SUMMARYProgram slicing is a useful technique for debugging, testing and program integration. Intuitively, by the slice of a program P is meant, for a point n and a variablev in P, the set of statements and expressions in P that affect the value of v at n. To determine a slice, there must be a precise analysis of the dependencies among the statements in the program. It is difficult, on the other hand, to analyze the program containing recursions. This paper presents a static analysis for the dependencies in the program containing recursion, as well as the algorithm to determine the slice based on the result of the analysis. To cope with the recursive definition of the procedure, the proposed algorithm assumes the interprocedure information needed in the computation. This information is modified to the correct direction, and the process is iterated until the result converges.The program dependence graph is extended to hold the interprocedure information. Compared to the conventional algorithm, the proposed algorithm can analyze efficiently the program containing recursions, and can be used in the system to provide interactively the slice information.
Grid middleware such as the Globus toolkit and grid standards such as the Open Grid Services Architecture (OGSA) are intended to be expressive enoughfor building distributed enterprise applications, yet their use in this context remains largely unexplored. Here, two specific issues related to the use ofgrid technology for web application systems, an important class of enterprise applications, are examined. The first is whether existing middleware can be used to move legacy web applications to a grid platform, and ifso, how; the second is whether such grid-enabling brings advantages in terms of additional functionality, enhanced performance, or simplified management. These issues are addressed by grid-enabling a sample J2EE Internet banking application and comparing its performance with the original version, and then designing a scalable software architecture that can use the dynamic resource allocation facilities ofgrids to handle fluctuating client demands. Initial performance studies suggest that the architecture can indeed scale in response to changes in client load, indicating that the application of grid technology in this context is potentially useful as a way to enhance the manageability ofthe overall system. 0-7803-9074-
We propose a data processing platform that can analyze a large amount of tree-structured data. The proposed platform stores tree-structured data in separated files corresponding to each attribute, and uses MapReduce framework for distributed computing. These methods enable to reduce disk I/O load, and to avoid computationally-intensive processing, such as grouping or combining of records. An early stage of data mining needs try-and-error processes to find out how to analyze and utilize the data. Our platform speeds up computations of the try-and-error processes, such as appending new attributes and calculating statistics of attributes. Experimental results show that the proposed methods are efficient to process large-scale tree-structure data, and our platform is comparable or superior to a traditional relational database system. With the proposed platform, it became possible to process 90 GB data within 5 minutes on 6 benchmark tasks. We also describe system architecture for the try-and-error phase, which integrates the proposed platform and a few Web applications. The main contributions of this paper are: (1) formulation of vertical partitioning for tree-structured data, (2) effective utilization of MapReduce, and (3) construction of large-scale data mining system for a try-and-error phase.
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