Details
| Originalsprache | Englisch |
|---|---|
| Titel des Sammelwerks | Product-Focused Software Process Improvement - 17th International Conference, PROFES 2016, Proceedings |
| Herausgeber/-innen | Sousuke Amasaki, Tommi Mikkonen, Michael Felderer, Pekka Abrahamsson, Anh Nguyen Duc, Andreas Jedlitschka |
| Erscheinungsort | Cham |
| Herausgeber (Verlag) | Springer International Publishing AG |
| Seiten | 731-738 |
| Seitenumfang | 8 |
| ISBN (Print) | 9783319490939 |
| Publikationsstatus | Veröffentlicht - 2016 |
Publikationsreihe
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Band | 10027 LNCS |
| ISSN (Print) | 0302-9743 |
| ISSN (elektronisch) | 1611-3349 |
Abstract
Efficient team communication is essential for software project success. Misunderstood or underestimated demands on customer requirements and insufficient information sharing within a team can rapidly cause the delay of software releases, hamper customer satisfaction or even endanger the project succeed. The challenges remain to quantify the right amount of communication according to durations, necessary effort, and the ambitions to avoid firefighting situations. Especially newly build or less experienced teams often struggle with their information flow. To improve team communication performances for these teams, we build an experience based classifier model that interpolates tendency forecasts with five approved team communication metrics from related work. The model matches archival project communications with present team conditions and computes tendency forecasts for the ongoing project. These future trends can indicate critical communication conditions right from early phases. Hence, they can reduce risks of miscommunication during a project.
ASJC Scopus Sachgebiete
- Mathematik (insg.)
- Theoretische Informatik
- Informatik (insg.)
- Allgemeine Computerwissenschaft
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Product-Focused Software Process Improvement - 17th International Conference, PROFES 2016, Proceedings. Hrsg. / Sousuke Amasaki; Tommi Mikkonen; Michael Felderer; Pekka Abrahamsson; Anh Nguyen Duc; Andreas Jedlitschka. Cham: Springer International Publishing AG, 2016. S. 731-738 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 10027 LNCS).
Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review
}
TY - GEN
T1 - Miscommunication in Software Projects: Early Recognition Through Tendency Forecasts
AU - Kortum, Fabian
AU - Klünder, Jil
AU - Schneider, Kurt
N1 - Funding Information: This work was funded by the German Research Foundation (DFG) under grant number 263807701 (Project TeamFLOW, 2015-2017). Publisher Copyright: © Springer International Publishing AG 2016. Copyright: Copyright 2017 Elsevier B.V., All rights reserved.
PY - 2016
Y1 - 2016
N2 - Efficient team communication is essential for software project success. Misunderstood or underestimated demands on customer requirements and insufficient information sharing within a team can rapidly cause the delay of software releases, hamper customer satisfaction or even endanger the project succeed. The challenges remain to quantify the right amount of communication according to durations, necessary effort, and the ambitions to avoid firefighting situations. Especially newly build or less experienced teams often struggle with their information flow. To improve team communication performances for these teams, we build an experience based classifier model that interpolates tendency forecasts with five approved team communication metrics from related work. The model matches archival project communications with present team conditions and computes tendency forecasts for the ongoing project. These future trends can indicate critical communication conditions right from early phases. Hence, they can reduce risks of miscommunication during a project.
AB - Efficient team communication is essential for software project success. Misunderstood or underestimated demands on customer requirements and insufficient information sharing within a team can rapidly cause the delay of software releases, hamper customer satisfaction or even endanger the project succeed. The challenges remain to quantify the right amount of communication according to durations, necessary effort, and the ambitions to avoid firefighting situations. Especially newly build or less experienced teams often struggle with their information flow. To improve team communication performances for these teams, we build an experience based classifier model that interpolates tendency forecasts with five approved team communication metrics from related work. The model matches archival project communications with present team conditions and computes tendency forecasts for the ongoing project. These future trends can indicate critical communication conditions right from early phases. Hence, they can reduce risks of miscommunication during a project.
KW - Experience-base
KW - Machine learning
KW - Team communication
UR - http://www.scopus.com/inward/record.url?scp=84998694421&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-49094-6_62
DO - 10.1007/978-3-319-49094-6_62
M3 - Conference contribution
SN - 9783319490939
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 731
EP - 738
BT - Product-Focused Software Process Improvement - 17th International Conference, PROFES 2016, Proceedings
A2 - Amasaki, Sousuke
A2 - Mikkonen, Tommi
A2 - Felderer, Michael
A2 - Abrahamsson, Pekka
A2 - Duc, Anh Nguyen
A2 - Jedlitschka, Andreas
PB - Springer International Publishing AG
CY - Cham
ER -