![]() ![]() # :lambda$scanClasses$19(.Resource,java.lang. # .classreading.MetadataReader:getClassMetadata() # .classreading.MetadataReaderFactory:getMetadataReader(.Resource) # .support.ResourcePatternResolver:getResources() # :getSqlSession(.SqlSessionFactory.ExecutorType.PersistenceExceptionTranslator) # :getSqlSession(.SqlSessionFactory) !entry! # $SqlSessionInterceptor:invoke(,) !entry! # :closeSqlSession(.SqlSession.SqlSessionFactory) boolean isClusterFile true List statCalcs new ArrayList() double.class files (these are used mostly to resolve types in source code). To view the source code for java.lang Double MINVALUE. You need to build some custom code to implement the ideas in the first paragraph, but DMS can provide most of the raw material. Write a program that uses the StatCalc class to. class files you weren't clear as to whether you wanted to climb into class files, too, hunting for information. Exercise 5.2 involved a class, StatCalc.java, that could compute some statistics of a set of numbers. DMS has an optional Java Front End that provides a full Java parser, builds Java ASTs and symbol tables, and can construct a call graph. The DMS Software Reengineering Toolkit is generalized compiler technology providing basic services of parsing, AST building/navigation, symbol table building/navigation, control flow, data flow and call graph construction. Then a custom scan of the ASTs of the functions in the call graph rooted in each implementing method (as indicated by the symbol tables) of an abstract method gives you a chance to locate a new operation whose type is the specific class of interest. Write a GUI program that uses the StatCalc class to compute and display statistics of numbers entered by the user. You can read the source code for this class in the file StatCalc.java. It sounds like you want something that provides access to the abstract syntax and a complete symbol table. I have written a little class called StatCalc that can be used to compute these statistics, as well as the sum of the items in the dataset and the number of items in the dataset.
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