SDexplorer: a generic toolkit for smoothly exploring massive-scale sequence diagram
作者： Kaixie Lyu , Kunihiro Noda , Takashi Kobayashia
关键词: Scalability 、 Reverse engineering 、 Filter (video) 、 Program comprehension 、 Sequence diagram 、 Programming language 、 Computer science 、 Software 、 Visualization 、 Diagram
摘要: To understand program's behavior, using reverse-engineered sequence diagram is a valuable technique. In practice, researchers usually record execution traces and generate according to them. However, the can be too large read while treating real-world software due massiveness of traces. Several studies on minimizing/compressing diagrams have been proposed; however, resulting may either still or losing important information. Besides, existing tools are highly customized for certain research purpose. address these problems, we present generic toolkit SDExplorer in this paper, which flexible lightweight tool effectively explore massive-scale scalable manner. Additionally, supports popular features (i.e. search, filter, grouping, etc.). We believe it an easy-to-use promising future evaluate compare techniques real maintenance tasks. available at https://lyukx.github.io/SDExplorer/.
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