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Impact of individual competence on agile effort estimation in academic setting
  • +1
  • Luka Fürst,
  • Tomaž Hovelja,
  • Marko Poženel,
  • Damjan Vavpotič
Luka Fürst
Univerza v Ljubljani Fakulteta za Racunalnistvo in Informatiko

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Tomaž Hovelja
Univerza v Ljubljani Fakulteta za Racunalnistvo in Informatiko
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Marko Poženel
Univerza v Ljubljani Fakulteta za Racunalnistvo in Informatiko
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Damjan Vavpotič
Univerza v Ljubljani Fakulteta za Racunalnistvo in Informatiko
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Abstract

Effort estimation is an important activity in agile software development. The goal of the presented study was to determine the influence of individual competence on software development effort estimation. In particular, we measured both the accuracy of effort estimation and the duration of the estimation process itself, both for three different estimation methods. The subjects of our study were teams of students of a graduate-level software engineering course at the University of Ljubljana, Faculty of Computer and Information Science. Based on the grades that individual students attained in their undergraduate study, we classified each team as ‘high-competence’ or ‘low-competence’ and additionally as ‘heterogeneous’ or ‘homogeneous’ (the criterion here being the variance of the members’ average grades). We found out that there was no significant difference in effort estimation accuracy neither between high-competence and low-competence teams nor between heterogeneous and homogeneous teams, regardless of which estimation method was used. However, high-competence teams spent significantly less time on effort estimation than low-competence ones. Likewise, for two of the employed estimation methods, heterogeneous teams completed effort estimation in a significantly shorter time than homogeneous teams. These results might benefit both academic and professional community.
26 Jun 2023Submitted to Software: Practice and Experience
26 Jun 2023Submission Checks Completed
26 Jun 2023Assigned to Editor
07 Jul 2023Review(s) Completed, Editorial Evaluation Pending
31 Jul 2023Reviewer(s) Assigned
17 Sep 2023Editorial Decision: Revise Major
29 Jan 2024Reviewer(s) Assigned