New NHPP SRM Based on Generalized S-shaped Fault-Detection Rate Function

The non-homogeneous Poisson process (NHPP) software has a crucial role in computer systems. Furthermore, the software is used in various environments. It was developed and tested in a controlled environment, while real-world operating environments may be different. Accordingly, the uncertainty of the operating environment must be considered. Moreover, predicting software failures is commonly an important part of study, not only for software developers, but also for companies and research institutes. Software reliability model can measure and predict the number of software failures, software failure intervals, software reliability, and failure rates. In this paper, we propose a new model with an inflection factor of the fault detection rate function, considering the uncertainty of operating environments and analyzing how the predicted value of the proposed new model is different than the other models. We compare the proposed model with several existing NHPP software reliability models using real software failure datasets based on ten criteria. The results show that the proposed new model has significantly better goodness-of-fit and predictability than the other models.

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Conversion method from fault detection rate to fault test coverage rate

10.1117/12.2619962 ◽

2021 ◽

Author(s):

Yi Deng ◽

Junyou Shi ◽

Zhenyang Lv

Keyword(s):

Fault Detection ◽

Detection Rate ◽

Coverage Rate ◽

Test Coverage ◽

Conversion Method

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Case Study Investigation of the Fault Detection and Error Locating Effects of Architecture-based Software Testing

International Journal of Software Engineering and Knowledge Engineering ◽

10.1142/s0218194020500096 ◽

2020 ◽

Vol 30 (02) ◽

pp. 191-216

Author(s):

Jihyun Lee ◽

Sungwon Kang

Keyword(s):

Fault Detection ◽

Software Testing ◽

Case Studies ◽

Detection Rate ◽

Software System ◽

Contributing Factors ◽

Types Of Faults ◽

Test Architecture

For software testing, it is well known that the architecture of a software system can be utilized to enhance testability, fault detection and error locating. However, how much and what effects architecture-based software testing has on software testing have been rarely studied. Thus, this paper undertakes case study investigation of the effects of architecture-based software testing specifically with respect to fault detection and error locating. Through comparing the outcomes with the conventional testing approaches that are not based on test architectures, we confirm the effectiveness of architecture-based software testing with respect to fault detection and error locating. The case studies show that using test architecture can improve fault detection rate by 44.1%–88.5% and reduce error locating time by 3%–65.2%, compared to the conventional testing that does not rely on test architecture. With regard to error locating, the scope of relevant components or statements was narrowed by leveraging test architecture for approximately 77% of the detected faults. We also show that architecture-based testing could provide a means of defining an exact oracle or oracles with range values. This study shows by way of case studies the extent to which architecture-based software testing can facilitate detecting certain types of faults and locating the errors that cause such faults. In addition, we discuss the contributing factors of architecture-based software testing which enable such enhancement in fault detection and error locating.

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A Novel Markov Model and its Application to BIT System

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.239-240.721 ◽

2012 ◽

Vol 239-240 ◽

pp. 721-725

Author(s):

Wen Rong Zheng ◽

Shu Zong Wang

Keyword(s):

Complex System ◽

Fault Diagnosis ◽

Fault Detection ◽

Markov Model ◽

False Alarm ◽

False Alarm Rate ◽

Detection Rate ◽

Intermittent Fault ◽

System A ◽

Main Factor

Intermittent fault is the main factor for the raise of false alarm during the process of the detection in built-in test (BIT). Two-state Markov model and three-state Markov model for test is built for system fault diagnosis with BIT. According to the application of BIT in some complex system, a comparison of the false alarm rate between two-state Markov model and three-state Markov model is present, which shows we can reduce the false alarm rate (FAR) and improve fault detection rate by using three-state Markov model in BIT.

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GENERAL FRAMEWORK FOR CHANGE POINT PROBLEM IN SOFTWARE RELIABILITY AND RELATED RELEASE TIME PROBLEM

International Journal of Reliability Quality and Safety Engineering ◽

10.1142/s0218539309003587 ◽

2009 ◽

Vol 16 (06) ◽

pp. 567-579 ◽

Cited By ~ 5

Author(s):

P. K. KAPUR ◽

R. B. GARG ◽

ANU. G. AGGARWAL ◽

ABHISHEK TANDON

Keyword(s):

Fault Detection ◽

Change Point ◽

Detection Rate ◽

Goodness Of Fit ◽

Release Time ◽

Point Problem ◽

Modeling Framework ◽

Change Point Problem ◽

Time Problem ◽

Release Time Problem

Reliable software is the need of the hour especially as it is an indispensable part of our new technological world. Many SRGMs have been proposed considering the change point approach in literature. Change point is defined as the point where the fault detection rate changes, it happens due to number of reasons viz, proficiency of the testing team, nature of faults to be detected etc. In this paper we develop a generalized modeling framework incorporating change point discussing the changing nature of fault detection rate and form a related release time problem which minimizes the total cost of the software and maintains a desirable level of reliability. A numerical example is given for the release problem and the proposed models are validated on real software error data to show their goodness of fit and applicability.

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