Background: In Agile Software Development (ASD) planning is valued more than the resulting plans. Planning and estimation are carried out at multiple levels in ASD. Agile plans and estimates are frequently updated to reflect the current situation. It supports shorter release cycles and flexibility to incorporate changing market and customer needs. Many empirical studies have been conducted to investigate effort estimation in ASD. However, the evidence on effort estimation in ASD has not been aggregated and organized.

Objective: This thesis has two main objectives: First, to identify and aggregate evidence, from both literature and industry, on effort estimation in ASD. Second, to support research and practice on effort estimation in ASD by organizing the identified knowledge.

Method: In this thesis we conducted a Systematic Literature Review (SLR), a systematic mapping study, a questionnaire based industrial survey and an interview based survey.

Results: The SLR and survey results showed that agile teams estimate effort, mostly during release and iteration planning, using techniques that are based on experts' subjective assessments. During effort estimation team related cost drivers, such as team members’ expertise, are considered important. The results also highlighted that implementation and testing are the only activities that are accounted for in effort estimates by most agile teams. Our mapping study identified that taxonomies in SE are mostly designed and presented in an ad-hoc manner. To fill this gap we updated an existing method to design taxonomies in a systematic way. The method is then used to design taxonomy on effort estimation in ASD using the evidence identified in our SLR and survey as input.

Conclusions: The proposed taxonomy is evaluated by characterizing effort estimation cases of selected agile projects reported in literature. The evaluation found that the reporting of the selected studies lacks information related to the context and predictors used during effort estimation in ASD. The taxonomy can be used in consistently reporting effort estimation studies in ASD to facilitate identification, aggregation and analysis of the evidence. The proposed taxonomy was also used to characterize the effort estimation activity of agile teams in three different software companies. The proposed taxonomy was found to be useful by interviewed agile practitioners in documenting important effort estimation related knowledge, which otherwise remain tacit in most cases.