2022 IEEE 22nd International Conference on Software Quality, Reliability and Security (QRS)最新文献_第7页

Semantic Feature Learning based on Double Sequences Structure for Software Defect Number Prediction 基于双序列结构语义特征学习的软件缺陷数预测

2022 IEEE 22nd International Conference on Software Quality, Reliability and Security (QRS) Pub Date : 2022-12-01 DOI: 10.1109/QRS57517.2022.00026

Tao Wang, Chuanqi Tao, Hongjing Guo, Lijin Tang

{"title":"Semantic Feature Learning based on Double Sequences Structure for Software Defect Number Prediction","authors":"Tao Wang, Chuanqi Tao, Hongjing Guo, Lijin Tang","doi":"10.1109/QRS57517.2022.00026","DOIUrl":"https://doi.org/10.1109/QRS57517.2022.00026","url":null,"abstract":"Software defect prediction(SDP), which predicts defective code areas, including files, code blocks, code lines, etc. It can help developers or testers in allocating test resources before the testing phase. Software defect number prediction(SDNP) is an important research direction of SDP. Previous studies mostly used regression-based methods or different neural networks to mine the semantic features contained in AST, but the way to represent code was relatively simple. In this article, we propose a framework for representing the semantic features in terms of sequences of nodes with a double sequence structure, by analyzing the ASTs and the changes in the code blocks between adjacent version. In addition, to combine statistical metric information, we also propose a model that dynamically determines the ratio of semantic features to traditional metric features during model training by using the gated fusion mechanism to perform SDNP. In the experimental part, we select 10 open source Java projects as training and test sets, and conduct a lot of comparative experiments. The experimental results demonstrate the superiority of our proposed method compared to the baseline approach.","PeriodicalId":143812,"journal":{"name":"2022 IEEE 22nd International Conference on Software Quality, Reliability and Security (QRS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128660103","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Automated Grey-Box Testing of Microservice Architectures 微服务架构的自动化灰盒测试

2022 IEEE 22nd International Conference on Software Quality, Reliability and Security (QRS) Pub Date : 2022-12-01 DOI: 10.1109/QRS57517.2022.00070

Luca Giamattei, Antonio Guerriero, R. Pietrantuono, S. Russo

{"title":"Automated Grey-Box Testing of Microservice Architectures","authors":"Luca Giamattei, Antonio Guerriero, R. Pietrantuono, S. Russo","doi":"10.1109/QRS57517.2022.00070","DOIUrl":"https://doi.org/10.1109/QRS57517.2022.00070","url":null,"abstract":"Microservices Architectures (MSA) have found large adoption in companies delivering online services, often in conjunction with agile development practices. Microservices are distributed, independent and polyglot entities – all features favouring black-box testing. However, for real-scale MSA, a pure black-box strategy may not be able to exercise the system to properly cover the interactions involving internal microservices.We propose a grey-box strategy (MACROHIVE) for automated testing and monitoring of (internal) microservices interactions. It uses combinatorial testing to generate valid and invalid tests from microservices specification. Tests execution and monitoring are automated by a service mesh infrastructure. MACROHIVE runs the tests and traces the interactions among microservices, to report about internal coverage and failing behaviour.MACROHIVE is experimented on TrainTicket, an open-source MSA benchmark. It performs comparably to state-of-the-art techniques in terms of edge-level coverage, but exposes internal failures undetected by black-box testing, gives detailed internal coverage information, and requires fewer tests.","PeriodicalId":143812,"journal":{"name":"2022 IEEE 22nd International Conference on Software Quality, Reliability and Security (QRS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125362759","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

A BiLSTM-Attention Model for Detecting Smart Contract Defects More Accurately 一种更准确检测智能合约缺陷的bilstm -注意力模型

2022 IEEE 22nd International Conference on Software Quality, Reliability and Security (QRS) Pub Date : 2022-12-01 DOI: 10.1109/QRS57517.2022.00016

Chen Qian, Tianyuan Hu, Bixin Li

{"title":"A BiLSTM-Attention Model for Detecting Smart Contract Defects More Accurately","authors":"Chen Qian, Tianyuan Hu, Bixin Li","doi":"10.1109/QRS57517.2022.00016","DOIUrl":"https://doi.org/10.1109/QRS57517.2022.00016","url":null,"abstract":"Smart contracts are applications running on the blockchain which control many virtual currencies. Since smart contracts are composed of code, they inevitably have defects. In recent years, many smart contract defects have caused lots of economic losses and harmful impacts. A contract that has defects may have some errors that cause unwanted results. As smart contracts cannot be modified once deployed, it is necessary to ensure that they are free from defects. In this paper, we focus on eleven defects of smart contracts and construct a deep learning-based model to detect these contract defects more accurately. Our model regards the smart contract’s operation codes as a sequential sentence and uses an Attention-based bidirectional long short term memory (BiLSTM-Attention) model to find smart contract defects. We evaluate our model’s and other models’ performance on 45622 real-world smart contracts. The experimental results show that our model can achieve higher accuracy (95.40%) and F1-score (95.38%). In addition, our model is highly efficient and can quickly detect large numbers of contracts.","PeriodicalId":143812,"journal":{"name":"2022 IEEE 22nd International Conference on Software Quality, Reliability and Security (QRS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125930606","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

EDDNet: An Efficient and Accurate Defect Detection Network for the Industrial Edge Environment EDDNet:面向工业边缘环境的高效、准确的缺陷检测网络

2022 IEEE 22nd International Conference on Software Quality, Reliability and Security (QRS) Pub Date : 2022-12-01 DOI: 10.1109/QRS57517.2022.00090

Runbing Qin, Ningjiang Chen, Yihui Huang

{"title":"EDDNet: An Efficient and Accurate Defect Detection Network for the Industrial Edge Environment","authors":"Runbing Qin, Ningjiang Chen, Yihui Huang","doi":"10.1109/QRS57517.2022.00090","DOIUrl":"https://doi.org/10.1109/QRS57517.2022.00090","url":null,"abstract":"Defect detection aims to locate the accurate position of defects in images, which is of great significance to quality inspection in the industrial product manufacturing. Currently, many defect detection methods rely on deep neural networks to extract features. Although the accuracy of these methods is relatively high, it is computationally intensive, making the methods difficult to deploy in resource-limited edge devices. In order to solve these problems, a lightweight defect detection model for the industrial edge environment is proposed, termed the efficient defect detection network (EDDNet). EfficientNet-B0 is used as the feature extraction backbone, extracting feature maps from feature layers of different depths of the network and fusing multilevel features by multilevel feature fusion (MFF). To obtain more information, we redesign the attention mechanism in MBConv blocks, taking the encoding space (ES) attention mechanism as a new module, which solves the problem that the defective image spatial information is ignored. The experimental results on the NEU-DET and DAGM2007 datasets and PCB defect datasets demonstrate the effectiveness of the proposed EDDNet and its possibility for application in industrial edge device.","PeriodicalId":143812,"journal":{"name":"2022 IEEE 22nd International Conference on Software Quality, Reliability and Security (QRS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125967042","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Conceptualizing the Secure Machine Learning Operations (SecMLOps) Paradigm 概念化安全机器学习操作(SecMLOps)范式

2022 IEEE 22nd International Conference on Software Quality, Reliability and Security (QRS) Pub Date : 2022-12-01 DOI: 10.1109/QRS57517.2022.00023

Xinrui Zhang, Jason Jaskolka

引用次数: 2

Can PoW Consensus Protocol Resist the Whale Attack? PoW共识协议能抵抗鲸鱼攻击吗?

2022 IEEE 22nd International Conference on Software Quality, Reliability and Security (QRS) Pub Date : 2022-12-01 DOI: 10.1109/QRS57517.2022.00058

Xueyong Sun, Qihao Bao, Bixin Li

{"title":"Can PoW Consensus Protocol Resist the Whale Attack?","authors":"Xueyong Sun, Qihao Bao, Bixin Li","doi":"10.1109/QRS57517.2022.00058","DOIUrl":"https://doi.org/10.1109/QRS57517.2022.00058","url":null,"abstract":"Proof of Work (PoW) is the most widely used consensus protocol. However, due to the hash rate competition mechanism, longest chain principle, and transaction fee mechanism of the PoW consensus protocol, malicious nodes can launch attacks to obtain more relative revenue than honest mining, which will discourage honest miners from packing transactions into blocks and verifying blocks. As a result, the speed of the nodes reaching consensus in the network is slowed down, or even consensus cannot be reached, which ultimately affects the security of the PoW consensus protocol.In this paper, the Markov Decision Process (MDP) is used to simulate the whale attack launched by malicious nodes, and evaluate the capability of PoW consensus protocol against the whale attack. The experimental results show that the PoW consensus protocol is secure in the Bitcoin network when the transaction fee is set in the range of 0.002-0.3 block rewards and the transaction volume should not exceed 21.09 block rewards. In addition, the PoW consensus protocol will be more secure with the adjustment of parameters such as the number of block confirmations, block generation interval and block size.","PeriodicalId":143812,"journal":{"name":"2022 IEEE 22nd International Conference on Software Quality, Reliability and Security (QRS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126550042","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An Empirical Study on Software Aging of Long-Running Object Detection Algorithms 长时间目标检测算法的软件老化实证研究

2022 IEEE 22nd International Conference on Software Quality, Reliability and Security (QRS) Pub Date : 2022-12-01 DOI: 10.1109/QRS57517.2022.00112

R. Pietrantuono, Domenico Cotroneo, E. Andrade, F. Machida

引用次数: 1

A Functional FMECA Approach for the Assessment of Critical Infrastructure Resilience 关键基础设施弹性评估的功能性FMECA方法

2022 IEEE 22nd International Conference on Software Quality, Reliability and Security (QRS) Pub Date : 2022-12-01 DOI: 10.1109/QRS57517.2022.00073

G. Carvalho, N. Medeiros, H. Madeira, Bruno Cabral

引用次数: 0

An Exploratory Study for GUI Posts on Stack Overflow 基于堆栈溢出的GUI帖子的探索性研究

2022 IEEE 22nd International Conference on Software Quality, Reliability and Security (QRS) Pub Date : 2022-12-01 DOI: 10.1109/QRS57517.2022.00114

Jing Ding, Liming Nie, Y. Liu, Zuohua Ding, J. Xuan

{"title":"An Exploratory Study for GUI Posts on Stack Overflow","authors":"Jing Ding, Liming Nie, Y. Liu, Zuohua Ding, J. Xuan","doi":"10.1109/QRS57517.2022.00114","DOIUrl":"https://doi.org/10.1109/QRS57517.2022.00114","url":null,"abstract":"Graphical User Interface (GUI) has become one of the most effective human-computer communication medium today. The quality of GUI is essential to the success of apps, especially for mobile apps. Developers not only have to understand the interaction of various components, but also follow the principles of design and implementation. It is helpful for developers to understand the challenges via analyzing the questions and answers (Q&A) on GUI development. However, there is no large-scale study on the GUI development posts on Stack Overflow. In this paper, we conduct an exploratory study on 23,741 posts related to GUI development on Stack Overflow. We first extract 20 topics related to GUI development using topic modeling. After manually classifying these GUI topics into 5 categories, we further quantitatively analyze the popularity and difficulty of GUI topics, the correlation between these two aspects, and qualitatively analyze the distribution of question types in posts. Finally, we have some interesting findings. These findings contain that the topic \"tool selection\" is the most popular topic, the topic \"thread\" has the highest percentage of unaccepted answers, and the topic \"client/server\" answer takes the longest time to be accepted. In addition, we discuss about possible inspirations of our research to GUI development stakeholders.","PeriodicalId":143812,"journal":{"name":"2022 IEEE 22nd International Conference on Software Quality, Reliability and Security (QRS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130947221","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

cPV – Simulation and Verification for Membrane Computing cPV -膜计算的仿真与验证

2022 IEEE 22nd International Conference on Software Quality, Reliability and Security (QRS) Pub Date : 2022-12-01 DOI: 10.1109/QRS57517.2022.00067

Yezhou Liu, Jing Sun, R. Nicolescu, Hai H. Wang

引用次数: 0