We present the design and evaluation of HyperStorylines, a technique that generalizes Storylines to visualize the evolution of relationships involving multiple types of entities such as, for example, people, locations, and companies. Datasets which describe such multi-entity relationships are often modeled as hypergraphs, that can be difficult to visualize, especially when these relationships evolve over time. HyperStorylines builds upon Storylines, enabling the aggregation and nesting of these dynamic, multi-entity relationships. We report on the design process of HyperStorylines, which was informed by discussions and workshops with data journalists; and on the results of a comparative study in which participants had to answer questions inspired by the tasks that journalists typically perform with such data. We observe that although HyperStorylines takes some practice to master, it performs better for identifying and characterizing relationships than the selected baseline visualization (PAOHVis) and was preferred overall.
Test coverage is about assessing the relevance of unit tests against the tested application. It is widely acknowledged that a software with a "good" test coverage is more robust against unanticipated execution, thus lowering the maintenance cost. However, insuring a coverage of a good quality is challenging, especially since most of the available test coverage tools do not discriminate software components that require a "strong" coverage from the components that require less attention from the unit tests.Hapao is an innovative test coverage tool, implemented in the Pharo Smalltalk programming language. It employs an effective and intuitive graphical representation to visually assess the quality of the coverage. A combination of appropriate metrics and relations visually shapes methods and classes, which indicates to the programmer whether more effort on testing is required.This paper presents the essence of Hapao using a real world case study.
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