Recommending Effort Estimation Methods for Software Project Management

Estimating a project's effort or schedule is a crucial task for software project management. However, project leaders are often overwhelmed when selecting an appropriate estimation method to best match the project characteristics and context. Recommender systems (RS) are applications that typically support online users when confronted with large sets of choices. Knowledge-based recommenders are a specific variant of these systems that exploit explicit knowledge models in order to infer matching items based on a set of specific requirements. This paper's contribution lies in its application of knowledge-based recommendation mechanisms to the domain of software project management and presents a recommender for effort estimation methods. An initial evaluation among software professionals showed promising results and disclosed helpful hints for further development.