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박중양,서동우,김영순,Park, Joong-Yang,Seo, Dong-Woo,Kim, Young-Soon 한국정보처리학회 2000 정보처리논문지 Vol.7 No.11
소프트웨어를 테스팅하는 동안 얻어지는 고장 데이터를 분석하여 소프트웨어의 신뢰성이 성장하는 과정을 평가하기 위해 여러 가지 소프트웨어 신뢰성 성장 모델들이 개발되었다. 그러나 이들 신뢰성 성장 모델들은 소프트웨어 개발과 사용환경에 관한 여러 가지 가정에 기반하고 있기 때문에, 이 가정이 적합하지 않은 상황이나 결함이 드물게 발생되는 소프트웨어에 대해서는 적절하지 않다. 입력영역에 기초한 소프트웨어 신뢰성 모델은 일반적으로 이러한 가정을 요구하지 않는데 디버깅 전의 소프트웨어와 디버깅 후의 소프트웨어를 별개의 것으로 다루어 많은 테스트 입력을 요하는 단점이 있다. 본 논문에서는 이러한 가정이 요구되지 않고 디버깅 전과 후의 소프트웨어를 동시에 테스트하는 방법에 기반을 둔 입력 영역 기반 소프트웨어 성장모델을 제안하고 그 통계적 특성을 조사한다. 이 모델은 모든 데이터를 다 활용하기 때문에 기존 입력영역 소프트웨어 신뢰성 모델에 비해 적은 테스트 입력을 필요로 할 것으로 기대된다. 그리고 소프트웨어의 유지보수 단계에 적용하기 위해 개발된 유사한 방법들과 비교한다.
시스템 크기와 복잡도를 고려한 누적 노력 기반의 소프트웨어 성장 모델
박중양(Park Joong Yang),김성희(Kim Seong Hee),박재흥(Park Jae Heung) 한국정보처리학회 1999 정보처리학회논문지 Vol.6 No.1
A software growth model, a mathematical model describing the growth behavior of a software system during the evolution process, enables us to predict the future system size and incremental effort required to meet the planned system size. This paper first introduces a software growth model defined with respect to the cumulative incremental effor. It was assumed that the incremental growth of a software system is proportional to the incremental effort and inversely proportional to the system complexity. A key factor is the functional form of the system complexity. A power function of the system size is suggested as a system complexity and then applied to a real data for its validation. Such a system complexity additionally provides us with a measure for complexity comparison. Since the measure is independent of the system size, it si useful for comparing complexities of software systems of different size.
초기하분포 소프트웨어 신뢰성 성장 모델에서의 무수 추정과 예측 방법
박중양(Park Joong Yang),유창열(Yoo Chang Yeul),이부권(Lee Bu Kwon) 한국정보처리학회 1998 정보처리학회논문지 Vol.5 No.9
The hyper-geometric distribution software reliability growth model was recently developed and successfully applied. Due to mathematical difficulty of the maximum likelihood method, the least squares method has been suggested for parameter estimation by the previous studies. We first summarize and compare the minimization criteria adopted by the previous studies. It is then shown that the weighted least squares method is more appropriate because of the nonhomogeneous variability of the number of newly detected faults. The adequacy of the weighted least squares method is illustrated by two numerical examples. Finally, we propose a new method for predicting the number of faults newly discovered by next test instances. The new prediction method can be used for determining the time to stop testing.
초기하분포 소프트웨어 신뢰성 성장 모델 ; 일반화 , 추정과 예측
박중양(Park Joong Yang),유창열(Yoo Chang Yeul),박재흥(Park Jae Heung) 한국정보처리학회 1999 정보처리학회논문지 Vol.6 No.9
The hyper-geometric distribution software reliability growth model (HGDM) was recently developed and successfully applied to real data sets. The HGDM considers the sensitivity factor as a parameter to be estimated. In order to reflect the random behavior of the test-and-debug process, this paper generalizes the HGDM by assuming that the sensitivity factor is a binomial random variable. Such a generalization enables us to easily understand the statistical characteristics of the HGDM. It is shown that the least squares method produces the identical results for both the HGDM and the generalized HGDM. Methods for computing the maximum likelihood estimates and predicting the future outcomes are also presented.
박중양(Joong Yang Park),서동우(Dong Woo Seo),김영순(Young Soon Kim) 한국정보처리학회 2000 정보처리학회논문지 Vol.7 No.11
A number of software reliability growth models (SRGMs) have been developed for evaluating software reliability growth behavior by analyzing the failure data obtained during testing software systems. However, since these SRGMs are based on several assumptions about software development and usage environments, SRGMs are inadequate for circumstances in which such assumptions do not hold or software systems rarely fail. The existing input domain-based reliability models, which do not require assumptions on software development and usage environment, deal the software system before debugging and the software system after debugging independently. Therefore many test inputs are usually demanded. This paper thus suggests an input domain-based SRGM, which does not require such assumptions and is based on the testing procedure that tests concurrently both the software system before debugging and the software system after debugging. The suggested model uses all the available data, the required number of test inputs can be possibly reduced. This reduction may compensate for the excessive testing time caused by executing the software systems before and after debugging. Its statistical characteristics are investigated and it is compared with similar approaches developed for the software maintenance phase.
박중양(Joong Yang Park),김성희(Seong Hee Kim),박재흥(Jae Heong Park) 한국정보처리학회 1999 정보처리학회논문지 Vol.6 No.12
The hyger-geometric distribution software reliability growth medel(HGDM) was recently developed and successfully applied to the problem of estimating the number of initial faults residual in a software at the beginning of the test-and-debug phase. Though the HGDM is a time-domain software reliability growth model(SRGM), it is not possible to compare the HGDM with other time-domain SRGMs. Furthermore the usual software reliability can not be computed. These drawbacks are derived from fact that the HGDM is not described in terms of the execution time. Thus we develop a continuous-time HGDM with binomial sensitivity factor in order to remove these drawbacks. Statistical characteristics of the suggested model are studied and its applicability is then examined by analyzing real test data sets. It is empirically shown that the continuous-time HGDM with binomail sensitivity factor can be used as an alternative to the current HGDM.
불완전 디버깅 환경에서의 신뢰성 보증 소프트웨어 양도 정책
박중양(Park Joong Yang),김영순(Kim Young Soon) 한국정보처리학회 1998 정보처리학회논문지 Vol.5 No.5
An important issue for software developers is to determine when to stop testing the software system and release it to users. Generally the release time is specified by the number of detected faults or the testing time needed to meet the reliability requirement. Software reliability directly depends on the number of remaining or corrected faults. All the detected faults are not always corrected under imperfect debugging environment. We therefore need a new approach to software release policy for imperfect debugging. This paper suggests a software release policy, which guarantees that the reliability requirement has been achieved. The suggested policy is then implemented and illustrated for specific SRGMs.
박중양(Joong Yang Park),이상운(Sang Un Lee),박재흥(Jae Heung Park) 한국정보처리학회 2000 정보처리학회논문지 Vol.7 No.7
Almost all existing software reliability models are based on the assumptions of the software usage and software failure process. There, therefore, is no universally applicable software reliability model. To develop a universal software reliability model, this paper suggests the predictive filter as a general software reliability prediction model for time domain failure data. Its usefulness is empirically verified by analyzing the failure data sets obtained from 14 different software projects. Based on the average relative prediction error, the suggested predictive filter is compared with other well-known neural network models and statistical software reliability growth models. Experimental results show that the predictive filter generally results in a simple model and adapts well across different software projects.