RETRACTED: Software Reliability Growth Fault Correction Model Based on Machine Learning and Neural Network Algorithm

Li, Liya

doi:10.1016/j.micpro.2020.103538

Cited by 7 publications

(4 citation statements)

References 11 publications

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“…For 51 × 39 × 9 anchors, Figure 5 shows the specific calculation process. Figure 5 displays that if the number of anchors corresponding to each position is k (k = 9), a 3 × 3 sliding window is adopted to convert each position into a unified 256dimensional feature [27] that corresponds to the output of the two parts. The anchor of this position is the regression between the probability of the object and the detection frame [28].…”

Section: Algorithm and Design Of Submersible Camera Model Based On De...mentioning

confidence: 99%

Application of Target Detection Method Based on Convolutional Neural Network in Sustainable Outdoor Education

Yang

Samsudin

Wang³

et al. 2023

Sustainability

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In order to realize the intelligence of underwater robots, this exploration proposes a submersible vision system based on neurorobotics to obtain the target information in underwater camera data. This exploration innovatively proposes a method based on the convolutional neural network (CNN) to mine the target information in underwater camera data. First, the underwater functions of the manned submersible are analyzed and mined to obtain the specific objects and features of the underwater camera information. Next, the dataset of the specific underwater target image is further constructed. The acquisition system of underwater camera information of manned submersibles is designed through the Single Shot-MultiBox Detector algorithm of deep learning. Furthermore, CNN is adopted to classify the underwater target images, which realizes the intelligent detection and classification of underwater targets. Finally, the model’s performance is tested through experiments, and the following conclusions are obtained. The model can recognize underwater organisms’ local, global, and visual features. Different recognition methods have certain advantages in accuracy, speed, and other aspects. The design here integrates deep learning technology and computer vision technology and applies it to the underwater field, realizing the association of the identified biological information with the geographic information and marine information. This is of great significance to realize the multi-information fusion of manned submersibles and the intelligent field of outdoor education. The contribution of this exploration is to provide a reasonable direction for the intelligent development of outdoor diving education.

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Section: Algorithm and Design Of Submersible Camera Model Based On De...mentioning

confidence: 99%

Application of Target Detection Method Based on Convolutional Neural Network in Sustainable Outdoor Education

Yang

Samsudin

Wang³

et al. 2023

Sustainability

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“…Zhu [22] introduced the concept of complex reliability, which considered both hardware and software components, and proposed maintenance policies applicable to such systems. Several recent software reliability studies have employed machine-learning and deep-learning techniques [23][24][25][26].…”

Section: Introductionmentioning

confidence: 99%

Study of a New Software Reliability Growth Model under Uncertain Operating Environments and Dependent Failures

Lee,

Chang,

Pham

2023

Mathematics

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The coronavirus disease (COVID-19) outbreak has prompted various industries to embark on digital transformation efforts, with software playing a critical role. Ensuring the reliability of software is of the utmost importance given its widespread use across multiple industries. For example, software has extensive applications in areas such as transportation, aviation, and military systems, where reliability problems can result in personal injuries and significant financial losses. Numerous studies have focused on software reliability. In particular, the software reliability growth model has served as a prominent tool for measuring software reliability. Previous studies have often assumed that the testing environment is representative of the operating environment and that software failures occur independently. However, the testing and operating environments can differ, and software failures can sometimes occur dependently. In this study, we propose a new model that assumes uncertain operating environments and dependent failures. In other words, the model proposed in this study takes into account a wider range of environments. The numerical examples in this study demonstrate that the goodness of fit of the new model is significantly better than that of the existing SRGM. Additionally, we show the utilization of the sequential probability ratio test (SPRT) based on the new model to assess the reliability of the dataset.

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“…However, the testing efforts spent in the actual testing process, the skill level of testers and various testing tools will affect the fault and reliability of the software in an unpredictable way, resulting in a certain random impact on the detection rate of each fault, which may produce irregular fluctuations. Aim at the influence brought by these uncertain factors, some scholars solve the problem by adding noise term into b(t) [3,4,14,23,26]; Other scholars build a data-driven reliability model [5,13,22] based on the data itself. This kind of model can interpret and analyze the fault data very well, but it can't establish a specific mathematical model analytic formula, which makes it difficult for managers to adjust and analyze the software fault later.…”

Section: Introductionmentioning

confidence: 99%

Open-source Software Reliability Modeling with Stochastic Impulsive Differential Equations

ZHENG¹,

Yang²,

Hu³

et al. 2023

Eksploatacja i Niezawodność – Maintenance and Reliability

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In reality, sudden updates of software, attacks of hackers, influence of the Internet market, etc. can cause a surge in the number of open-source software (OSS) faults (this moment is the time when impulse occurs), which results in impulsive phenomenon. For the existing software reliability models, dynamic process of software fault is considered to be continuous when assessing reliability, but continuity of the process can be disrupted with appearance of random impulses. Thus, to more accurately assess software reliability, we proposed an OSS reliability model with SIDE. In the model, dynamic process of software fault is divided into a continuous and a skipped part, described the continuous part of the process with SDE, and described destruction of the continuity caused by unpredictable random events with random impulses. Finally, the proposed model is verified with two datasets from real OSS project, and the results show that the proposed model is more in line with reality and has better fitting effect than the existing models.

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RETRACTED: Software Reliability Growth Fault Correction Model Based on Machine Learning and Neural Network Algorithm

Cited by 7 publications

References 11 publications

Application of Target Detection Method Based on Convolutional Neural Network in Sustainable Outdoor Education

Application of Target Detection Method Based on Convolutional Neural Network in Sustainable Outdoor Education

Study of a New Software Reliability Growth Model under Uncertain Operating Environments and Dependent Failures

Open-source Software Reliability Modeling with Stochastic Impulsive Differential Equations

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