Towards a Metric Suite Proposal to Quantify Confirmation Biases of Developers

Calikli, Gul; Bener, Ayse; Aytac, Turgay and Bozcan, Ovunc (2013). Towards a Metric Suite Proposal to Quantify Confirmation Biases of Developers. In: Empirical Software Engineering and Measurement, 2013 ACM / IEEE International Symposium on, IEEE, pp. 363–372.

DOI: https://doi.org/10.1109/ESEM.2013.47

URL: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?...

Abstract

The goal of software metrics is the identification and measurement of the essential parameters that affect software development. Metrics can be used to improve software quality and productivity. Existing metrics in the literature are mostly product or process related. However, thought processes of people have a significant impact on software quality as software is designed, implemented and tested by people. Therefore, in defining new metrics, we need to take into account human cognitive aspects. Our research aims to address this need through the proposal of a new metric scheme to quantify a specific human cognitive aspect, namely "confirmation bias". In our previous research, in order to quantify confirmation bias, we defined a methodology to measure confirmation biases of people. In this research, we propose a metric suite that would be used by practitioners during daily decision making. Our proposed metric set consists of six metrics with a theoretical basis in cognitive psychology and measurement theory. Empirical sample of these metrics are collected from two software companies that are specialized in two different domains in order to demonstrate their feasibility. We suggest ways in which practitioners may use these metrics to improve software development process.

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