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.

Despite the proliferation of screens in everyday environments, providing values to remote displays for exploring complex data sets is still challenging. Enhanced input for remote screens can increase their utility and enable the construction of rich data-driven environments. Here, we investigate the opportunities provided by a variable movement resistance slider (VMRS), based on a motorized slide potentiometer. These devices are often used in professional soundboards as an effective way to provide discrete input. We designed, built and evaluated a remote input device using a VMRS that facilitates choosing a number on a discrete scale. By comparing our prototype to a traditional slide potentiometer and a software slider, we determined that for conditions where users are not looking at the slider, VMRS can offer significantly better performance and accuracy. Our findings contribute to the understanding of discrete input and enable building new interaction scenarios for large display environments.