caa a22 4500 605495742 CHVBK 20210128100532.0 cr unu---uuuuu 210128e20151201xx s 000 0 eng 10.1007/s11219-014-9250-6 doi (NATIONALLICENCE)springer-10.1007/s11219-014-9250-6 Empirical analysis of factors affecting confirmation bias levels of software engineers [Elektronische Daten] [Gul Calikli, Ayse Bener] Confirmation bias is defined as the tendency of people to seek evidence that verifies a hypothesis rather than seeking evidence to falsify it. Due to the confirmation bias, defects may be introduced in a software product during requirements analysis, design, implementation and/or testing phases. For instance, testers may exhibit confirmatory behavior in the form of a tendency to make the code run rather than employing a strategic approach to make it fail. As a result, most of the defects that have been introduced in the earlier phases of software development may be overlooked leading to an increase in software defect density. In this paper, we quantify confirmation bias levels in terms of a single derived metric. However, the main focus of this paper is the analysis of factors affecting confirmation bias levels of software engineers. Identification of these factors can guide project managers to circumvent negative effects of confirmation bias, as well as providing guidance for the recruitment and effective allocation of software engineers. In this empirical study, we observed low confirmation bias levels among participants with logical reasoning and hypothesis testing skills. Springer Science+Business Media New York, 2014 Confirmation bias nationallicence Human factors nationallicence Software psychology nationallicence Calikli Gul Computing and Communications, Faculty of Maths, Computing and Technology, The Open University, Milton Keynes, UK aut Bener Ayse Data Science Laboratory, Mechanical and Industrial Engineering, Ryerson University, Toronto, Canada aut Software Quality Journal Springer US; http://www.springer-ny.com 23/4(2015-12-01), 695-722 0963-9314 23:4<695 2015 23 11219 https://doi.org/10.1007/s11219-014-9250-6 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s11219-014-9250-6 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Calikli Gul Computing and Communications, Faculty of Maths, Computing and Technology, The Open University, Milton Keynes, UK aut NATIONALLICENCE 700 1- Bener Ayse Data Science Laboratory, Mechanical and Industrial Engineering, Ryerson University, Toronto, Canada aut NATIONALLICENCE 773 0- Software Quality Journal Springer US; http://www.springer-ny.com 23/4(2015-12-01), 695-722 0963-9314 23:4<695 2015 23 11219