
    programming language features,
    release information,
    CI logs,
    deployment and delivery,
    test data,
    runtime information,
    software ecosystems,
    defect and software quality data,
    human and social aspects of development,
    development process,
    energy profile data.

2. New techniques, tools, and models.

The techniques, tools, and models should facilitate new ways to mine, analyze, or model software data. A submission could include (but is not limited to) techniques, tools, or models to:

    capture new forms of data,
    integrate data from multiple sources,
    visualize software data,
    model software data,
    solve SE problems,
    improve AI/ML/DS.

3. Considerations related to AI/ML/DS and SE.

These submissions should reflect on the current state-of-the-art research methods or current practices in mining, analyzing, or modeling software data. These submissions can also propose new research methods or guidelines. This theme includes topics such as (but not limited to)

    privacy of collected data,
    ethics of mining, analyzing, or modelling software data,
    biases in software data, analyses, and tools,
    fairness in software data, analyses, and tools,
    Replication studies.
Last updated by Dou Sun in 2020-10-18
Acceptance Ratio
YearSubmittedAcceptedAccepted(%)
2012862933.7%
2011782633.3%
2010672131.3%
2009652640%
2008422252.4%
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International Journal of Agent-Oriented Software Engineering Inder Science Publishers1746-1375
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Mathematical Methods of Operations Research1.023Springer1432-2994
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