Details
| Originalsprache | Englisch |
|---|---|
| Titel des Sammelwerks | 2012 3rd International Workshop on Recommendation Systems for Software Engineering, RSSE 2012 - Proceedings |
| Seiten | 31-32 |
| Seitenumfang | 2 |
| Publikationsstatus | Veröffentlicht - 2012 |
| Veranstaltung | 2012 3rd International Workshop on Recommendation Systems for Software Engineering, RSSE 2012 - Zurich, Schweiz Dauer: 4 Juni 2012 → 4 Juni 2012 |
Abstract
Successful software development requires software engineering skills as well as domain and user knowledge. This knowledge is difficult to master. Increasing complexity and fast evolving technologies cause deficits in development and system behavior. They cause discrepancies between expectations and observations. We propose using discrepancies as a trigger for recommendations to developers. Discrepancies in using a software application are combined with discrepancies between development artifacts. To efficiently support software engineers, recommendations must consider knowledge bases of discrepancies and resolution options. They evolve over time along with evolving experience. Hence, recommendations and organizational learning are intertwined.
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- Software
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2012 3rd International Workshop on Recommendation Systems for Software Engineering, RSSE 2012 - Proceedings. 2012. S. 31-32 6233405.
Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review
}
TY - GEN
T1 - Recommendations as learning
T2 - 2012 3rd International Workshop on Recommendation Systems for Software Engineering, RSSE 2012
AU - Schneider, Kurt
AU - Gärtner, Stefan
AU - Wehrmaker, Tristan
AU - Brügge, Bernd
PY - 2012
Y1 - 2012
N2 - Successful software development requires software engineering skills as well as domain and user knowledge. This knowledge is difficult to master. Increasing complexity and fast evolving technologies cause deficits in development and system behavior. They cause discrepancies between expectations and observations. We propose using discrepancies as a trigger for recommendations to developers. Discrepancies in using a software application are combined with discrepancies between development artifacts. To efficiently support software engineers, recommendations must consider knowledge bases of discrepancies and resolution options. They evolve over time along with evolving experience. Hence, recommendations and organizational learning are intertwined.
AB - Successful software development requires software engineering skills as well as domain and user knowledge. This knowledge is difficult to master. Increasing complexity and fast evolving technologies cause deficits in development and system behavior. They cause discrepancies between expectations and observations. We propose using discrepancies as a trigger for recommendations to developers. Discrepancies in using a software application are combined with discrepancies between development artifacts. To efficiently support software engineers, recommendations must consider knowledge bases of discrepancies and resolution options. They evolve over time along with evolving experience. Hence, recommendations and organizational learning are intertwined.
KW - end-user feedback
KW - heuristics
KW - recommendation
UR - http://www.scopus.com/inward/record.url?scp=84864650189&partnerID=8YFLogxK
U2 - 10.1109/RSSE.2012.6233405
DO - 10.1109/RSSE.2012.6233405
M3 - Conference contribution
AN - SCOPUS:84864650189
SN - 9781467317597
SP - 31
EP - 32
BT - 2012 3rd International Workshop on Recommendation Systems for Software Engineering, RSSE 2012 - Proceedings
Y2 - 4 June 2012 through 4 June 2012
ER -