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On researcher bias in Software Engineering experiments
University of Bari, ITA.
Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för programvaruteknik.ORCID-id: 0000-0002-0679-4361
University of Basilicata, ITA.
University of Bari, ITA.
Vise andre og tillknytning
2021 (engelsk)Inngår i: Journal of Systems and Software, ISSN 0164-1212, E-ISSN 1873-1228, Vol. 182, artikkel-id 111068Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

Researcher bias occurs when researchers influence the results of an empirical study based on their expectations, either consciously or unconsciously. Researcher bias might be due to the use of Questionable Research Practices (QRPs). In research fields like medicine, blinding techniques have been applied to counteract researcher bias. In this paper, we present two studies to increase our body of knowledge on researcher bias in Software Engineering (SE) experiments, including: (i) QRPs potentially leading to researcher bias; (ii) causes behind researcher bias; and (iii) possible actions to counteract researcher bias with a focus on, but not limited to, blinding techniques. The former is an interview study, intended as an exploratory study, with nine experts of the empirical SE community. The latter is a quantitative survey with 51 respondents, who were experts of the above-mentioned community. The findings from the exploratory study represented the starting point to design the survey. In particular, we defined the questionnaire of this survey to support the findings from the exploratory study. From the interview study, it emerged that some QRPs (e.g., post-hoc outlier criteria) are acceptable in certain cases. Also, it appears that researcher bias is perceived in SE and, to counteract researcher bias, a number of solutions have been highlighted. For example, duplicating the data analysis in SE experiments or fostering open data policies in SE conferences/journals. The findings from the interview study are mostly confirmed by those from the survey, and allowed us to delineate recommendations to counteract researcher bias in SE experiments. Some recommendations are intended for SE researchers, while others are purposeful for the boards of SE research venues. © 2021 Elsevier Inc.

sted, utgiver, år, opplag, sider
Elsevier Inc. , 2021. Vol. 182, artikkel-id 111068
Emneord [en]
Blinding, Experimenter bias, Researcher bias, Survey, Open Data, Software engineering, Blinding technique, Body of knowledge, Empirical studies, Exploratory studies, Interview study, Research fields, Software engineering experiments, Surveys
HSV kategori
Identifikatorer
URN: urn:nbn:se:bth-22141DOI: 10.1016/j.jss.2021.111068ISI: 000697027700003Scopus ID: 2-s2.0-85114408763OAI: oai:DiVA.org:bth-22141DiVA, id: diva2:1595132
Tilgjengelig fra: 2021-09-17 Laget: 2021-09-17 Sist oppdatert: 2022-01-17bibliografisk kontrollert

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