TY - GEN
T1 - The mind is a powerful place
T2 - 43rd IEEE/ACM International Conference on Software Engineering, ICSE 2021
AU - Wyrich, Marvin
AU - Preikschat, Andreas
AU - Graziotin, Daniel
AU - Wagner, Stefan
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021/5
Y1 - 2021/5
N2 - Static code analysis tools and integrated development environments present developers with quality-related software metrics, some of which describe the understandability of source code. Software metrics influence overarching strategic decisions that impact the future of companies and the prioritization of everyday software development tasks. Several software metrics, however, lack in validation: we just choose to trust that they reflect what they are supposed to measure. Some of them were even shown to not measure the quality aspects they intend to measure. Yet, they influence us through biases in our cognitive-driven actions. In particular, they might anchor us in our decisions. Whether the anchoring effect exists with software metrics has not been studied yet. We conducted a randomized and double-blind experiment to investigate the extent to which a displayed metric value for source code comprehensibility anchors developers in their subjective rating of source code comprehensibility, whether performance is affected by the anchoring effect when working on comprehension tasks, and which individual characteristics might play a role in the anchoring effect. We found that the displayed value of a comprehensibility metric has a significant and large anchoring effect on a developer's code comprehensibility rating. The effect does not seem to affect the time or correctness when working on comprehension questions related to the code snippets under study. Since the anchoring effect is one of the most robust cognitive biases, and we have limited understanding of the consequences of the demonstrated manipulation of developers by non-validated metrics, we call for an increased awareness of the responsibility in code quality reporting and for corresponding tools to be based on scientific evidence.
AB - Static code analysis tools and integrated development environments present developers with quality-related software metrics, some of which describe the understandability of source code. Software metrics influence overarching strategic decisions that impact the future of companies and the prioritization of everyday software development tasks. Several software metrics, however, lack in validation: we just choose to trust that they reflect what they are supposed to measure. Some of them were even shown to not measure the quality aspects they intend to measure. Yet, they influence us through biases in our cognitive-driven actions. In particular, they might anchor us in our decisions. Whether the anchoring effect exists with software metrics has not been studied yet. We conducted a randomized and double-blind experiment to investigate the extent to which a displayed metric value for source code comprehensibility anchors developers in their subjective rating of source code comprehensibility, whether performance is affected by the anchoring effect when working on comprehension tasks, and which individual characteristics might play a role in the anchoring effect. We found that the displayed value of a comprehensibility metric has a significant and large anchoring effect on a developer's code comprehensibility rating. The effect does not seem to affect the time or correctness when working on comprehension questions related to the code snippets under study. Since the anchoring effect is one of the most robust cognitive biases, and we have limited understanding of the consequences of the demonstrated manipulation of developers by non-validated metrics, we call for an increased awareness of the responsibility in code quality reporting and for corresponding tools to be based on scientific evidence.
KW - Anchoring effect
KW - Behavioral software engineering
KW - Code comprehension
KW - Cognitive bias
KW - metrics
KW - Placebo effect
UR - http://www.scopus.com/inward/record.url?scp=85110757318&partnerID=8YFLogxK
U2 - 10.1109/ICSE43902.2021.00055
DO - 10.1109/ICSE43902.2021.00055
M3 - Conference contribution
AN - SCOPUS:85110757318
T3 - Proceedings - International Conference on Software Engineering
SP - 512
EP - 523
BT - Proceedings - 2021 IEEE/ACM 43rd International Conference on Software Engineering, ICSE 2021
PB - IEEE Computer Society
Y2 - 22 May 2021 through 30 May 2021
ER -