• Journal of KIISE:Software and Applications
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• v.41 no.7
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• pp.518-522
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• 2014

A single state parsing automaton has the characteristics of the decision of actions which do not depend on the history of the parsing paths but on the current state. The single state parsing automaton hence has the advantage of the reduced parsing time and a small memory requirement compared to those of the conventional LR automaton. However, currently, the grammar classes generating single state parsing automata have not been known. This paper deals with the grammar classes generating single state parsing automata; in addition, this paper gives the generating method of single state parsing automata of the grammar classes.

• Journal of KIISE:Software and Applications
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• v.35 no.11
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• pp.701-704
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• 2008

A general automaton allows multiple input transitions, so a special treatment is required when the history of transitions is needed. An LR automaton keeps the past transitions in the stack to use them during parsing. On the other hand, when each state in an automaton contains in itself the past transition history, the trace overhead of past transitions is unnecessary. The paper suggests a single state parsing automaton that does not depend on the past transitions. The applicable grammar class is less than LR grammars, but each state in a new automaton contains the past information, so the tracing of the history is not required compared to LR automaton.

• Journal of KIISE
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• v.43 no.10
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• pp.1079-1084
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• 2016

Single-state parsing automata have a characteristic such that the decision of an action depends only on the current state but not on the parsing history. The memory space and the parsing time of single-state parsing automata are less than the memory space and the parsing time of LR automata. However, the applicable grammar class of single-state parsing automata is less than that of LR automata. This paper provides extended single-state parsing automata, which are applicable to LR grammars. In the prior work, the special state, referred to as the cyclic state was not treated in the construction of single-state parsing automata, and hence, the applicable grammar class was less than LR grammars. The paper solves the problem of cyclic states by processing dynamic information depending on an input string. The proposed method expands the application of grammar class of single-state parsing automata to LR grammars.

• Journal of KIISE
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• v.44 no.3
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• pp.239-245
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• 2017

Probabilistic grammar is used in natural language processing, and the parse result of the grammar has to preserve the probability of the original grammar. As for the representative parsing method, LL parsing and LR parsing, the former preserves the probability information of the original grammar, but the latter does not. A characteristic of a probabilistic parsing automaton has been studied; but, currently, the generating model of probabilistic parsing automata has not been known. The paper provides a model of probabilistic parsing automata based on the single state parsing automata. The generated automaton preserves the probability of the original grammar, so it is not necessary to test whether or not the automaton is probabilistic parsing automaton; defining a probability function for the automaton is not required. Additionally, an efficient automaton can be constructed by choosing an appropriate parameter.

• Proceedings of the Korean Information Science Society Conference
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• 2000.10a
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• pp.442-444
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• 2000

이 논문에서는 산업계의 표준으로 널리 사용되고 있는 객체 지향 시스템의 명세 언어인 UML의 sequence diagram을 이용하여 객체 지향 시스템을 검증하는 방법과 이 방법을 테스팅 오라클을 생성하는데 사용할 수 있는 프레임웍을 제시하였다. 우리는 sequence diagram을 테스팅 결과의 검증에 사용하기 위하여 정형적으로 재정의 하였다. 그리고 시제 논리의 강력한 검증 능력을 사용하기 위해서 Half-Order Dynamic Temporal Logic(HDTL)이라 불리는 새로운 시제 논리를 정의하였고 sequence diagram을 HDTL 논리식으로 변화시키는 의미 함수(semantic function)를 정의하였다. HDTL에서 오토마톤을 생성하기 위해서 Tableau 방법을 변형하여 적용시켰다. 이 결과 생성된 오토마톤은 이상 상태(anomaly), 즉 sequence diagram에 표현되지 않은 사건(evevt)의 발생을 검색하는 오라클로 사용할 수 있다. 테스팅의 결과를 수작업으로 검증하는 것은 매우 어렵고 오류가 발생하기 쉬운 작업이므로 제안한 방법은 유용하게 사용될 수 있다.

• Korean Journal of Ecology and Environment
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• v.37 no.3 s.108
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• pp.297-303
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• 2004

Two dimensional cellular automaton (CA) models were developed to investigate growth of biofilms in aquatic ecosystems. Simple local rules on CA were applied to governing growth of bacterial populations in relation to different nutrient concentrations. Initial bacterial distribution played an important role in determining population size and morphology of biofilm at low concentrations of nutrition. With clumped distribution, population size increased slowly compared with uniform and random distributions, while the porosity tented to be higher with uniform distribution compared with other initial distributions.

• Journal of KIISE
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• v.42 no.1
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• pp.44-53
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• 2015

Control flow information is useful in the analysis and comparison of programs. Virtualization-obfuscation hides control structures of the original program by transforming machine instructions into bytecode. Direct examination of the resulting binary reveals only the structure of the interpreter. Recovery of the original instructions requires knowledge of the virtual machine architecture, which is randomly generated and hidden. In this paper, we propose a method to reconstruct original control flow using only traces generated from the obfuscated binary. We consider traces as strings and find an automaton that represents the strings. State transitions in the automaton correspond to the control transfers in the original program. We have shown the effectiveness of our method with commercial obfuscators.

• Annual Conference on Human and Language Technology
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• 2018.10a
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• pp.225-227
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• 2018

세계화가 진행되는 요즘, 외국어의 한글 표기 수요가 점차 증가하고 있다. 하지만 현대 한글은 11,172자 밖에 표현할 수 없는 반면 훈민정음은 약 399억 음절을 표현할 수 있다. 하지만 기존 컴퓨터 시스템에서의 훈민정음은 훈민정음 창제원리가 반영되어 있지 않아 약 399억 음절을 온전히 표현할 수 없다. 본 연구의 목적으로 약 399억 음절 입력이 가능한 윈도우용 정음 입력기를 구현하기 위해 기존 연구에 이어 정음 조합 자동 장치를 연구하고 구현하여 이식함에 있다.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.23 no.3
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• pp.395-404
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• 2013

A pattern matching algorithm plays an important role in traffic identification and classification based on predefined patterns for intrusion detection and prevention. As attacks become prevalent and complex, current patterns are written using regular expressions, called regexes, which are expressed into the deterministic finite automata(DFA) due to the guaranteed worst-case performance in pattern matching process. Currently, because of the increased complexity of regex patterns and their large number, memory-efficient DFA from states reduction have become the mainstay of pattern matching process. However, most of the previous works have focused on reducing only the number of states on a single automaton, and thus there still exists a state blowup problem under the large number of patterns. To solve the above problem, we propose a new state compression algorithm that merges states on multiple automata. We show that by merging states with the same input character on multiple automata, the proposed algorithm can lead to a significant reduction of the number of states in the original DFA by as much as 40.0% on average.