Earticle

산업용 시스템과 군용 무기체계에서 사용되는 임베디드 시스템들은 높은 신뢰성을 요구하며, 탑재 소프트웨어의 비중이 높아지면서 소프트웨어 품질확보를 위한 테스트의 중요성이 강화되고 있다. 임베디드 소프트웨어에 대한 테스트는 하드웨어와 소프트웨어의 결합력이 매우 높다는 특성 때문에 통합 테스트를 통해 검증되어야 한다. 기존의 통합 테스트에서는 결함이 발생하더라도 디버깅을 위한 정보를 제공해 줄 수 있는 방법이 고려되지 않아 디버깅을 수행하는 데에 많은 시간과 비용이 소모된다는 문제점이 있었다. 본 논문에서는 임베디드 소프트웨어의 통합 테스트단계에서 발생한 결함에 대해 시험 데이터와 소프트웨어 로그를 통합하여 수집하고 연관 규칙을 이용한 마이닝 기반의 분석 방법을 제공함으로써 임베디드 소프트웨어의 디버깅을 보다 원활하게 할 수 있는 방법을 제안한다. 그리고시험을 통해 제안한 방법이 단일 결함에 대해서 디버깅을 위한 정보의 식별이 가능함을 확인하였다.

The embedded systems used in industry systems and military weapon systems require high reliability, and increasing the proportion of the embedded software increases the importance of testing to ensure software quality. Testing for embedded software should be validated through integration testing because of the tight coupling of hardware and software. There was a problem with the existing integration tests that it was not considered a method to provide information for debugging, even if a defect occurred, so it was time consuming and costly to perform debugging. In this paper, we suggest a method to make debugging of embedded software more seamless by integrating test data and software logs for defects occurred in the integrated testing phase of embedded system, and by providing a mining-based analysis method using associative rules. Through the test, it is confirmed that the proposed method can identify information for debugging with respect to single defect.

The software reliability growth model(SRGM) has been developed in order to estimate such reliability measures as remaining fault number, failure rate and reliability for the developing stage software. Almost of them assumed that the faults detected during testing were evetually removed. Namely, they have studied SRGM based on the assumption that the faults detected during testing were perfectly removed. The fault removing efficiency. however, is imperfect and it is widely known as so in general. It is very difficult to remove detected fault perfectly because the fault detecting is not easy and new error may be introduced during debugging and correcting. Therefore, the fault detecting efficiency may influence the SRGM or cost of developing software. It is a very useful measure for the developing software. much helpful for the developer to evaluate the debugging efficiency, and, moreover, help to additional workloads necessary. Therefore, it is very important to evaluate the effect of imperfect dubugging in point of SRGM and cost, and may influence the optimal release time and operational budget. I extent and study the generally used reliability and cost models to the imperfect debugging range in this paper.

Spectrum-based Fault Localization (SBFL) has been proven to be an effective technique to locate faulty statement in program code. SBFL metrics exploit the records of statement execution (spectra) by pass and fail test cases for each statement to rank its likeliness to be faulty. However, in some cases, these spectra contain duplicated and ambiguous information or noise which may deteriorate the performance of SBFL metrics. We propose six noise reduction schemes to eliminate test cases which provide duplicated and ambiguous information and evaluate the resulting performance improvements in SBFL metrics. Based on our findings, we further provide a guide for SBFL practitioners to select the best performing noise reduction scheme for the SBFL metrics that they use.

Spectrum-based Fault Localization (SBFL) is a well-known debugging technique that locates fault in program code by utilizing execution profiles (spectra) of pass and fail test cases. Hence, the performance of SBFL depends on the test cases executed and the test results. In the most extreme scenarios, the debugging process may have to be conducted with only one fail test case, one pass test case or no pass test case. These scenarios might occur due to extremely high or extremely low failure rates or when software testers decide to stop running more test cases due to time and resource constraints. However, limited test case execution profiles may reduce the accuracy of SBFL metrics. In view of this, we evaluate the performance of SBFL metrics in these extreme scenarios to identify the best performing SBFL metric for each of these scenarios. From the experiment results, we have further discovered the convergence in performance for SBFL metrics under these extreme scenarios.

Most software reliability growth models (SRGMs) take software faults detected that may be removed immediately into consideration. In fact, it costs often considerable resources to identify the root causes of faults detected and to remove them. In additional, detection effort and correction effort have the great effect on software debugging process. The detection effort function and correction effort function are defined as resource expenditures spent on software debugging process, respectively. In this paper, we investigate software debugging process using the queue theory. We propose finite server queuing models with resource and change-point under imperfect debugging environment. A real software failure project is demonstrated the effectiveness of proposed models, and numerical results demonstrate that new models can provide better fit and prediction.

Since ubiquitous embedded software is sensitive to the resources and environment of target system, it should be debugged in the same environment as actual target system. However, existing tools to debug embedded software, in which access to internal signal or resources is limited, are uneconomical. In the thesis, economical and practical USB-JTAG Adapter that can use open GDB is suggested. It can remove existing limitations of environment implementation that have many difficulties in implementing an environment for remote debugging. Hence, the thesis provides economical interfacing environment that can debug ubiquitous embedded software inside remote system.

Park, Seo and Kim은 소프트웨어의 시험단계와 유지보수단계에 모두 적용할 수 있는 입력 영역 기반 소프트웨어 신뢰성 성장 모델을 개발하였다. 이들의 모형은 완전디버깅의 가정 하에서 개발되어졌다. 입력 영역 기반 소프트웨어 신뢰성 성장 모델이 현실적이기 위해서는 이러한 가정은 개선되어야 한다. 본 논문에서는 불완전 디버깅 하에서 사용할 수 있는 입력 영역 기반 소프트웨어 신뢰성 성장 모델을 제안하고 그 통계적 특성을 조사한다.

Park, Seo and Kim (12) developed the input domain-based SRGM, which was able to quantitatively assess the reliability of a software system during the testing and operational phases. They assumed perfect debugging during testing and debugging phase. To make this input domain-based SRGM more realistic, this assumption should be relaxed. In this paper we generalize the input domain-based SRGM under imperfect debugging. Then its statistical characteristics are investigated.

The hyper-geometric distribution software reliability growth model (HGDM) usually assumes that all the software faults detected are perfectly removed without introducing new faults. However, since new faults can be introduced during the test-and-debug phase, the perfect debugging assumption should be relaxed. In this context, Hou, Kuo and Chang [7] developed a modified HGDM for imperfect debugging environment, assuming tat the learning factor is constant. In this paper we extend the existing imperfect debugging HGDM for tow respects: introduction of random sensitivity factor and allowance of variable learning factor. Then the statistical characteristics of he suggested model are studied and its applications to two real data sets are demonstrated.

Modules that consist of software are respectively coded in the early development phase and the modules are unified as a software. After unification, the software is repeatedly tested with a given taskset (the set of module tasks that are tested simultaneously) until a required performance level is satisfied. In this paper, we expand the one-module software debugging model of Jang and Lee (2011) to a multi-module debugging model and derive the taskset completion probability and the mean of the completed tasksets under the assumption that the processing times of module tasks given in a taskset are mutually dependent.

This paper proposes a new model by combining an infinite-server queueing model for multi-task processing software system with a perfect debugging model based on Markov process with two types of faults suggested by Lee et al. (2001). We apply this model for module and integration testing in the testing process. Also, we compute several measure, such as the expected number of tasks whose processes can be completed and the task completion probability are investigated under the proposed model.

인터넷에 접속되는 다양한 정보기기 등의 내장형 시스템에서 사용되는 실시간 소프트웨어를 개발하기 위해서는 자원이 풍부한 호스트 컴퓨터에서 동작되는 강력한 개발도구의 지원이 필수적이다. 디버스에이전트는 타겟시스템의 실시간 OS상에서 실행되는 하나의 태스크로서, 디버거로 대표되는 호스트시스템의 각종 도구들과 디버그 프로토콜에 의해 정의된 메시지를 주고 받으며 이 도구들에서 내리는 명령을 타겟 상에서 수행하는 역할을 담당한다. 본 논문에서는 디버그에이전트를 포함하는 실시간 소프트웨어 개발 환경에 대해 살펴보고, 원격디버깅을 지원하는 디버그에이전트의 구조와 기능, 디버그 프로토콜에 대하여 기술한다.