Toward Data-Driven Requirements Engineering
Nowadays, users can easily submit feedback about software products in app stores, social media, or user groups. Moreover, software vendors are collecting massive amounts of implicit feedback in the form of usage data, error logs, and sensor data. These trends suggest a shift toward data-driven user-...
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| Veröffentlicht in: | IEEE software 2016-01, Vol.33 (1), p.48-54 |
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| container_title | IEEE software |
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| creator | Maalej, Walid Nayebi, Maleknaz Johann, Timo Ruhe, Guenther |
| description | Nowadays, users can easily submit feedback about software products in app stores, social media, or user groups. Moreover, software vendors are collecting massive amounts of implicit feedback in the form of usage data, error logs, and sensor data. These trends suggest a shift toward data-driven user-centered identification, prioritization, and management of software requirements. Developers should be able to adopt the requirements of masses of users when deciding what to develop and when to release. They could systematically use explicit and implicit user data in an aggregated form to support requirements decisions. The goal is data-driven requirements engineering by the masses and for the masses. |
| doi_str_mv | 10.1109/MS.2015.153 |
| format | Article |
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| ispartof | IEEE software, 2016-01, Vol.33 (1), p.48-54 |
| issn | 0740-7459 1937-4194 |
| language | eng |
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| source | IEEE Electronic Library (IEL) |
| subjects | app reviews Computer programs decision support Digital media Error detection Feature extraction Feedback Logs Media Requirements analysis Requirements engineering Social networks Software software analytics software development Software engineering Stakeholders Stores Studies Systems development usage data |
| title | Toward Data-Driven Requirements Engineering |
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