• Journal of the Korea Society of Computer and Information
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• v.12 no.2 s.46
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• pp.1-8
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• 2007

Although the Java bytecode has numerous advantages, there are also shortcomings such as slow execution speed and difficulty in analysis. Therefore, in order for the Java class file to be effectively executed under the execution environment such as the network, it is necessary to convert it into optimized code. We implements CTOC. In order to statically determine the value and type, CTOC uses the SSA Form which separates the variable according to assignment. Also, it uses a Tree Form for statements. But, due to insertion of the $\phi$-function in the process of conversion into the SSA Form, the number of nodes increased. This paper shows the dead code elimination to obtain a more optimized code in SSA Form. We add new live field in each node and achieve dead code elimination in tree structures. We can confirm after dead code elimination though test results that nodes decreases.

• Proceedings of the Korean Information Science Society Conference
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• 2004.10a
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• pp.529-531
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• 2004

Just-Just-in-Time 컴파일러를 이용하여 자바의 성능을 향상시키려면 여러 문제들을 극복하여야 한다. 이 문제 중 중요한 부분을 차지하는 것이 null check 코드와 array bound check코드를 어떻게 최적화하느냐는 것이다. Static한 컴파일 환경에서는 이미 많은 연구가 진행되어 매우 강력한 성능을 가지는 알고리즘이 알려져 있으나 이를 컴파일 시간이 수행시간의 일부인 Just-in-Time 컴파일 환경에 적응하기에는 컴파일 오버헤드가 너무 커서 적절하지 않다. 현재 Just-in-Time 컴파일러들은 가볍고 단순한 알고리즘을 적용하지만 중복된 array bounds check를 충분히 제거하지 못하거나 아니면 강력하지만 flow-insensitive한 SSA form을 기반으로 해야 하는 알고리즘을 사용하고 있다. SSA form의 적용은 SSA form으로의 변환과 되돌림에 의한 overhead로 가볍고 빠른 컴파일러를 지향하는 Just-in-Time 컴파일러에 부합되지 않는다. 본 논문은 변수간의 대소관계를 표현하는 그래프를 array bounds check 알고리즘에 적용해 충분한 power를 내면서도 flow-sensitive한 환경에서 동작하는 알고리즘을 제안한다.

• 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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.4
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• pp.575-594
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• 2010

In this study, we propose a space search algorithm (SSA) and then introduce a hybrid optimization of fuzzy inference systems based on SSA and information granulation (IG). In comparison with "conventional" evolutionary algorithms (such as PSO), SSA leads no.t only to better search performance to find global optimization but is also more computationally effective when dealing with the optimization of the fuzzy models. In the hybrid optimization of fuzzy inference system, SSA is exploited to carry out the parametric optimization of the fuzzy model as well as to realize its structural optimization. IG realized with the aid of C-Means clustering helps determine the initial values of the apex parameters of the membership function of fuzzy model. The overall hybrid identification of fuzzy inference systems comes in the form of two optimization mechanisms: structure identification (such as the number of input variables to be used, a specific subset of input variables, the number of membership functions, and polyno.mial type) and parameter identification (viz. the apexes of membership function). The structure identification is developed by SSA and C-Means while the parameter estimation is realized via SSA and a standard least square method. The evaluation of the performance of the proposed model was carried out by using four representative numerical examples such as No.n-linear function, gas furnace, NO.x emission process data, and Mackey-Glass time series. A comparative study of SSA and PSO demonstrates that SSA leads to improved performance both in terms of the quality of the model and the computing time required. The proposed model is also contrasted with the quality of some "conventional" fuzzy models already encountered in the literature.

• 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.

• Journal of KIISE:Software and Applications
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• v.32 no.12
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• pp.1283-1291
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• 2005

One of the problems in boosting Java performance using a Just-in-Time (JIT) compiler is removing redundant array bound checks. In conventional static compilers, many powerful algorithms have been developed, yet they are not directly applicable to JIT compilation where the compilation time is part of the whole running time. In the current JIT compilers, we tan use either a naive algorithm that is not powerful enough or an aggressive algorithm which requires the transformation into a static single assignment (SSA) form of programs (and back to the original form after optimization), thus causing too much overhead not appropriate for JIT compilation This paper proposes a new algorithm based on an inequality graph which can eliminate array bounds check codes aggressively without resorting to the SSA form. When we actually perform this type of optimization, there are many constraints in code motion caused by the precise exception rule in Java specification, which would cause the algorithm to miss many opportunities for eliminating away bound checks. We also propose a new method to overcome these constraints.

• Journal of KIISE:Software and Applications
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• v.31 no.10
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• pp.1304-1319
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• 2004

We can significantly reduce the cost o# program testing by automating the process of test data generation. Test data generation usually concerns identifying input values on which a selected path is executed. Although lots of research has been done so far, there still remains a lot of issues to be addressed. One of the issues is the shape problem. The shape problem refers to the problem of figuring out a shape of the input data structure required to cause the traversal of a given path. In this paper, we introduce a new method for the shape problem. The method converts the selected path into static single assignment (SSA) form without pointer dereferences. This allows us to consider each statement in the selected path as a constraint involving equality or inequality. We solve the constraints to get a solution which will be represented in terms of the points-to relations for each input variable. Simple, but illustrative examples are given to explain the proposed method.

• 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.

• 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 Soil and Groundwater Environment
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• v.15 no.3
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• pp.34-43
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• 2010

The fate of hydrophobic organic contaminants (HOCs) in ground water is highly affected by the distribution and property of the carbonaceous materials (CMs) in subsurface sediments. CMs in soils consist of organic matters (e.g., cellulose, fulvic acid, humic acid, humin, etc.) and black carbon such as char, soot, etc. The distribution and property of CMs are governed by source materials and geological evolution (e.g., diagenesis, catagenesis, etc.) of them. In this study, the distribution and property of CMs in subsurface sediments near the Imjin river in the Republic of Korea and HOC sorption property to the subsurface sediments were investigated. The organic carbon contents of sand and clay/silt layers were about 0.35% and 1.37%, respectively. The carbon contents of condensed form of CMs were about 0.13% and 0.45%, respectively. The existence of black carbon was observed using scanning electron microscopes with energy dispersive spectroscopy. The specific surface areas (SSA) of CMs in heavy fraction(HFrCM) measured with N2 were $35-46m^2/g$. However, SSAs of those HFrCM mineral fraction was only $1.6-4.3m^2/g$. The results of thermogravimetric analysis show that the mass loss of HFrCM was significant at $50-200^{\circ}C$ and $350-600^{\circ}C$ due to the degradation of soft form and condensed form of CMs, respectively. The trichloroethylene (TCE) sorption capacities of sand and clay/silt layers were similar to each other, and these values were also similar to oxidzed layer of glacially deposited subsurface sediments of the Chanute Air Force Base (AFB) in Rantoul, Illinois. However, these were 7-8 times lower than TCE sorption capacity of reduced layer of the Chanute AFB sediments. For accurate prediction of the fate of hydrophobic organic contaminants in subsurface sediments, continuous studies on the development of characterization methods for CMs are required.