Pub Date : 2022-12-01DOI: 10.1109/QRS-C57518.2022.00046
Dong An, Shihai Wang, Liandie Zhu, Xunli Yang, Xiaobo Yan
Current research begins to apply unlabelled test cases to fault localization. However, in these methods, the labeled test cases randomly selected as the basis for fault localization cannot cover enough execution information, which will reduce fault localization efficiency. In this paper, a method based on K-Means clustering and similarity is proposed. At the beginning of the test, K-Means clustering is performed on the test case suite and the test cases filtered can cover more execution information. Next, for the test cases with failed execution results, the test cases with similar execution information are filtered to better highlight the fault information in the failed test cases. Experiments on Defects4J datasets show that the proposed method can be combined with other technologies to improve their efficiency, and the proposed method also has good compatibility with traditional software fault localization algorithms. The average improvement reached 13.37% in 8 scenarios.
{"title":"Prefilter: A Fault Localization Method using Unlabelled Test Cases based on K-Means Clustering and Similarity","authors":"Dong An, Shihai Wang, Liandie Zhu, Xunli Yang, Xiaobo Yan","doi":"10.1109/QRS-C57518.2022.00046","DOIUrl":"https://doi.org/10.1109/QRS-C57518.2022.00046","url":null,"abstract":"Current research begins to apply unlabelled test cases to fault localization. However, in these methods, the labeled test cases randomly selected as the basis for fault localization cannot cover enough execution information, which will reduce fault localization efficiency. In this paper, a method based on K-Means clustering and similarity is proposed. At the beginning of the test, K-Means clustering is performed on the test case suite and the test cases filtered can cover more execution information. Next, for the test cases with failed execution results, the test cases with similar execution information are filtered to better highlight the fault information in the failed test cases. Experiments on Defects4J datasets show that the proposed method can be combined with other technologies to improve their efficiency, and the proposed method also has good compatibility with traditional software fault localization algorithms. The average improvement reached 13.37% in 8 scenarios.","PeriodicalId":183728,"journal":{"name":"2022 IEEE 22nd International Conference on Software Quality, Reliability, and Security Companion (QRS-C)","volume":"24 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":"131423373","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}
Pub Date : 2022-12-01DOI: 10.1109/QRS-C57518.2022.00127
Xue Geng, Sheng-rong Zou, Junpeng Yao
In object-oriented software development, UML has become a de facto modeling standard. However, although UML is easy to understand and apply, it has inaccurate semantics, and UML is a semi-formal modeling language, which cannot be formally verified. Event-B is a formal method based on a large number of mathematical predicate logic, which is precise but difficult to understand and apply. Therefore, how to combine the advantages of UML diagram and Event-B method is the focus of the research. The previous transformation methods are based on the transformation from UML scatter diagram to Event-B, which is prone to conflict and inconsistency. Therefore, we propose a systematic transformation method that can realize the corresponding unification of elements in UML and those in Event-B. The general software system is a medium-sized system. We believe that the medium-sized system can be clearly expressed by using use case diagram, class diagram, state diagram and sequence diagram. In this paper, the transformation methods from these four diagrams to Event-B are given respectively. The transformation method of the system is applied to the elevator control system which requires high safety and reliability. The system transformation method from UML to Event-B not only improves the accuracy of UML and is easy for software practitioners to use, but also enhances the comprehensibility of formal methods and is conducive to the promotion and application of formal methods.
{"title":"Systematic Transformation Method from UML to Event-B","authors":"Xue Geng, Sheng-rong Zou, Junpeng Yao","doi":"10.1109/QRS-C57518.2022.00127","DOIUrl":"https://doi.org/10.1109/QRS-C57518.2022.00127","url":null,"abstract":"In object-oriented software development, UML has become a de facto modeling standard. However, although UML is easy to understand and apply, it has inaccurate semantics, and UML is a semi-formal modeling language, which cannot be formally verified. Event-B is a formal method based on a large number of mathematical predicate logic, which is precise but difficult to understand and apply. Therefore, how to combine the advantages of UML diagram and Event-B method is the focus of the research. The previous transformation methods are based on the transformation from UML scatter diagram to Event-B, which is prone to conflict and inconsistency. Therefore, we propose a systematic transformation method that can realize the corresponding unification of elements in UML and those in Event-B. The general software system is a medium-sized system. We believe that the medium-sized system can be clearly expressed by using use case diagram, class diagram, state diagram and sequence diagram. In this paper, the transformation methods from these four diagrams to Event-B are given respectively. The transformation method of the system is applied to the elevator control system which requires high safety and reliability. The system transformation method from UML to Event-B not only improves the accuracy of UML and is easy for software practitioners to use, but also enhances the comprehensibility of formal methods and is conducive to the promotion and application of formal methods.","PeriodicalId":183728,"journal":{"name":"2022 IEEE 22nd International Conference on Software Quality, Reliability, and Security Companion (QRS-C)","volume":"33 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":"115926609","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}
Pub Date : 2022-12-01DOI: 10.1109/QRS-C57518.2022.00028
Eina Hashimoto, Masatsugu Ichino, H. Yoshiura
Information on social media is important for forensics in the real and cyber worlds, because social media platforms are used for various illicit purposes. However, the anonymity of social media accounts hinders their forensic use. Conventional methods of deanonymizing social media accounts are not sufficiently precise, because they only use information from words in social media posts. Another drawback is that those methods require not only information from the anonymous accounts that are the target of deanonymization, but also information from real-name accounts belonging to the same people who own the anonymous accounts. This paper proposes a new deanonymization method that profiles anonymous accounts to infer their users' attributes and matches the inferred attributes with the known attributes of candidates for deanonymization. In this method, the profiling of anonymous accounts uses not only word information but also information from posted sentences and images. Evaluation with data from 78 volunteers demonstrates the proposed method's viability.
{"title":"Breaking Anonymity of Social Media by Profiling from Multimodal Information","authors":"Eina Hashimoto, Masatsugu Ichino, H. Yoshiura","doi":"10.1109/QRS-C57518.2022.00028","DOIUrl":"https://doi.org/10.1109/QRS-C57518.2022.00028","url":null,"abstract":"Information on social media is important for forensics in the real and cyber worlds, because social media platforms are used for various illicit purposes. However, the anonymity of social media accounts hinders their forensic use. Conventional methods of deanonymizing social media accounts are not sufficiently precise, because they only use information from words in social media posts. Another drawback is that those methods require not only information from the anonymous accounts that are the target of deanonymization, but also information from real-name accounts belonging to the same people who own the anonymous accounts. This paper proposes a new deanonymization method that profiles anonymous accounts to infer their users' attributes and matches the inferred attributes with the known attributes of candidates for deanonymization. In this method, the profiling of anonymous accounts uses not only word information but also information from posted sentences and images. Evaluation with data from 78 volunteers demonstrates the proposed method's viability.","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":"123863889","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}
Automated fault localization aims to reduce software maintenance's workload during software development's evolution. Applying different features extracted from bug reports and source files can help locate faults. However, these approaches consider programming languages as natural when measuring similarity features, considering only precise term matching and ignoring deep semantic similarity features. Furthermore, existing bug localization approaches need to utilize the structural information extracted from source files, where program languages have unique structural features compared to natural languages. In this paper, we proposed SemirFL, a model combining both Convolutional Neural Network(CNN) and revised Vector Space Model(rVSM), which is feeded with four metadata features (bug-fixing recency, bug-fixing frequency, collaborative filtering score, and class name similarity). SemirFL has been studied on four open-source projects. The experimental results show that SemirFL can significantly outperform the existing representative techniques in locating faults in the buggy source files.
{"title":"SemirFL: Boosting Fault Localization via Combining Semantic Information and Information Retrieval","authors":"Xiangyu Shi, Xiaolin Ju, Xiang Chen, Guilong Lu, Mengqi Xu","doi":"10.1109/QRS-C57518.2022.00055","DOIUrl":"https://doi.org/10.1109/QRS-C57518.2022.00055","url":null,"abstract":"Automated fault localization aims to reduce software maintenance's workload during software development's evolution. Applying different features extracted from bug reports and source files can help locate faults. However, these approaches consider programming languages as natural when measuring similarity features, considering only precise term matching and ignoring deep semantic similarity features. Furthermore, existing bug localization approaches need to utilize the structural information extracted from source files, where program languages have unique structural features compared to natural languages. In this paper, we proposed SemirFL, a model combining both Convolutional Neural Network(CNN) and revised Vector Space Model(rVSM), which is feeded with four metadata features (bug-fixing recency, bug-fixing frequency, collaborative filtering score, and class name similarity). SemirFL has been studied on four open-source projects. The experimental results show that SemirFL can significantly outperform the existing representative techniques in locating faults in the buggy source files.","PeriodicalId":183728,"journal":{"name":"2022 IEEE 22nd International Conference on Software Quality, Reliability, and Security Companion (QRS-C)","volume":"74 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":"124995828","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}
Pub Date : 2022-12-01DOI: 10.1109/QRS-C57518.2022.00116
Qinyun Liu, William C. Chu, Xiaochun Zhang, Shou-Yu Lee, Wei Mo
Creative products based on cultural heritage are high value-added products relying on wisdom, skills and talents, creating and promoting cultural resources and cultural products. Cultural heritage creative products are the organic integration of content creativity and cultural heritage carrier. At the technical level, the design algorithm has not been widely applied, but it has been studied. The output design algorithm fails to take into account both intelligent design and creative design. Computer cannot make creativity even based on the most robust algorithm. As the computing logic is 0 or 1. Quantum information theory can solve the problem. In this research, we proposed the creativity generation scheme inspired by multi data and information entanglement. Application scene is the culture products design with traditional elements based on world culture heritage, the Forbidden City. In this research, it is proposed the creativity generation scheme inspired by multi data and information entanglement.
{"title":"A Quantum Information and Cybernetics Based Algorithm for Creativity Applying in Cultural Heritage Products Design","authors":"Qinyun Liu, William C. Chu, Xiaochun Zhang, Shou-Yu Lee, Wei Mo","doi":"10.1109/QRS-C57518.2022.00116","DOIUrl":"https://doi.org/10.1109/QRS-C57518.2022.00116","url":null,"abstract":"Creative products based on cultural heritage are high value-added products relying on wisdom, skills and talents, creating and promoting cultural resources and cultural products. Cultural heritage creative products are the organic integration of content creativity and cultural heritage carrier. At the technical level, the design algorithm has not been widely applied, but it has been studied. The output design algorithm fails to take into account both intelligent design and creative design. Computer cannot make creativity even based on the most robust algorithm. As the computing logic is 0 or 1. Quantum information theory can solve the problem. In this research, we proposed the creativity generation scheme inspired by multi data and information entanglement. Application scene is the culture products design with traditional elements based on world culture heritage, the Forbidden City. In this research, it is proposed the creativity generation scheme inspired by multi data and information entanglement.","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":"129997546","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}
Pub Date : 2022-12-01DOI: 10.1109/QRS-C57518.2022.00019
Jingyuan Cai, Ying Zhou, Tianyuan Hu, Bixin Li
With the continuous development and innovation of blockchain technology, a large number of blockchain networks with various features have emerged to satisfy the needs of differ-ent scenarios. For example, Cross-Chain technologies have been proposed to enable information interaction and value transfer between two blockchains. In Cross-Chain asset transaction, the Hashed Timelock Contract (HTLC for short) algorithm is the most widely used to control asset transaction. However, the HTLC algorithm has a problem of low-level security assurance in practical applications: Attackers can associate the accounts of both parties involved in a Cross-Chain transaction by comparing contract parameters on different chains, which leads to the disclosure of identity privacy information of both relevant parties in the Cross-Chain transactions. In order to protect the identity privacy information of Cross-Chain traders, a new privacy protection method for Cross-Chain asset transaction was proposed based on Paillier homomorphic encryption (PTLC for short) in this paper, which uses Paillier homomorphic encryption to replace hash encryption in privacy protection process. It not only maintains a high security of Cross-Chain asset transaction, but also solves the major problem of identity privacy information leakage during whole asset transaction process. Experiments of cross-chain asset transactions are conducted in two different Ethereum private chains, and experimental results show that the proposed method PTLC can protect the identity privacy information effectively and achieve a low GAS consumption value in the Cross-Chain process.
{"title":"PTLC: Protect the Identity Privacy during Cross-Chain Asset Transaction More Effectively","authors":"Jingyuan Cai, Ying Zhou, Tianyuan Hu, Bixin Li","doi":"10.1109/QRS-C57518.2022.00019","DOIUrl":"https://doi.org/10.1109/QRS-C57518.2022.00019","url":null,"abstract":"With the continuous development and innovation of blockchain technology, a large number of blockchain networks with various features have emerged to satisfy the needs of differ-ent scenarios. For example, Cross-Chain technologies have been proposed to enable information interaction and value transfer between two blockchains. In Cross-Chain asset transaction, the Hashed Timelock Contract (HTLC for short) algorithm is the most widely used to control asset transaction. However, the HTLC algorithm has a problem of low-level security assurance in practical applications: Attackers can associate the accounts of both parties involved in a Cross-Chain transaction by comparing contract parameters on different chains, which leads to the disclosure of identity privacy information of both relevant parties in the Cross-Chain transactions. In order to protect the identity privacy information of Cross-Chain traders, a new privacy protection method for Cross-Chain asset transaction was proposed based on Paillier homomorphic encryption (PTLC for short) in this paper, which uses Paillier homomorphic encryption to replace hash encryption in privacy protection process. It not only maintains a high security of Cross-Chain asset transaction, but also solves the major problem of identity privacy information leakage during whole asset transaction process. Experiments of cross-chain asset transactions are conducted in two different Ethereum private chains, and experimental results show that the proposed method PTLC can protect the identity privacy information effectively and achieve a low GAS consumption value in the Cross-Chain process.","PeriodicalId":183728,"journal":{"name":"2022 IEEE 22nd International Conference on Software Quality, Reliability, and Security Companion (QRS-C)","volume":"78 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":"116341183","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}
In the software multi-fault scenario, the failed test cases of different fault sources are classified by clustering, and then the program statements in each cluster are ranked with suspicion by the fault location technology based on program spectrum. Software multi-fault location technology decouples failed test cases by clustering their code coverage information. At present, there are many clustering strategies for software failed test cases. However, due to the characteristics of high dimension, complex structure and variable shape of the execution information of failed test cases, it is difficult for a single clustering algorithm to accurately identify the cluster structure, so that it cannot be decoupled accurately. In this paper, a variety of clustering algorithms and different parameters are selected to obtain multiple cluster members, according to the clustering members to get the similarity matrix, and then hierarchical clustering is used to obtain the final clustering results, to achieve the integration between different clustering algorithms, so that the algorithm can identify the complex cluster structure, and then improve the efficiency of fault location.
{"title":"A Software Multi-Fault Clustering Ensemble Technology","authors":"Mingxing Zhang, Shihai Wang, Wentao Wu, Weiguo Qiu, Wandong Xie","doi":"10.1109/QRS-C57518.2022.00059","DOIUrl":"https://doi.org/10.1109/QRS-C57518.2022.00059","url":null,"abstract":"In the software multi-fault scenario, the failed test cases of different fault sources are classified by clustering, and then the program statements in each cluster are ranked with suspicion by the fault location technology based on program spectrum. Software multi-fault location technology decouples failed test cases by clustering their code coverage information. At present, there are many clustering strategies for software failed test cases. However, due to the characteristics of high dimension, complex structure and variable shape of the execution information of failed test cases, it is difficult for a single clustering algorithm to accurately identify the cluster structure, so that it cannot be decoupled accurately. In this paper, a variety of clustering algorithms and different parameters are selected to obtain multiple cluster members, according to the clustering members to get the similarity matrix, and then hierarchical clustering is used to obtain the final clustering results, to achieve the integration between different clustering algorithms, so that the algorithm can identify the complex cluster structure, and then improve the efficiency of fault location.","PeriodicalId":183728,"journal":{"name":"2022 IEEE 22nd International Conference on Software Quality, Reliability, and Security Companion (QRS-C)","volume":"15 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":"122602065","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}
Pub Date : 2022-12-01DOI: 10.1109/QRS-C57518.2022.00102
Ziyang Weng, Shuhao Wang, W. Yan, Yinger Liang
In this paper, we propose a method to calculate spatial semantic similarity based on sampled same-area time-series images. First, we preprocess the corpus data containing spatial information, then we project the coordinates in the preprocessed corpus data to obtain the actual spatial ranges, then we determine the contextual annotations of geographical feature gestures in the time-series images and perform comparison sampling, and finally we calculate the similarity between the coordinates of the overall same-area time-series image geo-corpus The similarity is evaluated for each two nodes in the set of the overall same-region geo-serial corpus. This paper identifies the causes of data noise and interpretation bias arising from the migration process of geographic data in time-series images, which effectively complements the traditional natural semantic similarity model and improves the effectiveness of intelligent geographic information retrieval and ancient landscape painting verification.
{"title":"Prototype Algorithm: Number Chain Features in Spatial Similarity Calculation of Time-Series Graph Sources","authors":"Ziyang Weng, Shuhao Wang, W. Yan, Yinger Liang","doi":"10.1109/QRS-C57518.2022.00102","DOIUrl":"https://doi.org/10.1109/QRS-C57518.2022.00102","url":null,"abstract":"In this paper, we propose a method to calculate spatial semantic similarity based on sampled same-area time-series images. First, we preprocess the corpus data containing spatial information, then we project the coordinates in the preprocessed corpus data to obtain the actual spatial ranges, then we determine the contextual annotations of geographical feature gestures in the time-series images and perform comparison sampling, and finally we calculate the similarity between the coordinates of the overall same-area time-series image geo-corpus The similarity is evaluated for each two nodes in the set of the overall same-region geo-serial corpus. This paper identifies the causes of data noise and interpretation bias arising from the migration process of geographic data in time-series images, which effectively complements the traditional natural semantic similarity model and improves the effectiveness of intelligent geographic information retrieval and ancient landscape painting verification.","PeriodicalId":183728,"journal":{"name":"2022 IEEE 22nd International Conference on Software Quality, Reliability, and Security Companion (QRS-C)","volume":"192 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":"116142949","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}
Pub Date : 2022-12-01DOI: 10.1109/QRS-C57518.2022.00024
Xiangke Mao, C. Li, Guigang Zhang, Xin Wei, Chunxiao Xing
Data provenance is a basic requirement for trusted data management in the era of big data. Before the emergence of blockchain technology, data provenance mainly used a centralized database to store data records, log records, etc., to facilitate subsequent audit tracking, but database has the security problem of data tampering. After the emergence of blockchain technology, researchers have conducted a lot of research on trusted data provenance in the Internet of Things (IoT), product supply chain, medical health and other fields based on the characteristics of blockchain decentralization, tamper resistance, and traceability, etc., to ensure the security and trustworthiness of data provenance results. This paper will sort out the research on the use of blockchain technology for data provenance in different fields in recent years, and analyze the similarities and differences between existing blockchain based data provenance methods as a whole. Finally, the possible challenges in data provenance based on blockchain technology are pointed out and the possible solutions are given.
{"title":"Application of Blockchain in Trusted Data Provenance","authors":"Xiangke Mao, C. Li, Guigang Zhang, Xin Wei, Chunxiao Xing","doi":"10.1109/QRS-C57518.2022.00024","DOIUrl":"https://doi.org/10.1109/QRS-C57518.2022.00024","url":null,"abstract":"Data provenance is a basic requirement for trusted data management in the era of big data. Before the emergence of blockchain technology, data provenance mainly used a centralized database to store data records, log records, etc., to facilitate subsequent audit tracking, but database has the security problem of data tampering. After the emergence of blockchain technology, researchers have conducted a lot of research on trusted data provenance in the Internet of Things (IoT), product supply chain, medical health and other fields based on the characteristics of blockchain decentralization, tamper resistance, and traceability, etc., to ensure the security and trustworthiness of data provenance results. This paper will sort out the research on the use of blockchain technology for data provenance in different fields in recent years, and analyze the similarities and differences between existing blockchain based data provenance methods as a whole. Finally, the possible challenges in data provenance based on blockchain technology are pointed out and the possible solutions are given.","PeriodicalId":183728,"journal":{"name":"2022 IEEE 22nd International Conference on Software Quality, Reliability, and Security Companion (QRS-C)","volume":"704 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":"116120876","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}
Pub Date : 2022-12-01DOI: 10.1109/QRS-C57518.2022.00045
Zhiyu Duan, Yujia Li, Pubo Ma, Xiaodong Gou, Shunkun Yang
The powerful technique, symbolic execution, has become a promising approach for analyzing deep complex software failure modes recently. However, as the software scale grows rapidly in intelligent automatic control system, these methods unavoidably suffer the curse of path explosion and low global coverage. To solve the problem, an evolutionary strategy guided symbolic execution framework is proposed for triggering hard-to-excite input-relevant faults. A novel alternate asynchronous search strategy is adopted to enhance the breadth-search capability of symbol execution. Furthermore, by combining ANGR, a popular symbolic execution engine, and genetic algorithm, this method synchronously triggers the potentially hidden hybrid fault modes at different levels in the software architecture. Case studies on the SIR test suite demonstrate that the GA-enhanced symbolic execution greatly improves coverage and accelerates test convergence. Among them, the coverage rate has increased by up to 23.7%. With a baseline of 95% line coverage, the proposed method can reduce the number of iterations by at least 43.3%.
{"title":"A Multi-Layer Fault Triggering Framework based on Evolutionary Strategy Guided Symbolic Execution for Automated Test Case Generation","authors":"Zhiyu Duan, Yujia Li, Pubo Ma, Xiaodong Gou, Shunkun Yang","doi":"10.1109/QRS-C57518.2022.00045","DOIUrl":"https://doi.org/10.1109/QRS-C57518.2022.00045","url":null,"abstract":"The powerful technique, symbolic execution, has become a promising approach for analyzing deep complex software failure modes recently. However, as the software scale grows rapidly in intelligent automatic control system, these methods unavoidably suffer the curse of path explosion and low global coverage. To solve the problem, an evolutionary strategy guided symbolic execution framework is proposed for triggering hard-to-excite input-relevant faults. A novel alternate asynchronous search strategy is adopted to enhance the breadth-search capability of symbol execution. Furthermore, by combining ANGR, a popular symbolic execution engine, and genetic algorithm, this method synchronously triggers the potentially hidden hybrid fault modes at different levels in the software architecture. Case studies on the SIR test suite demonstrate that the GA-enhanced symbolic execution greatly improves coverage and accelerates test convergence. Among them, the coverage rate has increased by up to 23.7%. With a baseline of 95% line coverage, the proposed method can reduce the number of iterations by at least 43.3%.","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":"126979023","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}
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