Scenario Mining

Scenario Mining is a systematic method for extracting, identifying, and synthesizing plausible usage scenarios from diverse data sources to inform and refine software requirements, distinguished by its focus on uncovering real-world user behaviors and contextual constraints inherent in empirical or operational environments.

40

Publications

1.7K

Citations

142

Authors

62

Institutions

Publications per year

2017–2026

16

Authors

142

  1. SM
    Shahar Maoz

    Tel Aviv University, Israel

    7 publications · 301 citations

    7

    h-index

  2. DL
    David Lo

    Singapore Management University, Singapore

    6 publications · 286 citations

    6

    h-index

  3. SK
    Shriram Krishnamurthi

    Brown University, United States

    2 publications · 81 citations

    2

    h-index

  4. DJ
    Daniel J. Dougherty

    Worcester Polytechnic Institute, United States

    2 publications · 81 citations

    2

    h-index

  5. NM
    Neil Maiden

    City, University of London, United Kingdom

    2 publications · 71 citations

    2

    h-index

1–5 of 142

Venues

  1. Technological Forecasting and Social Change

    2 publications · 90 citations

    2

    h-index

  2. Sensors

    1 publications · 24 citations

    1

    h-index

  3. IEEE Transactions on Intelligent Vehicles

    ITIVBL · 1 publications · 44 citations

    1

    h-index

  4. 2013 35th International Conference on Software Engineering (ICSE)

    Conference · 1 publications · 48 citations

    1

    h-index

  5. IEEE Robotics and Automation Letters

    1 publications · 25 citations

    1

    h-index

1–5