Earticle

현재 위치 Home

ESBASCA: A Novel Software Clustering Approach

첫 페이지 보기
  • 발행기관
    보안공학연구지원센터(IJSEIA) 바로가기
  • 간행물
    International Journal of Software Engineering and Its Applications 바로가기
  • 통권
    Vol.3 No.3 (2009.07)바로가기
  • 페이지
    pp.1-18
  • 저자
    Bilal Khan, Shaleeza Sohail, M. Younus Javed
  • 언어
    영어(ENG)
  • URL
    https://www.earticle.net/Article/A110704

※ 원문제공기관과의 협약기간이 종료되어 열람이 제한될 수 있습니다.

원문정보

초록

영어
Maintenance is one of the key phases of software development life cycle, for long term effective use of any software. It can become very lengthy and costly for large software systems, especially when subsystem boundaries are not clearly defined. System evolution, lack of up to date documentation and high turn over rate of software professionals (leading to non availability of original designers of the software systems) can complicate the system structure many folds by making the subsystem boundaries ambiguous. Automated software module clustering helps software professionals to recover high-level structure of the system by decomposing the system into smaller manageable subsystems, containing interdependent modules. We treat software clustering as an optimization problem and propose a technique to get near optimal decompositions of relatively independent subsystems, containing interdependent modules. We propose the use of self adaptive Evolution Strategies to search a large solution space consisting of modules and their relationships. We compare our proposed approach with a widely used genetic algorithm based approach on a number of test systems. Our proposed approach shows considerable improvement in terms of quality and effectiveness and consistency of the solutions for all tests cases.

목차

Abstract
 1. Introduction
 2. Literature Survey
 3. Evolution Strategies
  3.1. Objective Function
  3.2. Operators
  3.3. The ES Algorithm
 4. ES for Software Clustering
  4.1. Variable Selection
  4.2. Population Representation
  4.3. Fitness Function
 5. Results and Discussion
  5.1. Quality
  5.2. Effectiveness
  5.3. Consistency
 6. Conclusion and Future Work
 References

키워드

ESBASCA Software Clustering ES Algorithm

저자

  • Bilal Khan [ Department of Computer Engineering, College of E & ME, National University of Sciences and Technology (NUST), Pakistan ]
  • Shaleeza Sohail [ Department of Computer Engineering, College of E & ME, National University of Sciences and Technology (NUST), Pakistan ]
  • M. Younus Javed [ Department of Computer Engineering, College of E & ME, National University of Sciences and Technology (NUST), Pakistan ]

참고문헌

자료제공 : 네이버학술정보

간행물 정보

발행기관

  • 발행기관명
    보안공학연구지원센터(IJSEIA) [Science & Engineering Research Support Center, Republic of Korea(IJSEIA)]
  • 설립연도
    2006
  • 분야
    공학>컴퓨터학
  • 소개
    1. 보안공학에 대한 각종 조사 및 연구 2. 보안공학에 대한 응용기술 연구 및 발표 3. 보안공학에 관한 각종 학술 발표회 및 전시회 개최 4. 보안공학 기술의 상호 협조 및 정보교환 5. 보안공학에 관한 표준화 사업 및 규격의 제정 6. 보안공학에 관한 산학연 협동의 증진 7. 국제적 학술 교류 및 기술 협력 8. 보안공학에 관한 논문지 발간 9. 기타 본 회 목적 달성에 필요한 사업

간행물

  • 간행물명
    International Journal of Software Engineering and Its Applications
  • 간기
    월간
  • pISSN
    1738-9984
  • 수록기간
    2008~2016
  • 등재여부
    SCOPUS
  • 십진분류
    KDC 505 DDC 605

이 권호 내 다른 논문 / International Journal of Software Engineering and Its Applications Vol.3 No.3

    피인용수 : 0(자료제공 : 네이버학술정보)

    함께 이용한 논문 이 논문을 다운로드한 분들이 이용한 다른 논문입니다.

      페이지 저장