Feature selection methods facilitate removal of irrelevant attributes. Ineffective features may contain outliers that degrade performance of classifiers. We propose an ensemble filter base feature selection technique for multiclass classification. The technique combines results of four selection methods to create an ensemble list. The study uses a red wine dataset drawn from UC Irvine machine learning data repository and WEKA, a collection of machine learning algorithms for data mining tasks. The multiclass red wine dataset is binarized using WekaMulticlassClassifier utilizing the 1against 1 with pairwise coupling decomposing scheme. Using random forest algorithm and root mean square error values, a learning curve is generated that establishes an optimal ensemble sub-list. Outliers are detected using the Tukey statistical method. The proposed ensemble method outperformed the single feature methods. The study concludes by showing that unnecessary features and presence of outliers degrades classifiers performance. We recommend further studies on the effect of gradual selective removal of outliers on classification.
{"title":"An Ensemble Filter Feature Selection Method and Outlier Detection Method for Multiclass Classification","authors":"Dalton Ndirangu, W. Mwangi, L. Nderu","doi":"10.1145/3316615.3318223","DOIUrl":"https://doi.org/10.1145/3316615.3318223","url":null,"abstract":"Feature selection methods facilitate removal of irrelevant attributes. Ineffective features may contain outliers that degrade performance of classifiers. We propose an ensemble filter base feature selection technique for multiclass classification. The technique combines results of four selection methods to create an ensemble list. The study uses a red wine dataset drawn from UC Irvine machine learning data repository and WEKA, a collection of machine learning algorithms for data mining tasks. The multiclass red wine dataset is binarized using WekaMulticlassClassifier utilizing the 1against 1 with pairwise coupling decomposing scheme. Using random forest algorithm and root mean square error values, a learning curve is generated that establishes an optimal ensemble sub-list. Outliers are detected using the Tukey statistical method. The proposed ensemble method outperformed the single feature methods. The study concludes by showing that unnecessary features and presence of outliers degrades classifiers performance. We recommend further studies on the effect of gradual selective removal of outliers on classification.","PeriodicalId":268392,"journal":{"name":"Proceedings of the 2019 8th International Conference on Software and Computer Applications","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123782559","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}
Aspect sentiment analysis is a fine-gained task in sentiment analysis. In this paper, we propose a novel LSTM network model, which combines multi-attention and aspect contexts, i.e. LSTM-MATT-AC. Multi-attention mechanism that integrates the factors of location, content and class could adaptively capture important information in the contexts with the supervision of aspect targets. In other words, the model is more robust against irrelevant information. Simultaneously, aspect context mechanism extends differentiate left and right contexts given aspect targets and strengthens the expressive power of the model for handling more complication by mining deeper semantic information. Experiment results on SemEval2014 Task4 and Twitter datasets show that the accuracy of sentiment classification reaches 80.6%, 75.1% and 71.1% respectively. Compared to previous neural network-based sentiment analysis models, the accuracy has been further improved.
方面情感分析是情感分析中的一项精细任务。本文提出了一种结合多注意和方面上下文的LSTM网络模型，即LSTM- matt - ac。多注意机制融合了地点、内容和类别等因素，能够在方面目标的监督下自适应地捕捉情境中的重要信息。换句话说，模型对不相关信息的鲁棒性更强。同时，方面上下文机制扩展了在给定方面目标的情况下区分左右上下文的能力，并通过挖掘更深层次的语义信息增强了模型的表达能力，以处理更复杂的问题。在SemEval2014 Task4和Twitter数据集上的实验结果表明，情感分类的准确率分别达到80.6%、75.1%和71.1%。与以往基于神经网络的情感分析模型相比，精度得到了进一步提高。
{"title":"Multi-Attention Network for Aspect Sentiment Analysis","authors":"Huiyu Han, Xiaoge Li, Shuting Zhi, Haoyue Wang","doi":"10.1145/3316615.3316673","DOIUrl":"https://doi.org/10.1145/3316615.3316673","url":null,"abstract":"Aspect sentiment analysis is a fine-gained task in sentiment analysis. In this paper, we propose a novel LSTM network model, which combines multi-attention and aspect contexts, i.e. LSTM-MATT-AC. Multi-attention mechanism that integrates the factors of location, content and class could adaptively capture important information in the contexts with the supervision of aspect targets. In other words, the model is more robust against irrelevant information. Simultaneously, aspect context mechanism extends differentiate left and right contexts given aspect targets and strengthens the expressive power of the model for handling more complication by mining deeper semantic information. Experiment results on SemEval2014 Task4 and Twitter datasets show that the accuracy of sentiment classification reaches 80.6%, 75.1% and 71.1% respectively. Compared to previous neural network-based sentiment analysis models, the accuracy has been further improved.","PeriodicalId":268392,"journal":{"name":"Proceedings of the 2019 8th International Conference on Software and Computer Applications","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122657789","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}
Realizability checking is used to detect flaws in reactive system specifications that are difficult for humans to find. However, these checks are computationally costly. To address this problem, researchers have studied efficient methods for implementing such checking procedures. In this paper, we propose a new implementation method of realizability checking. While symbolic approaches have been adopted in many previous methods, we take a partially symbolic approach, in which binary decision diagrams (BDDs) are used partially. We developed a prototype realizability checker based on our method, and experimentally compared it to tools based on other implementation methods. Our prototype was efficient in comparison to the other tools.
{"title":"Towards Efficient Implementation of Realizability Checking for Reactive System Specifications","authors":"Masaya Shimakawa, Atsushi Ueno, Shohei Mochizuki, Takashi Tomita, Shigeki Hagihara, N. Yonezaki","doi":"10.1145/3316615.3316634","DOIUrl":"https://doi.org/10.1145/3316615.3316634","url":null,"abstract":"Realizability checking is used to detect flaws in reactive system specifications that are difficult for humans to find. However, these checks are computationally costly. To address this problem, researchers have studied efficient methods for implementing such checking procedures. In this paper, we propose a new implementation method of realizability checking. While symbolic approaches have been adopted in many previous methods, we take a partially symbolic approach, in which binary decision diagrams (BDDs) are used partially. We developed a prototype realizability checker based on our method, and experimentally compared it to tools based on other implementation methods. Our prototype was efficient in comparison to the other tools.","PeriodicalId":268392,"journal":{"name":"Proceedings of the 2019 8th International Conference on Software and Computer Applications","volume":"150 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122761587","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}
Delivery route optimization for logistic industry is one of applications proposed on smart meter infrastructure. It's expected to drastically reduce absent-delivery which amounts to 20% of total delivery in Japan, which estimated to save $billions a year. But as previous works pointed out, the concern on user privacy is the biggest hurdle yet to be addressed. In this research, we proposed a new approach to improve user privacy by converting electricity data into route data and optimize it before providing to service provider. Then, we tested pragmatic privacy improvement and route optimization through actual delivery experiment. Results showed that the information leakage rate (# of absence detection per delivery) decreased from 23% to 4% by this system and decreased to 2% with additional operational change. Also, the experiment validated decrease of absent-delivery rate from 23% to 2% and travel distance by 5% while improving privacy. Applying adequate method to "delivery optimization through occupancy prediction" enabled achieving both user privacy and absent-delivery reduction significantly.
{"title":"Privacy Enhancement for Delivery Route Optimization through Occupancy Prediction","authors":"Shimpei Ohsugi, Kenji Tanaka, N. Koshizuka","doi":"10.1145/3316615.3316625","DOIUrl":"https://doi.org/10.1145/3316615.3316625","url":null,"abstract":"Delivery route optimization for logistic industry is one of applications proposed on smart meter infrastructure. It's expected to drastically reduce absent-delivery which amounts to 20% of total delivery in Japan, which estimated to save $billions a year. But as previous works pointed out, the concern on user privacy is the biggest hurdle yet to be addressed. In this research, we proposed a new approach to improve user privacy by converting electricity data into route data and optimize it before providing to service provider. Then, we tested pragmatic privacy improvement and route optimization through actual delivery experiment. Results showed that the information leakage rate (# of absence detection per delivery) decreased from 23% to 4% by this system and decreased to 2% with additional operational change. Also, the experiment validated decrease of absent-delivery rate from 23% to 2% and travel distance by 5% while improving privacy. Applying adequate method to \"delivery optimization through occupancy prediction\" enabled achieving both user privacy and absent-delivery reduction significantly.","PeriodicalId":268392,"journal":{"name":"Proceedings of the 2019 8th International Conference on Software and Computer Applications","volume":"183 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133298985","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}
DevOps and Continuous Delivery (CD) are the terms that are always related to each other in Software Delivery and Operation Process area. DevOps introduces a significant agile perspective to deliver the software product in short cycle time that will reduce technical debt that is caused by delay. Continuous Delivery is one of the DevOps' practices that enables software organization to release new features and new products rapidly. However, the correct practices are still in ambiguity to the current CD process. This paper investigates the advantages and limitation of DevOps adoption to improve the CD process. A qualitative web survey has been conducted to identify the DevOps and Continuous Delivery advantages and adoption problems. 13 respondents' feedbacks have been collected and analyzed. Based on the survey, there are four significant DevOps' practices that need to be considered and developed as a proper guideline to introduce to practitioners.
{"title":"Adoption Issues in DevOps from the Perspective of Continuous Delivery Pipeline","authors":"M. Toh, S. Sahibuddin, M. N. Mahrin","doi":"10.1145/3316615.3316619","DOIUrl":"https://doi.org/10.1145/3316615.3316619","url":null,"abstract":"DevOps and Continuous Delivery (CD) are the terms that are always related to each other in Software Delivery and Operation Process area. DevOps introduces a significant agile perspective to deliver the software product in short cycle time that will reduce technical debt that is caused by delay. Continuous Delivery is one of the DevOps' practices that enables software organization to release new features and new products rapidly. However, the correct practices are still in ambiguity to the current CD process. This paper investigates the advantages and limitation of DevOps adoption to improve the CD process. A qualitative web survey has been conducted to identify the DevOps and Continuous Delivery advantages and adoption problems. 13 respondents' feedbacks have been collected and analyzed. Based on the survey, there are four significant DevOps' practices that need to be considered and developed as a proper guideline to introduce to practitioners.","PeriodicalId":268392,"journal":{"name":"Proceedings of the 2019 8th International Conference on Software and Computer Applications","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114264904","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}
At present, the WebVR technology based on mobile Internet is becoming more and more mature, but there is relatively little research on P2P transmission of WebVR scene data between mobile web pages. For the past WebTorrent scheme, the concept of interest domain and avatar behavior grouping is not considered, but only pure P2P transmission problem is considered. On the one hand, a more scalable WebVR peer-to-peer transmission platform is implemented based on PeerJS, on the other hand, considering the behavioral characteristics of WebVR avatars, a WebVR interest domain partitioning method based on user attribute recommendation algorithm is proposed. Experimental results show that the proposed scheme has good results for WebVR peer-to-peer transmission.
{"title":"A User Attribute Recommendation Algorithm and Peer3D Technology based WebVR P2P Transmission Scheme","authors":"Huijuan Zhang, Lei Qiao, Dongqing Wang","doi":"10.1145/3316615.3316726","DOIUrl":"https://doi.org/10.1145/3316615.3316726","url":null,"abstract":"At present, the WebVR technology based on mobile Internet is becoming more and more mature, but there is relatively little research on P2P transmission of WebVR scene data between mobile web pages. For the past WebTorrent scheme, the concept of interest domain and avatar behavior grouping is not considered, but only pure P2P transmission problem is considered. On the one hand, a more scalable WebVR peer-to-peer transmission platform is implemented based on PeerJS, on the other hand, considering the behavioral characteristics of WebVR avatars, a WebVR interest domain partitioning method based on user attribute recommendation algorithm is proposed. Experimental results show that the proposed scheme has good results for WebVR peer-to-peer transmission.","PeriodicalId":268392,"journal":{"name":"Proceedings of the 2019 8th International Conference on Software and Computer Applications","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114269969","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}
With the development of society, applying data mining schemes in the chemometrics discipline is increasing rapidly which makes this field very popular. However, machine learning algorithms face challenges in selecting best algorithm's parameters as well as selecting the features of the data that affect the decision-making process. Limited studies have in-depth explored ways of enhancing decision support systems in the chemometrics domain. Therefore, this study aims at reinforcing the decision-making process through proposing a robust approach: "feature selection" and "algorithm optimization" in conjunction with "cross-validation". Precisely, stratified tenfold cross-validation method was utilized to evaluate the parameter selection of both Multilayer perceptron and Partial least-squares regression algorithms, from the one hand, and to select the best prediction features, from the other hand. Results exhibited that Multilayer perceptron model overperformed partial least-squares regression model. This confirms that Multilayer perceptron can be efficiently used in the chemometrics discipline. Our result also listed the selected feature for the utilized data. Consequently, current study opens the door for enhancing the industry, generally, and the chemometrics-related manufacturing, especially. It also sheds some light on the significance of adopting cross-validation for model selection and parameter optimization in the chemometrics domain for improving the quality of the decision-making process.
{"title":"Reinforcing the Decision-making Process in Chemometrics: Feature Selection and Algorithm Optimization","authors":"Samer Muthana Sarsam","doi":"10.1145/3316615.3316644","DOIUrl":"https://doi.org/10.1145/3316615.3316644","url":null,"abstract":"With the development of society, applying data mining schemes in the chemometrics discipline is increasing rapidly which makes this field very popular. However, machine learning algorithms face challenges in selecting best algorithm's parameters as well as selecting the features of the data that affect the decision-making process. Limited studies have in-depth explored ways of enhancing decision support systems in the chemometrics domain. Therefore, this study aims at reinforcing the decision-making process through proposing a robust approach: \"feature selection\" and \"algorithm optimization\" in conjunction with \"cross-validation\". Precisely, stratified tenfold cross-validation method was utilized to evaluate the parameter selection of both Multilayer perceptron and Partial least-squares regression algorithms, from the one hand, and to select the best prediction features, from the other hand. Results exhibited that Multilayer perceptron model overperformed partial least-squares regression model. This confirms that Multilayer perceptron can be efficiently used in the chemometrics discipline. Our result also listed the selected feature for the utilized data. Consequently, current study opens the door for enhancing the industry, generally, and the chemometrics-related manufacturing, especially. It also sheds some light on the significance of adopting cross-validation for model selection and parameter optimization in the chemometrics domain for improving the quality of the decision-making process.","PeriodicalId":268392,"journal":{"name":"Proceedings of the 2019 8th International Conference on Software and Computer Applications","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123383522","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}
N. T. Duy, Tran Thi Thuy, Luong Thuy Chung, Ngo Tung Son, Tran Van Dinh
In this paper, we consider a two-way relay network system which contains multiple cooperative relays transmitting information between two sources with attendance of an eavesdropper. A null space beamforming scheme is applied to ensure the secrecy in system. Our goal is achieving maximal secrecy sum rate with a certain level power transmit. In [1], authors propose an approach to solve Secrecy Sum Rate Maximization (SSRM) problem, whereas we use another approach based on Different of Convex Functions Algorithm (DCA).
{"title":"DC programming and DCA for Secure Guarantee with Null Space Beamforming in Two-Way Relay Networks","authors":"N. T. Duy, Tran Thi Thuy, Luong Thuy Chung, Ngo Tung Son, Tran Van Dinh","doi":"10.1145/3316615.3316687","DOIUrl":"https://doi.org/10.1145/3316615.3316687","url":null,"abstract":"In this paper, we consider a two-way relay network system which contains multiple cooperative relays transmitting information between two sources with attendance of an eavesdropper. A null space beamforming scheme is applied to ensure the secrecy in system. Our goal is achieving maximal secrecy sum rate with a certain level power transmit. In [1], authors propose an approach to solve Secrecy Sum Rate Maximization (SSRM) problem, whereas we use another approach based on Different of Convex Functions Algorithm (DCA).","PeriodicalId":268392,"journal":{"name":"Proceedings of the 2019 8th International Conference on Software and Computer Applications","volume":"119 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123035992","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}
The main construction method of the current ontology is to rely on ontology experts for manual construction. Because manual construction requires a lot of manual participation, manual construction has great limitations. Text data as one of the main forms of data source, how to construct domain ontology automatically from texts and how to provide semantic retrieval support to text quickly by ontology is the hotspot of ontology research at present. Aiming at the above problems, an automatic construction method of domain ontology based on knowledge graph and association rule mining is presented, and it can extract the concepts, hierarchies and non-hierarchies of domain ontology from text, and finally form ontology by Jena. It also provides semantic retrieval of text by associating text and concepts in the process of ontology construction. Finally, the effect of automatic ontology construction is verified by the effect of text retrieval.
{"title":"Research on Domain Ontology Automation Construction Based on Chinese Texts","authors":"Bo Wang, Junwei Luo, Shuyuan Zhu","doi":"10.1145/3316615.3316685","DOIUrl":"https://doi.org/10.1145/3316615.3316685","url":null,"abstract":"The main construction method of the current ontology is to rely on ontology experts for manual construction. Because manual construction requires a lot of manual participation, manual construction has great limitations. Text data as one of the main forms of data source, how to construct domain ontology automatically from texts and how to provide semantic retrieval support to text quickly by ontology is the hotspot of ontology research at present. Aiming at the above problems, an automatic construction method of domain ontology based on knowledge graph and association rule mining is presented, and it can extract the concepts, hierarchies and non-hierarchies of domain ontology from text, and finally form ontology by Jena. It also provides semantic retrieval of text by associating text and concepts in the process of ontology construction. Finally, the effect of automatic ontology construction is verified by the effect of text retrieval.","PeriodicalId":268392,"journal":{"name":"Proceedings of the 2019 8th International Conference on Software and Computer Applications","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122133001","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}
Chunling Hu, Guoqing Geng, Bixin Li, Chao Tang, Xiaofeng Wang
Cloud application is a kind of software implemented using cloud computing technology and deployed in the cloud environment. This paper focuses on guaranteeing the interaction correctness between cloud application and users. In general, the main methods to do this are testing and verification. But in the cloud environment, testing is costly and the operation is extremely difficult, while the verification can avoid these shortcomings, and be suitable for cloud application. In this paper, we use SoaML(Service-Oriented Architecture Modeling Language) to model cloud application, apply hierarchical automaton to formalize ServiceInterface of SoaML, and translate SeviceInterface into PROMELA according to the semantics of automaton; Meanwhile, describe the ServiceContract of SoaML using linear temporal logic (LTL). Both PROMELA and LTL formula are integrated into SPIN model checker for automatic verification of cloud application. Experiment shows that we can verify the correctness of cloud application effectively.
{"title":"Verifying Cloud Application for the Interaction Correctness Using SoaML and SPIN","authors":"Chunling Hu, Guoqing Geng, Bixin Li, Chao Tang, Xiaofeng Wang","doi":"10.1145/3316615.3316714","DOIUrl":"https://doi.org/10.1145/3316615.3316714","url":null,"abstract":"Cloud application is a kind of software implemented using cloud computing technology and deployed in the cloud environment. This paper focuses on guaranteeing the interaction correctness between cloud application and users. In general, the main methods to do this are testing and verification. But in the cloud environment, testing is costly and the operation is extremely difficult, while the verification can avoid these shortcomings, and be suitable for cloud application. In this paper, we use SoaML(Service-Oriented Architecture Modeling Language) to model cloud application, apply hierarchical automaton to formalize ServiceInterface of SoaML, and translate SeviceInterface into PROMELA according to the semantics of automaton; Meanwhile, describe the ServiceContract of SoaML using linear temporal logic (LTL). Both PROMELA and LTL formula are integrated into SPIN model checker for automatic verification of cloud application. Experiment shows that we can verify the correctness of cloud application effectively.","PeriodicalId":268392,"journal":{"name":"Proceedings of the 2019 8th International Conference on Software and Computer Applications","volume":"103 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122539906","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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