Miscommunication in Software Projects: Early Recognition Through Tendency Forecasts

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10027)

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.

Keywords

Machine learning Team communication Experience-base 

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Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  1. 1.Software Engineering GroupLeibniz Universität HannoverHannoverGermany

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