A context model for IDE-based recommendation systems

Abstract

Context, as modeled through variables called contextual factors, can improve human-computer interaction. To date, in applications supporting software development, such as integrated development environments (IDEs) and recommendation systems for software engineering (RSSEs), contextual factors have generally been constrained to project artifacts, such as source code. In this paper, we present a context model that includes thirteen contextual factors, which capture various situations in which developers interact with an IDE. This context model can be used to support and enhance user interaction with an IDE or to improve the accuracy and timing of recommendations produced by RSSEs. To assess whether the proposed contextual factors are informative for a context model, we statistically evaluated the correlations between IDE command usage and different situations, as they are described by the factors. If a contextual factor correlates with the usage of a command this means that the user is using the command differently when the values of the contextual factor change. We discovered that different factors correlate with different commands and that all the factors correlate with some commands, hence, when a context change is detected, we can also expect a change in the interaction with an IDE.