Conference Paper

Telling stories about GNOME with Complicity.

Fac. of Inf., REVEAL, Univ. of Lugano, Lugano, Switzerland
DOI: 10.1109/VISSOF.2011.6069459 Conference: Proceedings of the 6th IEEE International Workshop on Visualizing Software for Understanding and Analysis, VISSOFT 2011, Williamsburg, VA, USA, September 29-30, 2011
Source: DBLP

ABSTRACT Traditionally, the target of software evolution research has been single software systems. However, in the recent years, researchers observed that software systems are often not developed in isolation, but within a larger context: the ecosystem level. Analyzing software evolution at the ecosystem level allows a better understanding of the evolution phenomenon, as the entire development context can be studied. Nonetheless, software ecosystem analysis is challenging because of the sheer amount of data to be processed and understood. We present Complicity, a web-based application that supports software ecosystem analysis by means of interactive visualizations. Complicity breaks down the data quantity by offering two abstraction levels: ecosystem and entity. To support a thorough exploration and analysis of ecosystem data, the tool provides a number of fixed viewpoints and the possibility of creating new viewpoints with given software metrics. We illustrate in a case study how Complicity can help to understand the GNOME ecosystem in a bottom-up approach, starting from a single project and contributor towards their impact on the ecosystem.

1 Bookmark
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: We present a dataset of the open source software ecosystem GNOME from a social point of view. We have collected historical data about the contributors to all GNOME projects stored on, taking into account the problem of identity matching, and as-sociating different activity types to the contributors. This type of information is very useful to complement the traditional, source-code related information one can ob-tain by mining and analyzing the actual source code. The dataset can be obtained at mgoeminne/sgl-flossmetric-dbmerge.
    Mining Software Repositories; 01/2013

Full-text (2 Sources)

Available from
Jun 4, 2014