2022 IEEE 22nd International Conference on Software Quality, Reliability, and Security Companion (QRS-C)最新文献_第8页

Software Defect Prediction via GIN with Hybrid Graphical Features 基于混合图形特征的GIN软件缺陷预测

2022 IEEE 22nd International Conference on Software Quality, Reliability, and Security Companion (QRS-C) Pub Date : 2022-12-01 DOI: 10.1109/QRS-C57518.2022.00066

Xuanye Wang, Lu Lu, Boye Wang, Yudong Shang, Hao Yang

{"title":"Software Defect Prediction via GIN with Hybrid Graphical Features","authors":"Xuanye Wang, Lu Lu, Boye Wang, Yudong Shang, Hao Yang","doi":"10.1109/QRS-C57518.2022.00066","DOIUrl":"https://doi.org/10.1109/QRS-C57518.2022.00066","url":null,"abstract":"Software defect prediction (SDP) is one of the determining factors in software development cycle, enabling developers to estimate the quality of delivery and thus improve the user experience. Generally, efforts have opted for building the abstract syntax tree (AST). However, AST is limited in its capacity of providing adequate semantic and structural information. This paper proposes a framework, which trains hybrid features combined from AST and control flow graph (CFG) via Graph Isomorphism Network (GIN) (H-GIN): The framework parses the CFG of the source code and converts redundant blocks to a concise representation by extracting AST. In addition, the contextual relationships between each block in the CFG is carefully preserved, after which the graphical representation of the code is obtained and then fed into the GIN to conduct a defect prediction. The experiments were performed on a large python dataset called PyTraceBus with Precision, Recall, and F1-score as evaluation criteria. Our approach outperforms the previous state-of-the-art methods, which clearly demonstrates the effectiveness of the proposed method.","PeriodicalId":183728,"journal":{"name":"2022 IEEE 22nd International Conference on Software Quality, Reliability, and Security Companion (QRS-C)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133691433","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

Software Bug Prediction based on Complex Network Considering Control Flow 考虑控制流的复杂网络软件缺陷预测

2022 IEEE 22nd International Conference on Software Quality, Reliability, and Security Companion (QRS-C) Pub Date : 2022-12-01 DOI: 10.1109/QRS-C57518.2022.00044

Zhanyi Hou, Ling-lin Gong, Minghao Yang, Yizhuo Zhang, Shunkun Yang

引用次数: 0

Exploring the Impact of Grouping Strategies on Cooperative Co-evolutionary Algorithms for Solving the Advertising Budget Allocation Problem 探讨分组策略对解决广告预算分配问题的协同进化算法的影响

2022 IEEE 22nd International Conference on Software Quality, Reliability, and Security Companion (QRS-C) Pub Date : 2022-12-01 DOI: 10.1109/QRS-C57518.2022.00098

Yongfeng Gu, Yuxuan Zhou, Hao Ding, Fan Jia, Shiping Wang

{"title":"Exploring the Impact of Grouping Strategies on Cooperative Co-evolutionary Algorithms for Solving the Advertising Budget Allocation Problem","authors":"Yongfeng Gu, Yuxuan Zhou, Hao Ding, Fan Jia, Shiping Wang","doi":"10.1109/QRS-C57518.2022.00098","DOIUrl":"https://doi.org/10.1109/QRS-C57518.2022.00098","url":null,"abstract":"The large-scale optimization problem (LSOP), which evolves high-dimensional decision variables, exists in many industrial situations. With the increasing number of decision variables, the performance of traditional evolutionary algorithms deteriorates obviously due to the huge search space and sophisticated optimal hyperplane. To solve the LSOP, many improved cooperative co-evolutionary algorithms are proposed, whose main idea is to group the decision variables into sub-components and evolve each component alternately to obtain the global optimal solution. The grouping strategy plays a core role in these algorithms, however, most of the comparative studies are conducted in experimental environments and a rare of them are conducted in real-world applications. In this paper, to explore the performance of different strategies, we compare four popular grouping strategies in a real-world problem, i.e., the Advertising Budget Allocation Problem. Experiments show that the grouping strategies indeed improve the performance of evolutionary algorithms and Differential Grouping performs effectively and efficiently in our experiment.","PeriodicalId":183728,"journal":{"name":"2022 IEEE 22nd International Conference on Software Quality, Reliability, and Security Companion (QRS-C)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124005352","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

On Securing the Communication in IoT Infrastructure using Elliptic Curve Cryptography 利用椭圆曲线加密技术保护物联网基础设施中的通信安全

2022 IEEE 22nd International Conference on Software Quality, Reliability, and Security Companion (QRS-C) Pub Date : 2022-12-01 DOI: 10.1109/QRS-C57518.2022.00121

Hugo Bourreau, Emeric Guichet, Amine Barrak, Benoît Simon, Fehmi Jaafar

{"title":"On Securing the Communication in IoT Infrastructure using Elliptic Curve Cryptography","authors":"Hugo Bourreau, Emeric Guichet, Amine Barrak, Benoît Simon, Fehmi Jaafar","doi":"10.1109/QRS-C57518.2022.00121","DOIUrl":"https://doi.org/10.1109/QRS-C57518.2022.00121","url":null,"abstract":"Internet of Things (IoT) is widely present nowadays, from businesses to connected houses, and more. IoT is considered a part of the Internet of the future and will comprise billions of intelligent communication. These devices transmit data from sensors to entities like servers to perform suitable responses. The problem of securing these data from cyberattacks increases due to the sensitive information it contains. In addition, studies have shown that most of the time data transiting in IoT devices does not apply encrypted communication. Thus, anyone has the ability to listen to or modify the information. Encrypting communications seems mandatory to secure networks and data transiting from sensors to servers. In this paper, we propose an approach to secure the transmission and the storage of data in IoT using Elliptic Curve Cryptography (ECC). The proposed method offers a high level of security at a reasonable computational cost. Indeed, we present an adequate architecture that ensures the use of a state-of-the-art cryptography algorithm to encrypt sensitive data in IoT.","PeriodicalId":183728,"journal":{"name":"2022 IEEE 22nd International Conference on Software Quality, Reliability, and Security Companion (QRS-C)","volume":"320 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120967639","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: 1

Design and Implementation of OOM Module based on Rust 基于Rust的面向对象模块的设计与实现

2022 IEEE 22nd International Conference on Software Quality, Reliability, and Security Companion (QRS-C) Pub Date : 2022-12-01 DOI: 10.1109/QRS-C57518.2022.00129

Linhan Li, Qianying Zhang, Shijun Zhao, Zhiping Shi, Yong Guan

{"title":"Design and Implementation of OOM Module based on Rust","authors":"Linhan Li, Qianying Zhang, Shijun Zhao, Zhiping Shi, Yong Guan","doi":"10.1109/QRS-C57518.2022.00129","DOIUrl":"https://doi.org/10.1109/QRS-C57518.2022.00129","url":null,"abstract":"The Linux kernel plays an important role in various application scenarios such as computers, mobile devices, and vehicles, in which security-sensitive information is stored. Undefined behavior in the C programming language is usually the cause of Linux kernel vulnerabilities, among which memory safety vulnerabilities are the most threatening. At present, the methods based on static/dynamic analysis and runtime software and hardware defense to ensure memory safety have the problems of poor performance, false positives, and poor compatibility. This paper presents the design and implementation of the OOM (out of memory) module based on the safe programming language Rust. We leverage the Rust FFI mechanism to design a foreign interface layer and a safe foreign interface layer to enable the reconstructed OOM module to invoke other Linux functionalities, and then use Rust to reconstruct the OOM module. The safety features of Rust language are used to avoid undefined behaviors, so as to improve the safety of the kernel. Finally, we export the C interface of the module to enable the invocation by the Linux kernel. Tests show that the OOM module performance and memory consumption after reconstruction are comparable to the original module.","PeriodicalId":183728,"journal":{"name":"2022 IEEE 22nd International Conference on Software Quality, Reliability, and Security Companion (QRS-C)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121332660","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: 1

DeepBoundary: A Coverage Testing Method of Deep Learning Software based on Decision Boundary Representation 深度边界:基于决策边界表示的深度学习软件覆盖率测试方法

2022 IEEE 22nd International Conference on Software Quality, Reliability, and Security Companion (QRS-C) Pub Date : 2022-12-01 DOI: 10.1109/QRS-C57518.2022.00032

Yue Liu, Lichao Feng, Xingya Wang, Shiyu Zhang

{"title":"DeepBoundary: A Coverage Testing Method of Deep Learning Software based on Decision Boundary Representation","authors":"Yue Liu, Lichao Feng, Xingya Wang, Shiyu Zhang","doi":"10.1109/QRS-C57518.2022.00032","DOIUrl":"https://doi.org/10.1109/QRS-C57518.2022.00032","url":null,"abstract":"With the increasing application of Deep Learning (DL) Software in safety-critical fields such as autonomous driving, we need adequate testing to ensure software quality. Observing the decision-making behavior of a Deep Neural Network (DNN) is an essential step in DL software testing. Taking Guiding Deep Learning System Testing Using Surprise Adequacy (SADL) as an example, it uses the independent neuron activation values in the DNN to represent the decision-making behavior. However, the behavior of the DNN needs to be jointly determined by the continuous outputs of all neurons. As a result, the coverage value of SADL constant volatility and lack of stability. To mitigate this problem, we propose a coverage testing method based on the decision boundary representation, DeepBoundary, for the decision-making behavior of DL software. Unlike SADL, DeepBoundary generates decision boundary data to represent the decision behavior of the DNN, which makes the testing results more stable. On this basis, we calculate the kernel density between the testing data and the decision boundary data. It measures the position of the testing data in the decision space and the distance from the decision boundary. Finally, as an adequacy indicator, we calculate the decision boundary density coverage (DBC) of the entire testing set. The experiment on the dataset MNIST and two DL software shows that DeepBoundary can generate actual decision boundary data. The average confidence error in the DNNs output layer is only 4.20E-05. Compared with SADL, DeepBoundary has a stronger correlation with the defect detection ratio, which can more accurately represent testing adequacy.","PeriodicalId":183728,"journal":{"name":"2022 IEEE 22nd International Conference on Software Quality, Reliability, and Security Companion (QRS-C)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122640565","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

Visual Sensitivity Controlling Colour Model in Creative Computing 创造性计算中的视觉灵敏度控制色彩模型

2022 IEEE 22nd International Conference on Software Quality, Reliability, and Security Companion (QRS-C) Pub Date : 2022-12-01 DOI: 10.1109/QRS-C57518.2022.00115

Yinwei Liu

引用次数: 0

The Real-Time General Display and Control Platform Designing Method based on Software Product Line 基于软件产品线的实时通用显示与控制平台设计方法

2022 IEEE 22nd International Conference on Software Quality, Reliability, and Security Companion (QRS-C) Pub Date : 2022-12-01 DOI: 10.1109/QRS-C57518.2022.00056

Xiaowei Guo, Ning Cao, Xibing Yang

引用次数: 0

CIL-BSP: Bug Report Severity Prediction based on Class Imbalanced Learning 基于类不平衡学习的Bug报告严重性预测

2022 IEEE 22nd International Conference on Software Quality, Reliability, and Security Companion (QRS-C) Pub Date : 2022-12-01 DOI: 10.1109/QRS-C57518.2022.00051

Yu Su, Xinping Hu, Xiang Chen, Yubin Qu, Qianshuang Meng

{"title":"CIL-BSP: Bug Report Severity Prediction based on Class Imbalanced Learning","authors":"Yu Su, Xinping Hu, Xiang Chen, Yubin Qu, Qianshuang Meng","doi":"10.1109/QRS-C57518.2022.00051","DOIUrl":"https://doi.org/10.1109/QRS-C57518.2022.00051","url":null,"abstract":"The bug reports' severity can be used for developers to prioritize which bugs to be fixed first. However, this process depends on the developers' expertise in assigning the correct bug severity. In our previous study, we propose a novel bug report severity prediction method EKD-BSP, which utilizes the bug summary and the keywords extracted from the bug description. However, a class imbalance exists in our gathered bug report severity prediction datasets. To solve this issue, we design a novel method CIL-BSP by further considering the class imbalanced methods. Moreover, we apply hyperparameter optimization to CIL-BSP and consider different optimization strategies. To verify the effectiveness of CIL-BSP, we select two real-world open-source projects Eclipse and Mozilla as our experimental subjects. Based on our empirical results, we find that performing hyper-parameter optimization can significantly improve the severity prediction performance of CIL-BSP. Moreover, optimization hyperparameters on the classifier can contribute more than the class imbalanced method.","PeriodicalId":183728,"journal":{"name":"2022 IEEE 22nd International Conference on Software Quality, Reliability, and Security Companion (QRS-C)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128095476","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

Social Media Safety Practices and Flagging Sensitive Posts 社交媒体安全实践和标记敏感帖子

2022 IEEE 22nd International Conference on Software Quality, Reliability, and Security Companion (QRS-C) Pub Date : 2022-12-01 DOI: 10.1109/QRS-C57518.2022.00012

Lisa M. DiSalvo, Gabriela Viviana Saenz, W. E. Wong, Dongcheng Li

{"title":"Social Media Safety Practices and Flagging Sensitive Posts","authors":"Lisa M. DiSalvo, Gabriela Viviana Saenz, W. E. Wong, Dongcheng Li","doi":"10.1109/QRS-C57518.2022.00012","DOIUrl":"https://doi.org/10.1109/QRS-C57518.2022.00012","url":null,"abstract":"Today, social media has uniquely become a force for positive change, community building, and sharing ideas. But with millions of people, of all ages, tuned into social media many hazards and mishaps can arise due to inadequate content monitoring. Therefore, our research problem deals with social media safety practices, flagging sensitive posts, and effective content monitoring. In this paper, an examination will be made of the most impactful hazards and mishaps that arise from poor social media content monitoring, incorrect flagging, public safety, and the spread of misinformation. In addition, this paper will discuss the shortcomings of content monitoring tools currently on the market and how they can be improved. Finally, this paper goes over the findings and areas of research related to the University of Texas Dallas 2022 Software Safety REU program. Through the synthesis and culmination of exploring social media safety practices, we have curated an application to manually label social media posts according to a pre-established corpus of violent phrases.","PeriodicalId":183728,"journal":{"name":"2022 IEEE 22nd International Conference on Software Quality, Reliability, and Security Companion (QRS-C)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125700793","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