Identifying properties of UML state machine diagrams that affect data and control dependence

  • Authors:

  • HyeonJeong Kim;Vidroha Debroy;DooHwan Bae

  • Affiliations:

  • Korea Advanced Institute of Science and Technology, GuSeong Dong, YuSeong Gu, DaeJeon, South Korea and University of Texas at Dallas, Richardson;University of Texas at Dallas, Richardson;Korea Advanced Institute of Science and Technology, GuSeong Dong, YuSeong Gu, DaeJeon, South Korea

  • Venue:
  • Proceedings of the 2011 ACM Symposium on Applied Computing
  • Year:
  • 2011

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Abstract

Program slicing is a useful reduction technique in many areas such as debugging and testing, and thus, there has also been some research to try and apply slicing techniques to flat state-based models at the design level, for their maintenance and quality improvement. However, such state-based models have difficulties in specifying large and complex software systems, and so the benefit obtained from slicing such models, is very limited. In contrast, UML state machine diagrams can properly describe the behavior of large software systems; but it is difficult to apply a slicing algorithm to automatically reduce the diagram with respect to a point of interest, because of the unique properties (such as hierarchy and orthogonality) of these diagrams. In this paper, we identify important issues relevant to the slicing of UML state machine diagrams with regards to data and control dependence. We also show why the unique properties of these diagrams are important to consider when retrieving data and control dependence information, by virtue of an illustrative example.