[논문]Self-adaptive testing to determine sample size for flash memory solutions

Byun, Chul-Hoon; Jeon, Chang-Kyun; Lee, Taek; In, Hoh Peter

doi:10.3837/tiis.2014.06.019

[국내논문] Self-adaptive testing to determine sample size for flash memory solutions 원문보기

KSII Transactions on internet and information systems : TIIS, v.8 no.6, 2014년, pp.2139 - 2151

Byun, Chul-Hoon (Department of Computer Science & Engineering, Korea University) , Jeon, Chang-Kyun (Department of Computer Science & Engineering, Korea University) , Lee, Taek (Department of Computer Science & Engineering, Korea University) , In, Hoh Peter (Department of Computer Science & Engineering, Korea University)

Abstract ▼ AI-Helper

Embedded system testing, especially long-term reliability testing, of flash memory solutions such as embedded multi-media card, secure digital card and solid-state drive involves strategic decision making related to test sample size to achieve high test coverage. The test sample size is the number of flash memory devices used in a test. Earlier, there were physical limitations on the testing period and the number of test devices that could be used. Hence, decisions regarding the sample size depended on the experience of human testers owing to the absence of well-defined standards. Moreover, a lack of understanding of the importance of the sample size resulted in field defects due to unexpected user scenarios. In worst cases, users finally detected these defects after several years. In this paper, we propose that a large number of potential field defects can be detected if an adequately large test sample size is used to target weak features during long-term reliability testing of flash memory solutions. In general, a larger test sample size yields better results. However, owing to the limited availability of physical resources, there is a limit on the test sample size that can be used. In this paper, we address this problem by proposing a self-adaptive reliability testing scheme to decide the sample size for effective long-term reliability testing.

Keyword

참고문헌 (13)

R. Kavitha, V. R. Kavitha and N. S. Kumar, "Requirement based test case prioritization," in Proc. of Communication Control and Computing Technologies (ICCCCT), pp. 826-829, Oct. 2010.
X. Zhang, C. Nie, B. Xu and B. Qu, "Test Case Prioritization Based on Varying Testing Requirement Priorities and Test Case Costs," in Proc. of Quality Software (QSIC), pp. 15-24, Oct. 2007.
D-Dmfrsqnm, P. Runeson and A. Ljung, "Improving Regression Testing Transparency and Efficiency with History-Based Prioritization - An Industrial Case Study," in Proc. of Software Testing, Verification and Validation (ICST), pp. 367-376, Mar. 2011.
M. Staats, P. Loyola and G. Rothermel, "Oracle-Centric Test Case Prioritization," in Proc. of Software Reliability Engineering (ISSRE), pp. 311-320, Nov. 2012.
B. Jiang, Z. Zhang, W. K. Chan and T. H. Tse, "Adaptive Random Test Case Prioritization," in Proc. of Automated Software Engineering (ASE), pp. 233-244, Nov. 2009.
Z. Q. Zhou, "Using Coverage Information to Guide Test Case Selection in Adaptive Random Testing," in Proc. of Computer Software and Applications Conference Workshops (COMPSACW), pp. 208-213, July 2010.
M. J. Arafeen and H. Do, "Adaptive Regression Testing Strategy: An Empirical Study," in Proc. of Software Reliability Engineering (ISSRE), pp. 130-139, 2011.
M. Fredericks, J. Ramirez and H. C. Cheng, "Towards run-time testing of dynamic adaptive systems," in Proc. of Software Engineering for Adaptive and Self-Managing Systems (SEAMS), pp. 169-174, May 2013.
J. Ramirez, C. Jensen and H. C. Cheng, "A taxonomy of uncertainty for dynamically adaptive systems," in Proc. of Software Engineering for Adaptive and Self-Managing Systems (SEAMS), pp. 99-108, June 2012.
P. Vromant, D. Weyns, S. Malek and J. Andersson, "On interacting control loops in self-adaptive systems," in Proc. of Software Engineering for Adaptive and Self-Managing Systems (SEAMS), pp. 202-207, 2011.
B. Sander and D. Eleco, "A self-adaptive deployment framework for service-oriented systems," in Proc. of Software Engineering for Adaptive and Self-Managing Systems (SEAMS), pp. 208-217, 2011.
N. Kaushik, M. Salehie, L. Tahvildari, L. Sen and M. Moore, "Dynamic Prioritization in Regression Testing," in Proc. of Software Testing, Verification and Validation Workshops (ICSTW), pp. 135-138, Mar. 2011.
M. Salehie and L. Tahvildari, "Self-adaptive software: Landscape and Research challenges," in Proc. of ACM Transactions on Autonomous and Adaptive Systems (TAAS), Vol. 4, No. 2, May 2009.

저자의 다른 논문 :

LOADING...

활용도 분석정보

상세보기

다운로드

내보내기

활용도 Top5 논문

해당 논문의 주제분야에서 활용도가 높은 상위 5개 콘텐츠를 보여줍니다.
더보기 버튼을 클릭하시면 더 많은 관련자료를 살펴볼 수 있습니다.

내보내기 구분	파일저장 인쇄 메일전송
구성항목	기본정보 상세정보 관리번호, 논문명, 저널/프로시딩명, 저자 , 발행년, 권, 호, 시작페이지, 끝페이지, 발행기관 관리번호, 논문명, 대등논문명, 저자 , 저널/프로시딩명, 발행기관, 발행년, 발행언어, 권, 호, 시작페이지, 끝페이지, ISBN, ISSN, 주제분야, 키워드, 초록(한글), 초록(영문), 저자(소속기관)
저장형식	Text(ASCII format) Excel format RefWorks Direct Export RIS format (for Reference Manager, ProCite, EndNote), Scholar's Aids, Mendeley
메일정보	받는사람 (필수) @ 보내는사람 (선택) @ 제목 내용 KISTI 검색결과 이메일 서비스
안내	총 건의 자료가 검색되었습니다. 다운받으실 자료의 인덱스를 입력하세요. (1-10,000) 검색결과의 순서대로 최대 10,000건 까지 다운로드가 가능합니다. 데이타가 많을 경우 속도가 느려질 수 있습니다.(최대 2~3분 소요) 다운로드 파일은 UTF-8 형태로 저장됩니다. 파일의 내용이 제대로 보이지 않을실 때는 웹브라우저 상단의 보기 -> 인코딩 -> 자동선택 여부를 확인하십시오. ~ Text(ASCII format) Excel format

연합인증

[국내논문] Self-adaptive testing to determine sample size for flash memory solutions 원문보기

Abstract ▼ AI-Helper

Keyword

참고문헌 (13)

이 논문을 인용한 문헌

저자의 다른 논문 :

연구과제 타임라인

활용도 분석정보

활용도 Top5 논문

관련 콘텐츠

원문 보기

원문 URL 링크

오픈액세스(OA) 유형

이 논문과 함께 이용한 콘텐츠

AI-Helper ※ AI-Helper는 오픈소스 모델을 사용합니다.

선택된 텍스트

연합인증

[국내논문] Self-adaptive testing to determine sample size for flash memory solutions 원문보기

Abstract ▼ AI-Helper

Keyword

참고문헌 (13)

이 논문을 인용한 문헌

저자의 다른 논문 :

Jeon, Chang-Kyun (1) 이택 (3) 인호 (21)

연구과제 타임라인

전체(0) 논문(0) 특허(0) 보고서(0)

전체(0) 논문(0) 특허(0) 보고서(0)

활용도 분석정보

활용도 Top5 논문 더보기

관련 콘텐츠

원문 보기

원문 URL 링크

오픈액세스(OA) 유형

이 논문과 함께 이용한 콘텐츠

AI-Helper ※ AI-Helper는 오픈소스 모델을 사용합니다.

선택된 텍스트

활용도 Top5 논문