Measuring the Use of Norm Models to Interpret Software Licenses: An Eye Tracking Study

Sharing of software source code has flourished through the open source initiative. Freelance software developers and enterprises alike are engaged in using, distributing and contributing to open source software. To make software exchanges possible, licenses need to be applied to source code when they are released to an open source community. As the procurement of open source software often happens in a federated manner (i.e., by individual developers), the norms in licenses need to be interpreted by individuals that have little to no legal experience. Norms represent legal statements expressing the binding rules that regulate the conduct of parties involved in a legal relation. Research efforts in software engineering have focused on the development of norm models for reasoning about legal compliance. These efforts assume that models support the reader to interpret the legal text. This research seeks to investigate this assumption in the context of a proposed interface in which norm models are integrated with corresponding software license in a multi-view interface inspired by program comprehension tools. Using a case study designed research, we will investigate the visual attention pattern of users, relative to license text and norm models representations, when given an open source license comprehension task. The goal of this research is to have an initial understanding of the use of norm model representations in the context of license comprehension. The logic linking specific propositions to the collected measures will be based on eye-tracking metrics derived from fixations. For this case study, subjects will be selected based on expertise and background involving software license comprehension. Additionally, this exploratory case study will contribute to the development of interesting research questions regarding norm-models based interface to interpret legal texts