| dc.description.abstract | The search for an understanding of how the developer’s brain behaves during software development is an object of study of increasing interest in recent years. Despite the development of new studies collecting psychophysiological data from developers and using them in experiments, little has been explored about the applicability of such data in software engineering. Therefore, the development of this work aims to propose a tool for the integration of psychophysiological data in integrated development environments, to present them to developers, and verify their impact on the software development process. Therefore, the tool CognIDE was developed based on the opportunities identified by conducting a systematic mapping of the literature, where 2084 studies were identified, of which 27 were selected as primary studies. For the evaluation of the proposed tool, a controlled experiment was carried out and executed among 61 individuals in the technology area, aiming to assess the impact of presenting, in the IDE, the Cognitive Load metric on their Anomalies Perceptions and Levels of Refactoring Intention. As a result, it was observed that presenting the Cognitive Load metric, when it presents its value as High, combined with the number of Code Anomalies, can assist the developer in the identification of anomalies, in addition to serving as input for the decision of refactoring excerpts from source code. The development of this work brought as main contributions: (1) expansion of the state-of-the-art regarding the integration of psychophysiological data in IDEs and its applicability in software engineering; (2) the implementation of the CognIDE tool and its approach to data integration; (3) empirical knowledge about the impact of displaying developers’ psychophysiological data in IDEs. | |
