Pub Date : 2022-03-01DOI: 10.1109/ICECCS54210.2022.00015
Xinyue Li, Wu Chen
Adaptive software can autonomously adjust system parameters, structure, and behavior in response to possible anomalies. Event analysis, which is responsible for data perception and predictive analysis of the entire system, is the foundation of the entire adaptive process. However, as the size of software systems increases dramatically, the systems interact more closely with each other. This makes it difficult to guarantee the system in terms of recognition accuracy. And in a more dynamic and uncertain environment, event analysis has a lag, which is difficult to meet the tasks with high real-time requirements. Most of the existing event analysis methods are based on rule-based reasoning and ontology reasoning methods, which cannot well meet the requirements of event recognition accuracy and timeliness. To solve the above problems, this paper proposes an adaptive software multi-level event analysis method for uncertain environments. First, we use fuzzing to eliminate noise interference and other problems in the data collection process. Second, an event recognition method based on “anomaly detection and hybrid inference” is established to solve the inaccurate event mapping relationship and reduce the system overhead. Finally, an event prediction method based on dynamic multi-fault trees and multi-valued decision diagrams is established to meet the system's real-time requirements. The experimental results show that the proposed method can effectively ensure the effective detection of system anomalies and the accurate identification of abnormal events, and realize the reliable analysis of anomalies under uncertain environments.
{"title":"Multi-layer Event Analytic Method of Adaptive Software Orienting at Uncertain Environments","authors":"Xinyue Li, Wu Chen","doi":"10.1109/ICECCS54210.2022.00015","DOIUrl":"https://doi.org/10.1109/ICECCS54210.2022.00015","url":null,"abstract":"Adaptive software can autonomously adjust system parameters, structure, and behavior in response to possible anomalies. Event analysis, which is responsible for data perception and predictive analysis of the entire system, is the foundation of the entire adaptive process. However, as the size of software systems increases dramatically, the systems interact more closely with each other. This makes it difficult to guarantee the system in terms of recognition accuracy. And in a more dynamic and uncertain environment, event analysis has a lag, which is difficult to meet the tasks with high real-time requirements. Most of the existing event analysis methods are based on rule-based reasoning and ontology reasoning methods, which cannot well meet the requirements of event recognition accuracy and timeliness. To solve the above problems, this paper proposes an adaptive software multi-level event analysis method for uncertain environments. First, we use fuzzing to eliminate noise interference and other problems in the data collection process. Second, an event recognition method based on “anomaly detection and hybrid inference” is established to solve the inaccurate event mapping relationship and reduce the system overhead. Finally, an event prediction method based on dynamic multi-fault trees and multi-valued decision diagrams is established to meet the system's real-time requirements. The experimental results show that the proposed method can effectively ensure the effective detection of system anomalies and the accurate identification of abnormal events, and realize the reliable analysis of anomalies under uncertain environments.","PeriodicalId":344493,"journal":{"name":"2022 26th International Conference on Engineering of Complex Computer Systems (ICECCS)","volume":"82 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128480935","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 : 2022-03-01DOI: 10.1109/ICECCS54210.2022.00027
Yulin Bao, Chenyi Zhang, Xilong Zhuo, Yongliang Wang
Pointer analysis is an important tool for program analysis and program optimization procedures used in modern compilers and bug checkers. This paper introduces parameter-sensitivity, a new methodology that improves pointer analysis for object-oriented programming languages such as Java. In this approach, we construct a method context for a callee method by a list of objects including both the receiver object and the objects that are passed as parameters at a call site. We believe that such a context is able to represent a significant portion of the current abstract state before the method invocation. The algorithm has been implemented in the Soot framework, and it is evaluated on the benchmarks from DaCapo, compared with the standard object-sensitive pointer analysis algorithms. The preliminary result demonstrates that our parameter-sensitive pointer analysis can achieve better precision with less time consumption than the standard k-object-sensitive algorithms.
{"title":"Parameter Sensitive Pointer Analysis for Java","authors":"Yulin Bao, Chenyi Zhang, Xilong Zhuo, Yongliang Wang","doi":"10.1109/ICECCS54210.2022.00027","DOIUrl":"https://doi.org/10.1109/ICECCS54210.2022.00027","url":null,"abstract":"Pointer analysis is an important tool for program analysis and program optimization procedures used in modern compilers and bug checkers. This paper introduces parameter-sensitivity, a new methodology that improves pointer analysis for object-oriented programming languages such as Java. In this approach, we construct a method context for a callee method by a list of objects including both the receiver object and the objects that are passed as parameters at a call site. We believe that such a context is able to represent a significant portion of the current abstract state before the method invocation. The algorithm has been implemented in the Soot framework, and it is evaluated on the benchmarks from DaCapo, compared with the standard object-sensitive pointer analysis algorithms. The preliminary result demonstrates that our parameter-sensitive pointer analysis can achieve better precision with less time consumption than the standard k-object-sensitive algorithms.","PeriodicalId":344493,"journal":{"name":"2022 26th International Conference on Engineering of Complex Computer Systems (ICECCS)","volume":"91 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114800549","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 : 2022-03-01DOI: 10.1109/ICECCS54210.2022.00016
Camille Coti, L. Petrucci, Daniel Alberto Torres González
As exascale platforms are in sight, high-performance computing needs to take failures into account and provide fault-tolerant applications and environments. Checkpoint-restart approaches do not require modifying the application, but are expensive at large scale. Application-based fault tolerance is more specific to the application and is expected to achieve better performance. In this paper, we address fault-tolerant matrix factorization with algorithms that present good performance, both during failure-free executions and when failures happen. A challenge when designing fault-tolerant algorithms is to make sure they are resilient to any failure scenario. Therefore, we design a model for these algorithms and prove they can tolerate failures at any moment, as long as enough processes are still alive.
{"title":"A Formal Model for Fault Tolerant Parallel Matrix Factorization","authors":"Camille Coti, L. Petrucci, Daniel Alberto Torres González","doi":"10.1109/ICECCS54210.2022.00016","DOIUrl":"https://doi.org/10.1109/ICECCS54210.2022.00016","url":null,"abstract":"As exascale platforms are in sight, high-performance computing needs to take failures into account and provide fault-tolerant applications and environments. Checkpoint-restart approaches do not require modifying the application, but are expensive at large scale. Application-based fault tolerance is more specific to the application and is expected to achieve better performance. In this paper, we address fault-tolerant matrix factorization with algorithms that present good performance, both during failure-free executions and when failures happen. A challenge when designing fault-tolerant algorithms is to make sure they are resilient to any failure scenario. Therefore, we design a model for these algorithms and prove they can tolerate failures at any moment, as long as enough processes are still alive.","PeriodicalId":344493,"journal":{"name":"2022 26th International Conference on Engineering of Complex Computer Systems (ICECCS)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134600148","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 : 2022-03-01DOI: 10.1109/iceccs54210.2022.00003
{"title":"[Copyright notice]","authors":"","doi":"10.1109/iceccs54210.2022.00003","DOIUrl":"https://doi.org/10.1109/iceccs54210.2022.00003","url":null,"abstract":"","PeriodicalId":344493,"journal":{"name":"2022 26th International Conference on Engineering of Complex Computer Systems (ICECCS)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126380637","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 : 2022-03-01DOI: 10.1109/iceccs54210.2022.00002
{"title":"Proceedings 2022 26th International Conference on Engineering of Complex Computer Systems [Title page iii]","authors":"","doi":"10.1109/iceccs54210.2022.00002","DOIUrl":"https://doi.org/10.1109/iceccs54210.2022.00002","url":null,"abstract":"","PeriodicalId":344493,"journal":{"name":"2022 26th International Conference on Engineering of Complex Computer Systems (ICECCS)","volume":"583 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115854339","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 : 2022-03-01DOI: 10.1109/iceccs54210.2022.00001
{"title":"Proceedings 2022 26th International Conference on Engineering of Complex Computer Systems [Title page i]","authors":"","doi":"10.1109/iceccs54210.2022.00001","DOIUrl":"https://doi.org/10.1109/iceccs54210.2022.00001","url":null,"abstract":"","PeriodicalId":344493,"journal":{"name":"2022 26th International Conference on Engineering of Complex Computer Systems (ICECCS)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134211888","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 : 2022-03-01DOI: 10.1109/ICECCS54210.2022.00023
Ran Li, Huibiao Zhu, R. Banach
The cyber-physical system (CPS) is a dynamic system that contains both continuous and discrete behaviors. It has a wide range of applications in fields such as health care equipment, intelligent traffic control and environmental monitoring. However, the combination of continuous physical behavior and discrete control behavior may complicate the design of systems further. It is of great necessity to give an explicit formal language and its semantics for CPS. In this paper, we elaborate the modeling language for CPS based on our previous work. This language supports shared variables to model the interaction between the physical and the cyber. Additionally, we give it denotational semantics and algebraic semantics, especially focus on the continuous behavior and its composition with the discrete behavior. Throughout this paper, we also present some examples to illustrate the feasibility of the language and its semantics.
{"title":"Denotational and Algebraic Semantics for Cyber-physical Systems","authors":"Ran Li, Huibiao Zhu, R. Banach","doi":"10.1109/ICECCS54210.2022.00023","DOIUrl":"https://doi.org/10.1109/ICECCS54210.2022.00023","url":null,"abstract":"The cyber-physical system (CPS) is a dynamic system that contains both continuous and discrete behaviors. It has a wide range of applications in fields such as health care equipment, intelligent traffic control and environmental monitoring. However, the combination of continuous physical behavior and discrete control behavior may complicate the design of systems further. It is of great necessity to give an explicit formal language and its semantics for CPS. In this paper, we elaborate the modeling language for CPS based on our previous work. This language supports shared variables to model the interaction between the physical and the cyber. Additionally, we give it denotational semantics and algebraic semantics, especially focus on the continuous behavior and its composition with the discrete behavior. Throughout this paper, we also present some examples to illustrate the feasibility of the language and its semantics.","PeriodicalId":344493,"journal":{"name":"2022 26th International Conference on Engineering of Complex Computer Systems (ICECCS)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131264108","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 : 2022-03-01DOI: 10.1109/ICECCS54210.2022.00010
Paul Perrotin, Nicolas Belloir, Salah Sadou, David Hairion, A. Beugnard
Due to the increasing complexity of modern systems, the level of responsibility dedicated to the human operator has grown, particularly in Socio-Technical Systems (STS) where humans are considered as subsystems. Like every system, the human operator can fail by behaving in undesired ways, and consequently have a negative impact on the system. Thus, to improve the resilience of the overall system, it is necessary to manage the vulnerability of humans. In this paper we present an approach to assess human vulnerabilities in an STS through its architecture. We propose a model that describes the STS, based on human characteristics having a significant impact on human vulnerabilities. We define an assessment metric for each characteristic. We propose an approach allowing not only to assess the vulnerability of a specific human in the system, but also to understand how a vulnerability propagates through the system. We implemented this approach with a dedicated architecture description language, called Hos-ML, allowing the architect to deal with STS vulnerabilities.
{"title":"HoS-ML: Socio-Technical System ADL Dedicated to Human Vulnerability Identification","authors":"Paul Perrotin, Nicolas Belloir, Salah Sadou, David Hairion, A. Beugnard","doi":"10.1109/ICECCS54210.2022.00010","DOIUrl":"https://doi.org/10.1109/ICECCS54210.2022.00010","url":null,"abstract":"Due to the increasing complexity of modern systems, the level of responsibility dedicated to the human operator has grown, particularly in Socio-Technical Systems (STS) where humans are considered as subsystems. Like every system, the human operator can fail by behaving in undesired ways, and consequently have a negative impact on the system. Thus, to improve the resilience of the overall system, it is necessary to manage the vulnerability of humans. In this paper we present an approach to assess human vulnerabilities in an STS through its architecture. We propose a model that describes the STS, based on human characteristics having a significant impact on human vulnerabilities. We define an assessment metric for each characteristic. We propose an approach allowing not only to assess the vulnerability of a specific human in the system, but also to understand how a vulnerability propagates through the system. We implemented this approach with a dedicated architecture description language, called Hos-ML, allowing the architect to deal with STS vulnerabilities.","PeriodicalId":344493,"journal":{"name":"2022 26th International Conference on Engineering of Complex Computer Systems (ICECCS)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125752109","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 : 2022-03-01DOI: 10.1109/ICECCS54210.2022.00021
Sami Evangelista, L. Petrucci, L. Kristensen
The inherent computational complexity of validating and verifying concurrent systems implies a need to be able to exploit parallel and distributed computing architectures. We present a new distributed algorithm for state space exploration of concurrent systems on computing clusters. Our algorithm relies on Remote Direct Memory Access (RDMA) for low-latency transfer of states between computing elements, and on state reconstruction trees for compact representation of states on the computing elements themselves. For the distribution of states between computing elements, we propose a concept of state stealing. We have implemented our proposed algorithm using the OpenSHMEM API for RDMA and experimentally evaluated it on the Grid'500 testbed with a set of benchmark models. The experimental results show that our algorithm scales well with the number of available computing elements, and that our state stealing mechanism generally provides a balanced workload distribution.
{"title":"Distributed Explicit State Space Exploration with State Reconstruction for RDMA Networks","authors":"Sami Evangelista, L. Petrucci, L. Kristensen","doi":"10.1109/ICECCS54210.2022.00021","DOIUrl":"https://doi.org/10.1109/ICECCS54210.2022.00021","url":null,"abstract":"The inherent computational complexity of validating and verifying concurrent systems implies a need to be able to exploit parallel and distributed computing architectures. We present a new distributed algorithm for state space exploration of concurrent systems on computing clusters. Our algorithm relies on Remote Direct Memory Access (RDMA) for low-latency transfer of states between computing elements, and on state reconstruction trees for compact representation of states on the computing elements themselves. For the distribution of states between computing elements, we propose a concept of state stealing. We have implemented our proposed algorithm using the OpenSHMEM API for RDMA and experimentally evaluated it on the Grid'500 testbed with a set of benchmark models. The experimental results show that our algorithm scales well with the number of available computing elements, and that our state stealing mechanism generally provides a balanced workload distribution.","PeriodicalId":344493,"journal":{"name":"2022 26th International Conference on Engineering of Complex Computer Systems (ICECCS)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128768786","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}
To speed up the efficiency of software development, the ability to retrieve codes through natural language is fundamental. At present, the approach of code search based on deep learning has been extensively researched and achieved a lot of results. However, these models are much complex and the training relies on artificially extracted features. Different from other deep learning models, we simulate people's reading habit of expanding content first and then refining content when learning new knowledge and propose the concept of Extension-Compression Learning. The model can effectively express the features of code and natural language through Extension Learning and Compression Learning. We evaluate the effect of the approach on the code search task with a small dataset and a large dataset, and the results show that all indicators are better than those of other approaches that embed code and text into a joint vector space.
{"title":"Extension-Compression Learning: A deep learning code search method that simulates reading habits","authors":"Lian Gu, Zihui Wang, Jiaxin Liu, Yating Zhang, Dong Yang, Wei Dong","doi":"10.1109/ICECCS54210.2022.00032","DOIUrl":"https://doi.org/10.1109/ICECCS54210.2022.00032","url":null,"abstract":"To speed up the efficiency of software development, the ability to retrieve codes through natural language is fundamental. At present, the approach of code search based on deep learning has been extensively researched and achieved a lot of results. However, these models are much complex and the training relies on artificially extracted features. Different from other deep learning models, we simulate people's reading habit of expanding content first and then refining content when learning new knowledge and propose the concept of Extension-Compression Learning. The model can effectively express the features of code and natural language through Extension Learning and Compression Learning. We evaluate the effect of the approach on the code search task with a small dataset and a large dataset, and the results show that all indicators are better than those of other approaches that embed code and text into a joint vector space.","PeriodicalId":344493,"journal":{"name":"2022 26th International Conference on Engineering of Complex Computer Systems (ICECCS)","volume":"326 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115840749","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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