CHS: SMALL: Collaborative Research: Adaptive Development Environments: Modeling and Supporting Cognitive Styles of Software Developers

University Of Tennessee Knoxville, Knoxville TN

Investigators

Abstract

This research will investigate mechanisms to seamlessly support the different cognitive styles and information needs of software developers, such that development environments can model the developers' behavior and adapt to their individual needs. Software development is a notoriously complex endeavor that requires developers to use an environment where information is fragmented across different tools and repositories. Although integrated development environments may help, they are often inadequate in supporting developers' information needs. Major barriers are caused by development environments not adapting to the developers' cognitive styles and information needs. This project will advance the knowledge of software developers' behavior and transform software development tools to be more efficient and more inclusive to a wider population of software developers. It also addresses a fundamental issue concerning broader participation, that of individual differences in problem solving. Models and tools that accommodate these individual differences may help level the playing field. The methodology involves four stages: (1) conduct empirical studies to understand developers' information needs and cognitive styles, (2) build predictive models of developer behavior based on their cognitive styles, (3) create development environments that adapt to support developers' cognitive styles, and (4) evaluate the effectiveness of the predictive models and the adaptive environments. This work will generate a deep understanding of the impact of cognitive styles on how developers learn and make sense of the development history to place their work in the context of past and ongoing changes. It is novel in providing an integrated perspective on the broader set of history explorations in which programmers engage when they are programming as well as in leading to empirically validated predictive models that not only model how development activities are influenced by differences in cognitive styles, but also by the development task at hand. Key goals include the design and evaluation of a novel environment that not only allows developers to seamlessly explore different aspects of the development histories, but also adapts to support the individual needs of a developer. Extensive curated versions of the collected data will be developed and shared with the scientific community to promote additional research into the topic. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.