Model-Based Diagnosis of Software Functional Dependencies
Abstract: Researchers have developed framework for diagnosis analysis that are called “Model Based Diagnosis Systems”. These systems are very general in scope, covers a wide range of malfunctions uncovering and identifying repair measures. This thesis is an effort to diagnose complex and lengthy static source code. Without executing source code discrepancies can only be identified by finding procedural dependencies. With respect to modern programming languages, many software bugs arise due to logical erroneous calculations or miss handling of data structures. Modern Integrated Development Environments (IDE) like Visual Studio, J-Builder and Eclipse etc are strong enough to analyze and parse static text code to identify syntactical and type conversion errors. Some of IDE’s can automatically fix such kind of errors or provide different possible suggestions to developer. In this thesis we have analyzed and extracted functional dependencies of source code. This extracted information can increase programmer’s understanding about code when they are extremely large or complex. By modeling this information into a model system, reduces time to debug the code in case of any failure. This increases productivity in terms of software development and in debugger skills as well. The main contribution of this thesis is the use of model based diagnosis techniques on software functional dependency graphs and charts. Keywords: Model Based Diagnosis Systems, Integrated Development Environments, Procedural Dependencies, Erroneous calculations, Call graphs, Directed graph markup language.
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