{"title":"A Fault Localization Method Based on Similarity Weighting with Unlabeled Test Cases","authors":"Xunli Yang, B. Liu, Dong An, Wandong Xie, Wei Wu","doi":"10.1109/QRS-C57518.2022.00061","DOIUrl":"https://doi.org/10.1109/QRS-C57518.2022.00061","url":null,"abstract":"In software fault localization problems, existing fault localization algorithms usually rely heavily on the perfection of test oracle. But in practice, there are a large number of test cases that lack accurate execution results. In order to utilize on unlabeled test cases, many test prediction and use case filter methods have been proposed. However, these methods ignore the similarity between test cases, which has been proven effective in fault localization studies using labeled test cases. Therefore, this paper proposes a fault localization method based on similarity weighting with unlabeled test cases. It uses the similarity of unlabeled test cases filtered by information entropy and labeled failed test cases as weights, and weights the suspicion calculation coefficients to enhance the importance of use cases similar to the failed cases. The experimental results show that similarity weighting effectively improves fault localization efficiency on all three program sets and all three localization algorithms. It can be seen that similarity of use case information also has an important role in the use of unlabeled test cases.","PeriodicalId":183728,"journal":{"name":"2022 IEEE 22nd International Conference on Software Quality, Reliability, and Security Companion (QRS-C)","volume":"65 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":"114225129","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}
{"title":"What Should Abeeha do? an Activity for Phishing Awareness","authors":"R. Fatima, Affan Yasin, Lin Liu, Jianmin Wang","doi":"10.1109/QRS-C57518.2022.00120","DOIUrl":"https://doi.org/10.1109/QRS-C57518.2022.00120","url":null,"abstract":"The increase in Social Engineering (SE) attacks during COVID-19 pandemic has made it imperative to educate people about SE techniques and methods. For the last many years, we have worked on games, which disseminate awareness among the participants about Social Engineering concepts. The aim of this study is to share our newly designed card-based game, which is simple to understand, and can be conducted in classroom environment.","PeriodicalId":183728,"journal":{"name":"2022 IEEE 22nd International Conference on Software Quality, Reliability, and Security Companion (QRS-C)","volume":"32 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":"114239274","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}
{"title":"A Selective Maintenance Strategy on Network-Based System with Constrained Flow","authors":"Wenjin Zhu, Zhifeng Zheng","doi":"10.1109/QRS-C57518.2022.00070","DOIUrl":"https://doi.org/10.1109/QRS-C57518.2022.00070","url":null,"abstract":"The railway network, power system and pipeline system can be modeled as a network with many nodes and arcs with constrained flow. These critical infrastructures are designed to fulfill some continuous missions, such as traffic flow and electricity. However, due to aging and load-stress, the healthy state of the system will degrade and the reliability will decrease gradually. Different from the other systems which can be shut down for maintenance, the network-based system must provide continuous service meanwhile keep its reliability at a certain criterion. Thus, in this paper, a system is modeled by a network with single-origin and single-destination. The arcs degrade gradually and are modeled by a Gamma distribution with load-stress. The minimum flow of the network should be satisfied all the time. A selective maintenance strategy with sliding maintenance window is proposed based on the remaining useful life and the maximum change of network flow of each arcs. The aim of this study is to optimize the maintenance sequence of the arcs and meanwhile keep the continuous constraint of the network flow. Some numerical simulations will be conducted.","PeriodicalId":183728,"journal":{"name":"2022 IEEE 22nd International Conference on Software Quality, Reliability, and Security Companion (QRS-C)","volume":"42 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":"117209388","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}
{"title":"Evaluation of Software Testing Adequacy based on AHP and BPNN","authors":"Wenhong Liu, Jinliang Gao, Qiong Xue, Dong Guo, Wei Zhang","doi":"10.1109/QRS-C57518.2022.00031","DOIUrl":"https://doi.org/10.1109/QRS-C57518.2022.00031","url":null,"abstract":"There are many factors that affect the evaluation of software testing adequacy, and it is easy to be influenced by human factors when using conventional evaluation methods. Analytic hierarchy process (AHP) is a kind of simple and flexible and practical multi-criteria decision-making method, which is especially suitable for those problems that are difficult to be completely quantitatively analyzed. BP neural network (BPNN) is a widely used intelligent algorithm based on biological neural network, which can better simulate experts for evaluation. Therefore, AHP and BPNN can be combined to evaluate software testing adequacy. Firstly, the evaluation index system of software testing adequacy is constructed from two aspects of testing agency and testing project, and then the comprehensive evaluation model of software testing adequacy is given by using AHP and BPNN. Finally, an example is analyzed.","PeriodicalId":183728,"journal":{"name":"2022 IEEE 22nd International Conference on Software Quality, Reliability, and Security Companion (QRS-C)","volume":"106 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":"128936557","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}
{"title":"RUSTY: Effective C to Rust Conversion via Unstructured Control Specialization","authors":"Xiangjun Han, Baojian Hua, Yang Wang, Ziyao Zhang","doi":"10.1109/QRS-C57518.2022.00122","DOIUrl":"https://doi.org/10.1109/QRS-C57518.2022.00122","url":null,"abstract":"Rust is an emerging programming language designed for both performance and security, and thus many research efforts have been conducted recently to migrate legacy code bases in C/C++ to Rust to exploit Rust's safety benefits. Unfortunately, prior studies on C to Rust conversion still have three limitations: 1) complex structure; 2) code explosion; and 3) poor performance. These limitations greatly affect the effectiveness and usefulness of such conversions. This paper presents Rusty, the first system for effective C to Rust code conversion via unstructured control specialization. The key technical insight of Rusty is to implement C-style syntactic sugars on top of Rust, thus eliminating the discrepancies between the two languages. We have implemented a software prototype for Rusty and conducted experiments to evaluate the effectiveness and testify the usefulness of it by applying Rusty to micro-benchmarks, as well as 3 real-world C projects: 1) Vim; 2) cURL; and 3) the silver searcher. And experimental results demonstrated that Rusty is effective in eliminating unstructured controls, reducing the code size by 16% on average with acceptable overhead (less than 61 microseconds per line of C code).","PeriodicalId":183728,"journal":{"name":"2022 IEEE 22nd International Conference on Software Quality, Reliability, and Security Companion (QRS-C)","volume":"1 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":"129197157","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}
{"title":"Modeling Method and Correctness Verification of Power Grid Safety and Stability Control Strategy System","authors":"Hengfei Yang, Bo Shen, G. Xu, Yonghua Chen","doi":"10.1109/QRS-C57518.2022.00091","DOIUrl":"https://doi.org/10.1109/QRS-C57518.2022.00091","url":null,"abstract":"To solve the problems of the high development cost of power grid safety and control system and difficult verification of the correctness of control logic, based on the idea of model-driven architecture, this paper proposes a modeling method for power grid safety and control strategy system. In order to verify the correctness of the control logic, a corresponding verification method is proposed in this paper with the help of the model checking tool SPIN, and the effectiveness of the method is proved by experiments with concrete examples.","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":"127873020","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}
An Wu, Chen Zheng, Zao Hou, Feng Duan, Zhiqiang Cai
{"title":"An Excellence Level Evaluation Model of Intelligent Manufacturing Unit","authors":"An Wu, Chen Zheng, Zao Hou, Feng Duan, Zhiqiang Cai","doi":"10.1109/QRS-C57518.2022.00071","DOIUrl":"https://doi.org/10.1109/QRS-C57518.2022.00071","url":null,"abstract":"The construction of intelligent manufacturing unit is a process of gradual improvement. It is very important to define the current level of the unit. However, it is difficult to use one evaluation system to evaluate all units in an enterprise because of the difference of each unit. This paper took the product manufacturing unit as the research object, according to the production characteristics of products, manufacturing unit is divided into three different Excellence Grades: Meticulous, Lean and Excellent. Combined with the characteristics of the production and test process, the characteristic factors of the manufacturing process of products were extracted from the aspects of “man, machine, material, method, environment and testing”, and the characteristic factors were decomposed and summarized to form an Excellent Process Grade evaluation model. Finally, the A.J.Klee method and Expert evaluation method were used to calculate the weight of factors at all levels and obtain the Excellence Level of manufacturing units.","PeriodicalId":183728,"journal":{"name":"2022 IEEE 22nd International Conference on Software Quality, Reliability, and Security Companion (QRS-C)","volume":"19 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":"128004030","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}
{"title":"Using Fuzzing to Help Abstract Interpretation Based Program Verification","authors":"Renjie Huang, Banghu Yin, Liqian Chen","doi":"10.1109/QRS-C57518.2022.00133","DOIUrl":"https://doi.org/10.1109/QRS-C57518.2022.00133","url":null,"abstract":"Interpretation has been successfully applied to static analysis, by computing over-approximation of the concrete semantics of various program for many years. However, in the context of program verification, abstract interpretation is not apt to generate counter-examples when the property does not hold. Dynamic analysis is known for its ability to generate inputs to find program vulnerabilities. In this paper, we propose an method that uses fuzzing to help abstract interpretation based program verification, especially to help generating inputs that violate the target property. During the verification process, we feed the fuzzer with the necessary precondition of violating the target assertion computed by abstract interpretation, and then run the fuzzer to generate inputs satisfying the necessary precondition but violating the target assertion. The result shows promising ability of our approach in generating counter-example for target property in comparison with other state-of-the-art tools.","PeriodicalId":183728,"journal":{"name":"2022 IEEE 22nd International Conference on Software Quality, Reliability, and Security Companion (QRS-C)","volume":"21 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":"127822761","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}
{"title":"Hierarchical Action Embedding for Effective Autonomous Penetration Testing","authors":"H. Nguyen, T. Uehara","doi":"10.1109/QRS-C57518.2022.00030","DOIUrl":"https://doi.org/10.1109/QRS-C57518.2022.00030","url":null,"abstract":"Penetration testing is an efficient technique in cyber-security. Using reinforcement learning to enhance the automation and accuracy of penetration testing is a promising approach. However, intricate network systems and the lack of a cyber-security knowledge base remain obstacles to this approach. Here, we propose a hierarchical action embedding that represents penetration testing action space. It helps improve the tactic of re-inforcement learning agents in complicated network scenarios by indicating the relation between actions using MITRE ATT&CK knowledge. The results of three testing configurations s how that the hierarchical action embedding improves the effectiveness of reinforcement learning compared to previous algorithms.","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":"114855025","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}
Changtian He, Qing Sun, Ji Wu, Hai-yan Yang, Tao Yue
{"title":"Feature Difference based Misclassified Sample Detection for CNN Models Deployed in Online Environment","authors":"Changtian He, Qing Sun, Ji Wu, Hai-yan Yang, Tao Yue","doi":"10.1109/QRS-C57518.2022.00126","DOIUrl":"https://doi.org/10.1109/QRS-C57518.2022.00126","url":null,"abstract":"In recent years, Convolutional Neural Network (CNN) has achieved a great success in computer vision. However, at present, for an image classification task, there is no CNN model that can perform 100% accurately due to insufficient or excessive feature learning. Once a CNN model deployed to perform tasks online, misclassified samples might lead the system with the CNN model deployed to enter an unsafe state such as collisions. To assess the performance of such online models, we, in this paper, propose Parallel Signal Routing Paths (PSRP) method to identify misclassified samples by extracting execution paths for each sample and comparing inherent feature differences in terms of CNN nodes between misclassified and well-classified samples, for the ultimate aim of addressing the challenge of test data not having ground-truth labels in online environment where the CNN models are deployed, and give availability results for applying PSRP on 3 public datasets and 3 typical CNN models.","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":"130344677","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}