Abstract
Active database systems have been developed since several years and represent a powerful means to respond automatically to events that are taking place inside or outside the database. However, one of the main stumbling blocks for their widespread use is the lack of proper tools for the verification of active database behavior. This paper copes with this need by presenting TriGS Debugger, a tool which supports mechanisms for predicting, understanding and manipulating active database behavior. First, TriGS Debugger provides a holistic view of both active and passive behavior by visualizing their interdependencies, thus facilitating pre-execution analysis. Active behavior is represented in terms of Event/Condition/Action rules, passive behavior is represented in terms of classes and their methods. Second, post-execution analysis is supported by tracing and graphically representing active behavior not only in terms of primitive events and serially executed rules but also by considering composite events and rules, which are executed in parallel. Special emphasize is drawn on the complexity of the resulting trace data by allowing to customize the visualization using a filter mechanism as well as by providing the possibility to mine behavior patterns out of the trace data and to visualize them in an aggregated fashion. Third, TriGS Debugger allows to interactively examine and manipulate the active behavior at runtime. In particular, mechanisms are provided to set breakpoints, to replay single events or event sequences, to (de)activate selected events and rules, and to modify rule properties and the rule code itself.
Original language | English |
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Publication status | Published - Mar 2000 |
Fields of science
- 101004 Biomathematics
- 101027 Dynamical systems
- 101028 Mathematical modelling
- 101029 Mathematical statistics
- 101014 Numerical mathematics
- 101015 Operations research
- 101016 Optimisation
- 101017 Game theory
- 101018 Statistics
- 101019 Stochastics
- 101024 Probability theory
- 101026 Time series analysis
- 102 Computer Sciences
- 102001 Artificial intelligence
- 102003 Image processing
- 102004 Bioinformatics
- 102013 Human-computer interaction
- 102018 Artificial neural networks
- 102019 Machine learning
- 103029 Statistical physics
- 106005 Bioinformatics
- 106007 Biostatistics
- 202017 Embedded systems
- 202035 Robotics
- 202036 Sensor systems
- 202037 Signal processing
- 305901 Computer-aided diagnosis and therapy
- 305905 Medical informatics
- 305907 Medical statistics
- 102032 Computational intelligence
- 102033 Data mining
- 101031 Approximation theory