No abstract

No abstract

Abstract-Self-explanation is one cognitive strategy through which developers comprehend error notifications. Selfexplanation, when left solely to developers, can result in a significant loss of productivity because humans are imperfect and bounded in their cognitive abilities. We argue that modern IDEs offer limited visual affordances for aiding developers with self-explanation, because compilers do not reveal their reasoning about the causes of errors to the developer.The contribution of our paper is a foundational set of visual annotations that aid developers in better comprehending error messages when compilers expose their internal reasoning. We demonstrate through a user study of 28 undergraduate Software Engineering students that our annotations align with the way in which developers self-explain error notifications. We show that these annotations allow developers to give significantly better self-explanations when compared against today's dominant visualization paradigm, and that better self-explanations yield better mental models of notifications.The results of our work suggest that the diagrammatic techniques developers use to explain problems can serve as an effective foundation for how IDEs should visually communicate to developers.

Propellant mass-gauging in unsettled (sloshing) fluids is an important and unsolved problem in spacecraft operations and mission design. In the present work, we demonstrate the efficacy of the experimental modal analysis technique in determining the volume of fluid present in model spacecraft propellant tanks undergoing significant sloshing. Using data acquired over approximately 37 minutes of time in zero-gravity conditions provided over two years of parabolic flights, we estimate the resolution of the technique at low tank fill-fractions where other mass-gauging techniques are known to fail.

No abstract