Pub Date : 2016-08-01DOI: 10.1109/ICSESS.2016.7883004
L. Yuhua, Lu Min-yan, X. Biao
For high reliability software, mission critical system software and embedded system software, to demonstrate convincingly and validly that the software satisfies the reliability requirements is one of the most challenging issues. In this paper, we present a method for developing software reliability case based on software reliability characteristic model and measures of defect control. Three software reliability argument patterns are proposed. As a case study, we take the load control software to demonstrate how a software reliability case can be generated using the proposed method and corresponding argument patterns.
{"title":"Software reliability case development method based on software reliability characteristic model and measures of defect control","authors":"L. Yuhua, Lu Min-yan, X. Biao","doi":"10.1109/ICSESS.2016.7883004","DOIUrl":"https://doi.org/10.1109/ICSESS.2016.7883004","url":null,"abstract":"For high reliability software, mission critical system software and embedded system software, to demonstrate convincingly and validly that the software satisfies the reliability requirements is one of the most challenging issues. In this paper, we present a method for developing software reliability case based on software reliability characteristic model and measures of defect control. Three software reliability argument patterns are proposed. As a case study, we take the load control software to demonstrate how a software reliability case can be generated using the proposed method and corresponding argument patterns.","PeriodicalId":175933,"journal":{"name":"2016 7th IEEE International Conference on Software Engineering and Service Science (ICSESS)","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130297747","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 : 2016-08-01DOI: 10.1109/ICSESS.2016.7883250
Shan Tang, Liping Li, Xiaolin Cao
The execution context of today's software systems changes continually, which makes systems have to cope with changing environments while at the same time facing high non-functional requirements such as flexibility and dependability. Runtime adaptation technology can modify behaviors and structures in response to changes in the system itself or in its environment and thus improve dependability at run time. This leads to a more flexible and effective way to build dependable software system. However, current works address adaptation often remain a neglected gap between the architecture model and the system state. To solve this problem, we present a systematic process that covers requirements modeling, architecture and system modeling of trustworthy software based on a runtime self-adaptation perspective.
{"title":"Research on building trustworthy software system by self-adaptation","authors":"Shan Tang, Liping Li, Xiaolin Cao","doi":"10.1109/ICSESS.2016.7883250","DOIUrl":"https://doi.org/10.1109/ICSESS.2016.7883250","url":null,"abstract":"The execution context of today's software systems changes continually, which makes systems have to cope with changing environments while at the same time facing high non-functional requirements such as flexibility and dependability. Runtime adaptation technology can modify behaviors and structures in response to changes in the system itself or in its environment and thus improve dependability at run time. This leads to a more flexible and effective way to build dependable software system. However, current works address adaptation often remain a neglected gap between the architecture model and the system state. To solve this problem, we present a systematic process that covers requirements modeling, architecture and system modeling of trustworthy software based on a runtime self-adaptation perspective.","PeriodicalId":175933,"journal":{"name":"2016 7th IEEE International Conference on Software Engineering and Service Science (ICSESS)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134175807","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 : 2016-08-01DOI: 10.1109/ICSESS.2016.7883113
Zhiquan Lai, Yongjun Shen, Guidong Zhang
In the field of information security, risk assessment is the core of the risk management and control. This paper proposes a security risk assessment method based on threat analysis combined with AHP and entropy weight. This method has features that are suitable for website such as practical, easy operative and independent. And the AHP and entropy weight make the evaluation results more objective. This paper gives the calculation model of the method and the main procedures of risk assessment. Finally, take a website as an example to verify the rationality and effectiveness of this method.
{"title":"A security risk assessment method of website based on threat analysis combined with AHP and entropy weight","authors":"Zhiquan Lai, Yongjun Shen, Guidong Zhang","doi":"10.1109/ICSESS.2016.7883113","DOIUrl":"https://doi.org/10.1109/ICSESS.2016.7883113","url":null,"abstract":"In the field of information security, risk assessment is the core of the risk management and control. This paper proposes a security risk assessment method based on threat analysis combined with AHP and entropy weight. This method has features that are suitable for website such as practical, easy operative and independent. And the AHP and entropy weight make the evaluation results more objective. This paper gives the calculation model of the method and the main procedures of risk assessment. Finally, take a website as an example to verify the rationality and effectiveness of this method.","PeriodicalId":175933,"journal":{"name":"2016 7th IEEE International Conference on Software Engineering and Service Science (ICSESS)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134522823","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 : 2016-08-01DOI: 10.1109/ICSESS.2016.7883159
Wang Lei, Guoqiang Xiao
Most of the current image retrieval systems for large scale database rely on the Bag-of-Words (BoW) representation and inverted index. We analyze these systems and find that the retrieval performance is largely determined by the discriminative ability of their inverted indexes. This motivates us to combine SIFT and local color features into a two-dimensional inverted index (TD-II). Each dimension of TD-II corresponds to one kind of features, so the precision of visual match is enhanced. After constructing the TD-II of local features, we introduce a semantic-aware co-indexing algorithm which utilizes 1000 semantic attributes to insert similar images to the initial set of TD-II. Embedding semantic attributes into TD-II is totally off-line and effectively enhances the retrieval performance of TD-II. Experimental results demonstrate the competitive performance of our method, comparing with recent retrieval methods on two benchmark datasets, i.e., Ukbench and Holidays.
{"title":"Image retrieval using two-dimensional inverted index and semantic attributes","authors":"Wang Lei, Guoqiang Xiao","doi":"10.1109/ICSESS.2016.7883159","DOIUrl":"https://doi.org/10.1109/ICSESS.2016.7883159","url":null,"abstract":"Most of the current image retrieval systems for large scale database rely on the Bag-of-Words (BoW) representation and inverted index. We analyze these systems and find that the retrieval performance is largely determined by the discriminative ability of their inverted indexes. This motivates us to combine SIFT and local color features into a two-dimensional inverted index (TD-II). Each dimension of TD-II corresponds to one kind of features, so the precision of visual match is enhanced. After constructing the TD-II of local features, we introduce a semantic-aware co-indexing algorithm which utilizes 1000 semantic attributes to insert similar images to the initial set of TD-II. Embedding semantic attributes into TD-II is totally off-line and effectively enhances the retrieval performance of TD-II. Experimental results demonstrate the competitive performance of our method, comparing with recent retrieval methods on two benchmark datasets, i.e., Ukbench and Holidays.","PeriodicalId":175933,"journal":{"name":"2016 7th IEEE International Conference on Software Engineering and Service Science (ICSESS)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130959046","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 : 2016-08-01DOI: 10.1109/ICSESS.2016.7883010
Shaolei Wang, Lei Zhang, Chaojing Tang
In this paper, the problem of false traceroute links caused by load balancing is analysed and formulated. To solve this problem, the authors proposed a novel reliable assumption called the Last Link Assumption based on a fact that neglected by most researchers. The limitations of proposed assumption is analysed and presented. Then, the authors proposed an effective probing algorithm called the Last Link Inference Algorithm based on the proposed assumption. After that, the effectiveness of proposed algorithm for link inference in the presence of symmetric and asymmetric per-packet load balancing is demonstrated by comparing the topology measurement results of experimental networks with classic traceroute and Paris traceroute. The support rate of proposed algorithm in the Internet environment could reach 87.5% according to our topology measurement experiment.
{"title":"Link inference in the presense of load balancing","authors":"Shaolei Wang, Lei Zhang, Chaojing Tang","doi":"10.1109/ICSESS.2016.7883010","DOIUrl":"https://doi.org/10.1109/ICSESS.2016.7883010","url":null,"abstract":"In this paper, the problem of false traceroute links caused by load balancing is analysed and formulated. To solve this problem, the authors proposed a novel reliable assumption called the Last Link Assumption based on a fact that neglected by most researchers. The limitations of proposed assumption is analysed and presented. Then, the authors proposed an effective probing algorithm called the Last Link Inference Algorithm based on the proposed assumption. After that, the effectiveness of proposed algorithm for link inference in the presence of symmetric and asymmetric per-packet load balancing is demonstrated by comparing the topology measurement results of experimental networks with classic traceroute and Paris traceroute. The support rate of proposed algorithm in the Internet environment could reach 87.5% according to our topology measurement experiment.","PeriodicalId":175933,"journal":{"name":"2016 7th IEEE International Conference on Software Engineering and Service Science (ICSESS)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130981453","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 : 2016-08-01DOI: 10.1109/ICSESS.2016.7883015
Ye Fei
Sentiment classification is widely used in some areas, such as product reviews, movie reviews, and micro-blogging reviews. Sentiment classification method is mainly bag of words model, Naive Bayes and Support Vector Machine. In recent years, the machine learning method represented by support vector machine (SVM) is widely used in the field of sentiment classification. There are more and more experiments show that support vector machine (SVM) performs better than the traditional bag of words model in the field of sentiment classification. However, more researches mainly focus on semantic analysis and feature extraction on sentiment, but also did not consider the case of sample imbalance. The purpose of this study was to test the feasibility of sentiment classification based on the genetic algorithm to optimize SVM model. Genetic algorithm is an optimization algorithm, which often used for selecting the feature subset and the optimization of the SVM parameters. This paper presents a novel optimization method, which select the optimal support vector subset by genetic algorithm and optimize SVM parameters. We construct the experiment show that the proposed method has improved significantly on sentiment classification than the traditional SVM modeling capabilities.
{"title":"Simultaneous Support Vector selection and parameter optimization using Support Vector Machines for sentiment classification","authors":"Ye Fei","doi":"10.1109/ICSESS.2016.7883015","DOIUrl":"https://doi.org/10.1109/ICSESS.2016.7883015","url":null,"abstract":"Sentiment classification is widely used in some areas, such as product reviews, movie reviews, and micro-blogging reviews. Sentiment classification method is mainly bag of words model, Naive Bayes and Support Vector Machine. In recent years, the machine learning method represented by support vector machine (SVM) is widely used in the field of sentiment classification. There are more and more experiments show that support vector machine (SVM) performs better than the traditional bag of words model in the field of sentiment classification. However, more researches mainly focus on semantic analysis and feature extraction on sentiment, but also did not consider the case of sample imbalance. The purpose of this study was to test the feasibility of sentiment classification based on the genetic algorithm to optimize SVM model. Genetic algorithm is an optimization algorithm, which often used for selecting the feature subset and the optimization of the SVM parameters. This paper presents a novel optimization method, which select the optimal support vector subset by genetic algorithm and optimize SVM parameters. We construct the experiment show that the proposed method has improved significantly on sentiment classification than the traditional SVM modeling capabilities.","PeriodicalId":175933,"journal":{"name":"2016 7th IEEE International Conference on Software Engineering and Service Science (ICSESS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132141703","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 : 2016-08-01DOI: 10.1109/ICSESS.2016.7883238
Siping Chen
Dissolved gas analysis is one of the most common techniques to detect the faults in the power transformers. Most of existing diagnosis method will need large amount of labeled data sets to construct classifier, while normally ignoring without unlabeled data sets. This paper presents a power transformer fault diagnosis method which based on semi-supervised classifying. In Its learning process, the semi-supervised classifying method can simultaneously use labeled data sets and unlabeled data sets to acquire more information so that make better learning effect. A semi-supervised classifying (SSC) method adopting fuzzy nearest neighborhood label propagation (FNNLP-SSC)is adopted to diagnose the fault of power transformer, in the meantime, the proposed method, based on the similarity connections between a sample and its K nearest data, classifies the unlabeled data by making the labels propagate from the labeled data to unlabeled data. The experiments indicate that method of this paper has been proposed has higher fault diagnosis accuracy compared with C-means (FCM) algorithm and the three ratio method IEC. Also, it verifies the effectiveness and feasibility of the proposed method in the transformer fault diagnosis.
{"title":"A kind of semi-supervised classifying method research for power transformer fault diagnosis","authors":"Siping Chen","doi":"10.1109/ICSESS.2016.7883238","DOIUrl":"https://doi.org/10.1109/ICSESS.2016.7883238","url":null,"abstract":"Dissolved gas analysis is one of the most common techniques to detect the faults in the power transformers. Most of existing diagnosis method will need large amount of labeled data sets to construct classifier, while normally ignoring without unlabeled data sets. This paper presents a power transformer fault diagnosis method which based on semi-supervised classifying. In Its learning process, the semi-supervised classifying method can simultaneously use labeled data sets and unlabeled data sets to acquire more information so that make better learning effect. A semi-supervised classifying (SSC) method adopting fuzzy nearest neighborhood label propagation (FNNLP-SSC)is adopted to diagnose the fault of power transformer, in the meantime, the proposed method, based on the similarity connections between a sample and its K nearest data, classifies the unlabeled data by making the labels propagate from the labeled data to unlabeled data. The experiments indicate that method of this paper has been proposed has higher fault diagnosis accuracy compared with C-means (FCM) algorithm and the three ratio method IEC. Also, it verifies the effectiveness and feasibility of the proposed method in the transformer fault diagnosis.","PeriodicalId":175933,"journal":{"name":"2016 7th IEEE International Conference on Software Engineering and Service Science (ICSESS)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133140647","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 : 2016-08-01DOI: 10.1109/ICSESS.2016.7883033
Xingbin Ge, Zhiyi Qu
Location-based services have been deep into all aspects of life and it provides a convenient and efficient service experience for people. Currently, technology is relatively mature and widely used in the outdoor positioning. By contrast, for indoor positioning, although there are a lot of hot technology, but they are mostly insufficient lead to it is hard to popularize. So how to improve the popularity of indoor positioning in the case of improve the positioning accuracy has became a hot research topoc. This paper analyzes and studies several typical fingerprint localization algorithm, including NN, KNN and WKNN, and then propose an algorithmic improvement program, it introduces signal propagation model, finds and narrows the K-gon.
{"title":"Optimization WIFI indoor positioning KNN algorithm location-based fingerprint","authors":"Xingbin Ge, Zhiyi Qu","doi":"10.1109/ICSESS.2016.7883033","DOIUrl":"https://doi.org/10.1109/ICSESS.2016.7883033","url":null,"abstract":"Location-based services have been deep into all aspects of life and it provides a convenient and efficient service experience for people. Currently, technology is relatively mature and widely used in the outdoor positioning. By contrast, for indoor positioning, although there are a lot of hot technology, but they are mostly insufficient lead to it is hard to popularize. So how to improve the popularity of indoor positioning in the case of improve the positioning accuracy has became a hot research topoc. This paper analyzes and studies several typical fingerprint localization algorithm, including NN, KNN and WKNN, and then propose an algorithmic improvement program, it introduces signal propagation model, finds and narrows the K-gon.","PeriodicalId":175933,"journal":{"name":"2016 7th IEEE International Conference on Software Engineering and Service Science (ICSESS)","volume":"292 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114095654","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 : 2016-08-01DOI: 10.1109/ICSESS.2016.7883005
Jessada Tomyim, A. Pohthong
User requirements for software development are getting more complicated and are changing all the time. Not only should the requirements engineering process be well-organized but requirements change management should also be effective, especially for complex systems. However, the software engineering methodology employed can also make requirements change difficult to manage. Object-oriented software engineering using unified modeling language (UML) describes software systems by providing multiple views and diagrams. Therefore, software development with UML needs effective requirements change management. This study proposed a requirements change management model for object-oriented methodology with UML. In order to demonstrate the proposed model, business models from the selected case study, Mission Hospital Phuket, were chosen as the user requirements for the prototype system. Two aspects of the proposed system's performance were evaluated in the research laboratory: (1) users' expectation and (2) users' satisfaction.
{"title":"Requirements change management based on object-oriented software engineering with unified modeling language","authors":"Jessada Tomyim, A. Pohthong","doi":"10.1109/ICSESS.2016.7883005","DOIUrl":"https://doi.org/10.1109/ICSESS.2016.7883005","url":null,"abstract":"User requirements for software development are getting more complicated and are changing all the time. Not only should the requirements engineering process be well-organized but requirements change management should also be effective, especially for complex systems. However, the software engineering methodology employed can also make requirements change difficult to manage. Object-oriented software engineering using unified modeling language (UML) describes software systems by providing multiple views and diagrams. Therefore, software development with UML needs effective requirements change management. This study proposed a requirements change management model for object-oriented methodology with UML. In order to demonstrate the proposed model, business models from the selected case study, Mission Hospital Phuket, were chosen as the user requirements for the prototype system. Two aspects of the proposed system's performance were evaluated in the research laboratory: (1) users' expectation and (2) users' satisfaction.","PeriodicalId":175933,"journal":{"name":"2016 7th IEEE International Conference on Software Engineering and Service Science (ICSESS)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134024168","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 : 2016-08-01DOI: 10.1109/ICSESS.2016.7883224
Jiehong Wu, Ilia Detchenkov, Yang Cao
Mobile Ad Hoc network is rapidly developing research area, one of the open question in this area is secure data inside the network. Encryption algorithms play a main role in information security systems. On the other side, those algorithms consume a significant amount of computing resources such as CPU time, memory, and battery power. This paper provides evaluation of three of the common encryption algorithms: AES, Blowfish, and GOST. A comparison has been conducted for those encryption algorithms at different sizes of data blocks. Key expansion time and encryption/decryption speed was measured. Simulation results are given to demonstrate the effectiveness of each algorithm.
{"title":"A study on the power consumption of using cryptography algorithms in mobile devices","authors":"Jiehong Wu, Ilia Detchenkov, Yang Cao","doi":"10.1109/ICSESS.2016.7883224","DOIUrl":"https://doi.org/10.1109/ICSESS.2016.7883224","url":null,"abstract":"Mobile Ad Hoc network is rapidly developing research area, one of the open question in this area is secure data inside the network. Encryption algorithms play a main role in information security systems. On the other side, those algorithms consume a significant amount of computing resources such as CPU time, memory, and battery power. This paper provides evaluation of three of the common encryption algorithms: AES, Blowfish, and GOST. A comparison has been conducted for those encryption algorithms at different sizes of data blocks. Key expansion time and encryption/decryption speed was measured. Simulation results are given to demonstrate the effectiveness of each algorithm.","PeriodicalId":175933,"journal":{"name":"2016 7th IEEE International Conference on Software Engineering and Service Science (ICSESS)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134526140","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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