SEMar 14, 2014

Using Cluster Curves to Control Software Development Projects

arXiv:1403.3498v1
Originality Synthesis-oriented
AI Analysis

This addresses the need for better control and predictability in software development projects, but appears incremental as it builds on existing frameworks like software project control centers.

The paper tackles the problem of making software development projects more predictable and controllable by introducing the Sprint I controlling approach, which uses context-oriented cluster curves for online interpretation and visualization of project data, and provides initial evaluation results.

Online interpretation and visualization of project data are gaining increasing importance on the long road towards predictable and controllable software project execution. This paper sketches the Sprint I controlling approach for software development projects and gives first evaluation results. The approach is grounded on the usage of context-oriented cluster curves and integrated in the framework of software project control centers.

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