• Journal of Information Processing Systems
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• v.3 no.1
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• pp.26-32
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• 2007

Although the Java bytecode has numerous advantages, it also has certain shortcomings such as its slow execution speed and difficulty of analysis. In order to overcome such disadvantages, a bytecode analysis and optimization must be performed. The control flow of the bytecode should be analyzed; next, information is required regarding where the variables are defined and used to conduct a dataflow analysis and optimization. There may be cases where variables with an identical name contain different values at different locations during execution, according to the value assigned to a given variable in each location. Therefore, in order to statically determine the value and type, the variables must be separated according to allocation. In order to achieve this, variables can be expressed using a static single assignment form. After transformation into a static single assignment form, the type information of each node expressed by each variable and expression must be configured to perform a static analysis and optimization. Based on the basic type information, this paper proposes a method for finding the related equivalent nodes, setting nodes with strong connection components, and efficiently assigning each node type.

• The Journal of the Korea Contents Association
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• v.6 no.2
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• pp.117-126
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• 2006

Although the Java bytecode has numerous advantages, there are also shortcomings such as slow execution speed and difficulty in analysis. In order to overcome such disadvantages, bytecode analysis and optimization must be performed. First control flow of the bytecode should be analyzed, after which information is required regarding where the variables are defined and used to conduct data flow analysis and optimization. There may be cases where variables with an identical name contain different values at a different location during the execution according to the value assigned to a variable in each location. Therefore, in order to statically determine the value and type, the variables must be separated according to allocation. In order to do so, the variables can be expressed using a static single assignment form. After the transformation into a static single assignment form, the type information of each node expressed by each variable and expression must be configured to perform static analysis and optimization. Based on the basic type information, this paper proposes a method for finding related equivalent nodes, setting the nodes with strongly connection components and efficiently assigning each node the type.

• Journal of the Korea Society of Computer and Information
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• v.11 no.1 s.39
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• pp.107-117
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• 2006

Java language creates class files through Java compiler. Class files include informations involved with achievement of program. We can do analysis and optimization for efficient codes by analyzing class files. This paper analyzes bytecodes using informations of Java class files. We translate stack-based Java bytecodes into 3-address codes. Then we translate into static single assignment form using the 3-address codes. Static single assignment form provides a compact representation of a variable's definition-use information. Static single assignment form is often used as an intermediate representation during code optimization. Static sing1e assignment form renames each occurrence of a variable such that each variable is defined only once.

• The Journal of the Korea Contents Association
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• v.5 no.3
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• pp.73-81
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• 2005

CTOC(Classes To Optimized Classes) is a Java bytecode framework for optimization and analysis. Although Java bytecode has a significant amount of type information embedded in it, there are no explicit types for local variables. However, knowing types for local variables is very useful for both program optimization and analysis. This paper is a first part of CTOC framework. In this paper, we present methods for inferring static types for local variables in a 3-address, stackless, representation of Java bytecode. We use SSA Form(Single Static Assignment Form) for spliting local variables. Splited local variables will use to prepare for static type inference.

• Journal of the Korea Society of Computer and Information
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• v.11 no.4 s.42
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• pp.87-96
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• 2006

Although bytecode has many good features, it has slow execution speed and it is not an ideal representation for program analysis or optimization. For analysises and optimizations. bytecode must be translated to a Static Single Assignment Form(SSA Form) But when bytecode is translated a SSA Form it has lost type informations of son variables. For resolving these problem in this paper, we create extended control flow graph on bytecode. Also we convert the control flow graph to SSA Form for static analysis. Calculation about many informations such as dominator, immediate dominator. dominance frontier. ${\phi}$-Function. renaming are required to convert to SSA Form. To obtain appropriate type for generated SSA Form, we proceed the followings. First. we construct call graph and derivation graph of classes. And the we collect information associated with each node. After finding equivalence nodes and constructing Strongly Connected Component based on the collected informations. we assign type to each node.

• Proceedings of the Korean Information Science Society Conference
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• 2007.06c
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• pp.505-509
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• 2007

Static Single Assignment (SSA) form is an intermediate representation which encodes information about data and control flow that is use used to facilitate program analysis and optimization. SSA form simplifies this process with its size linear to program size. Thus we use SSA form to efficiently facilitate bytecode level analysis and optimizations in our CTOC program processor project. In this paper, we illustrate the application and implement implementation of SSA form using an example. We give the conclusion after experimental results.

• Journal of Computing Science and Engineering
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• v.2 no.3
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• pp.301-320
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• 2008

Partial redundancy elimination (PRE) is an interesting compiler optimization because of its effectiveness and generality. Among many PRE algorithms, the one in static single assignment form (SSAPRE) has benefits over other bit-vector-based PRE algorithms. It preserves the properties of the SSA form after PRE and exploits the sparsity of the SSA form, resulting in reduced analysis and optimization time. This paper presents a practical improvement of the SSAPRE algorithm that further reduces the analysis and optimization time. The underlying idea is removing unnecessary ${\Phi}$'s during the ${\Phi}$-Insertion phase that is the first step of SSAPRE. We classify the expressions into three categories: confined expressions, local expressions, and the others. We show that unnecessary ${\Phi}$'s for confined and local expressions can be easily detected and removed. We implement our locality-based SSAPRE algorithm in a C compiler and evaluate its effectiveness with 20 applications from SPEC benchmark suites. In our measurements, on average 91 of ${\Phi}$'s identified by the original demand-driven SSAPRE algorithm are unnecessary for PRE. Pruning these unnecessary ${\Phi}$'s in the ${\Phi}$-Insertion phase makes our locality-based SSAPRE algorithm 1.8 times faster, on average, than the original SSAPRE algorithm.

• The KIPS Transactions:PartD
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• v.13D no.7 s.110
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• pp.939-946
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• 2006

Although the Java bytecode has numerous advantages, there are also shortcomings such as slow execution speed and difficulty in analysis. In order to overcome such disadvantages, bytecode analysis and optimization must be performed. We implements CTOC for optimized codes. An extended CFG must be first created in order to analyze and optimize a bytecode. Due to unique bytecode properties, the existing CFG must be expanded according to the bytecode. Furthermore, the CFG must be converted into SSA Form for a static analysis, for which calculation is required for various information such as the dominate relation, dominator tree, immediate dominator, $\phi$-function, rename, and dominance frontier. This paper describes the algorithm and the process for converting the existing CFG into the SSA From. The graph that incorporates the SSA Form is later used for type inference and optimization.

• Journal of Korean Society of Transportation
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• v.11 no.1
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• pp.67-86
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• 1993

A formulation of dynamic traffic assignment between multiple origins and single destination was first introduced in 1987 by Merchant and Nemhauser, and then expanded for multiple destination in the late 1980's (Carey, 1987). Based on behavioral choice theory which provides proper demand elasticities with respect to changes in policy variables, traffic phenomena can be analysed more realistically, especially in peak periods. However, algorithms for these models are not well developed so far(working with only small toy network) and solutions of these models are not unique. In this paper, a new model is developed which keeps the simplicity of static models, but provides the sensitivity of dynamic models with changes of O-D flows over time. It can be viewed as a joint departure time and route choice model, in the given time periods(6-7, 7-8, 8-9 and 9-10 am). Standard multinomial logit model has been used for simulating the choice behavior of destination, mode, route and departure time within a framework of the incremental network assignment model. The model developed is workable in a PC 386 with 175 traffic zones and 3581 links of Seoul and tested for evaluating the exclusive use of Namsan tunnel for HOV and the left-turn prohibition. Model's performance results and their statistical significance are also presented.

• Journal of the Korea Society of Computer and Information
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• v.21 no.9
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• pp.91-100
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• 2016

In this research, emergency vehicle dispatching problems faced with in the wake of massive natural disasters are considered. Here, the emergency vehicle dispatching problems can be regarded as a single machine stochastic scheduling problems, where the processing times are independently and identically distributed random variables, are considered. The objective of minimizing the expected number of tardy jobs, with distinct job due dates that are independently and arbitrarily distributed random variables, is dealt with. For these problems, optimal static-list policies can be found by solving corresponding assignment problems. However, for the special cases where due dates are exponentially distributed random variables, using a proposed dynamic programming approach is found to be relatively faster than solving the corresponding assignment problems. This so-called Pivot Dynamic Programming approach exploits necessary optimality conditions derived for ordering the jobs partially.