Pub Date : 1900-01-01DOI: 10.18293/jvlc2020-n2-010
Chunying Zhao, Cong Chen, Kang Zhang, Jun Kong
Regression testing is a type of software testing that aims at identifying faults caused by code changes. Regression testing is important especially during software evolution and maintenance. As developers integrate programs or make updates to a software system, they need to make sure the changes do not adversely affect other parts of the system. Using dynamic analysis, behavioral regression testing (BERT) is one of the techniques proposed to solve the problem by re-executing test cases that target the affected area. It compares the behavior of a program before and after the changes upon certain test cases. This paper proposes Visual BEhavioral Regression Testing (ViBERT), a visualization approach to comparing the behavioral differences between the new and old versions of a program in regression testing. We build a prototype called SoftLink, a visual environment that shows correlation/difference between two versions of a program behavior. SoftLink displays call graphs of two executions on angled parallel planes in a 3D space, and constructs correlations between them. It provides developers with an intuitive interpretation of the testing results. A case study is presented.
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Pub Date : 1900-01-01DOI: 10.18293/jvlc2020-n2-008
Hanzhong Zheng, Justin Kramer, Shi-Kuo Chang
The evolution of the software architecture has been progressively shifting to emphasize modularity, isolation, scalability, agility, and loose coupling. Service-oriented architecture (SOA) has started to gain popularity in this direction. Micro-services are a lightweight SOA that aim to largely scale applications while ensuring isolation and distribution. Modularity is sometimes left behind or difficult to achieve with fine-grained distribution of programmer responsibilities. In this paper, we propose an automatic modularity enforcement (AME) framework during the software development life cycle (SDLC) through intermediate representation. Our idea was inspired by automatic software development for building a scalable application. We implemented this framework to support visual software development using the Java Spring Boot Micro-service tool.
软件架构的发展已经逐渐转向强调模块化、隔离性、可伸缩性、敏捷性和松耦合。面向服务的体系结构(SOA)已经开始在这个方向上流行起来。微服务是一种轻量级SOA，旨在大规模扩展应用程序，同时确保隔离和分布。模块化有时会被遗忘，或者很难通过细粒度的程序员职责分布来实现。在本文中，我们通过中间表示提出了一个软件开发生命周期(SDLC)中的自动模块化实施(AME)框架。我们的想法是受到用于构建可伸缩应用程序的自动软件开发的启发。我们使用Java Spring Boot微服务工具实现这个框架来支持可视化软件开发。
{"title":"Auto-Modularity Enforcement Framework Using Micro-service Architecture","authors":"Hanzhong Zheng, Justin Kramer, Shi-Kuo Chang","doi":"10.18293/jvlc2020-n2-008","DOIUrl":"https://doi.org/10.18293/jvlc2020-n2-008","url":null,"abstract":"The evolution of the software architecture has been progressively shifting to emphasize modularity, isolation, scalability, agility, and loose coupling. Service-oriented architecture (SOA) has started to gain popularity in this direction. Micro-services are a lightweight SOA that aim to largely scale applications while ensuring isolation and distribution. Modularity is sometimes left behind or difficult to achieve with fine-grained distribution of programmer responsibilities. In this paper, we propose an automatic modularity enforcement (AME) framework during the software development life cycle (SDLC) through intermediate representation. Our idea was inspired by automatic software development for building a scalable application. We implemented this framework to support visual software development using the Java Spring Boot Micro-service tool.","PeriodicalId":297195,"journal":{"name":"J. Vis. Lang. Sentient Syst.","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121479079","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 : 1900-01-01DOI: 10.18293/jvlc2020-n2-009
F. Colace, Marco Lombardi, D. Santaniello
In the panorama of Italian coastal tourism, there are many unique and unexplored places. These places, which suffer from the lack of government investment, present the need to be promoted through low consumption systems and widely used distributed applications. The present work aims to develop innovative solutions to support citizens and tourists to offer advanced services, highly customizable, able to allow, through the use of new technologies, a more engaging, stimulating, and attractive use of information than the current forms. The developed system is based on graph-based formalisms such as Context Dimension Tree and Bayesian Networks, representing the context through its main components and react to it anticipating users' needs. Through the development of a mobile app, it was analyzed a case study applied in the area of Amalfi Coast (in Italy). Finally, an experimental campaign was conducted with promising results.
{"title":"CACHE: Contextual Approach for Cultural Heritage Enhancing","authors":"F. Colace, Marco Lombardi, D. Santaniello","doi":"10.18293/jvlc2020-n2-009","DOIUrl":"https://doi.org/10.18293/jvlc2020-n2-009","url":null,"abstract":"In the panorama of Italian coastal tourism, there are many unique and unexplored places. These places, which suffer from the lack of government investment, present the need to be promoted through low consumption systems and widely used distributed applications. The present work aims to develop innovative solutions to support citizens and tourists to offer advanced services, highly customizable, able to allow, through the use of new technologies, a more engaging, stimulating, and attractive use of information than the current forms. The developed system is based on graph-based formalisms such as Context Dimension Tree and Bayesian Networks, representing the context through its main components and react to it anticipating users' needs. Through the development of a mobile app, it was analyzed a case study applied in the area of Amalfi Coast (in Italy). Finally, an experimental campaign was conducted with promising results.","PeriodicalId":297195,"journal":{"name":"J. Vis. Lang. Sentient Syst.","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124430186","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 : 1900-01-01DOI: 10.18293/jvlc2020-n2-007
Loredana Caruccio, Stefano Cirillo
The automatic discovery from data of Functional Dependencies (FDs), and their extensions Relaxed Functional Dependencies (RFDs), represents one of the main tasks in the data profiling research area. Several algorithms that deal with the “complex” problem of discovering RFDs have been recognized as a fundamental tool to automatically collect them starting from data. Moreover, the characteristics of scenarios involving “big” data require also profiling tasks to evolve towards continuous ones, which must be capable to dynamically collect and update the set of holding RFDs on the analyzed data. In this context, one of the most critical scenarios is represented by the possibility to discover RFDs over data streams. Nevertheless, although the main goal of discovery algorithms is allowing for fast execution processes, to enable the analysis of the resulting RFDs, it is necessary to also devise methods to continuously monitor discovery results. Thus, one of the main goals is to reduce the users’ effort in moving in and out the possible huge quantity of holding RFDs. To this end, in this paper, we present DEVICE, a tool for continuously monitoring resulting RFDs during the execution of discovery processes. In particular, it permits to analyze the evolution of results by using a lattice representation of the search space. Moreover, zooming and filtering functionalities enable the user to focus the analysis on a specific portion of the search space. The effectiveness of the proposed tool has been evaluated in a scenario studying the application of different discovery strategies over a well-known and real-world dataset.
{"title":"Monitoring Evolution of Dependency Discovery Results","authors":"Loredana Caruccio, Stefano Cirillo","doi":"10.18293/jvlc2020-n2-007","DOIUrl":"https://doi.org/10.18293/jvlc2020-n2-007","url":null,"abstract":"The automatic discovery from data of Functional Dependencies (FDs), and their extensions Relaxed Functional Dependencies (RFDs), represents one of the main tasks in the data profiling research area. Several algorithms that deal with the “complex” problem of discovering RFDs have been recognized as a fundamental tool to automatically collect them starting from data. Moreover, the characteristics of scenarios involving “big” data require also profiling tasks to evolve towards continuous ones, which must be capable to dynamically collect and update the set of holding RFDs on the analyzed data. In this context, one of the most critical scenarios is represented by the possibility to discover RFDs over data streams. Nevertheless, although the main goal of discovery algorithms is allowing for fast execution processes, to enable the analysis of the resulting RFDs, it is necessary to also devise methods to continuously monitor discovery results. Thus, one of the main goals is to reduce the users’ effort in moving in and out the possible huge quantity of holding RFDs. To this end, in this paper, we present DEVICE, a tool for continuously monitoring resulting RFDs during the execution of discovery processes. In particular, it permits to analyze the evolution of results by using a lattice representation of the search space. Moreover, zooming and filtering functionalities enable the user to focus the analysis on a specific portion of the search space. The effectiveness of the proposed tool has been evaluated in a scenario studying the application of different discovery strategies over a well-known and real-world dataset.","PeriodicalId":297195,"journal":{"name":"J. Vis. Lang. Sentient Syst.","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114922047","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}
V. Moscato, A. Picariello, Giancarlo Sperlí, F. Amato
In the last decade Recommender Systems have become useful tools helping users to find “what they need” from considerable amount of data. One of the more obvious applications of such systems in the Cultural Heritage domain is to assist users when visiting cultural environments (such as museums, archaeological sites, old town centers and so on), providing a multimedia guide that is able to dynamically suggest relevant information available in multiple web repositories (e.g. multimedia sharing systems and on-line social networks). In this paper, we propose a novel recommendation approach that combines several aspects of users i.e. their preferences (usually in the shape of items’ metadata) and interactions within a social community modeled using hypergraphs together with items’ multimedia features and context information within a general framework that can support di↵erent applications (touristic guiding services for museums, visiting paths recommendation for old town centers and archeological sites, etc.). Preliminary experiments on user satisfaction show how our approach provides very promising and interesting results.
{"title":"Recommender Systems and Social Networks: an application in Cultural Heritage","authors":"V. Moscato, A. Picariello, Giancarlo Sperlí, F. Amato","doi":"10.18293/DMS2016-001","DOIUrl":"https://doi.org/10.18293/DMS2016-001","url":null,"abstract":"In the last decade Recommender Systems have become useful tools helping users to find “what they need” from considerable amount of data. One of the more obvious applications of such systems in the Cultural Heritage domain is to assist users when visiting cultural environments (such as museums, archaeological sites, old town centers and so on), providing a multimedia guide that is able to dynamically suggest relevant information available in multiple web repositories (e.g. multimedia sharing systems and on-line social networks). In this paper, we propose a novel recommendation approach that combines several aspects of users i.e. their preferences (usually in the shape of items’ metadata) and interactions within a social community modeled using hypergraphs together with items’ multimedia features and context information within a general framework that can support di↵erent applications (touristic guiding services for museums, visiting paths recommendation for old town centers and archeological sites, etc.). Preliminary experiments on user satisfaction show how our approach provides very promising and interesting results.","PeriodicalId":297195,"journal":{"name":"J. Vis. Lang. Sentient Syst.","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125947471","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 : 1900-01-01DOI: 10.18293/jvlc2020-n2-006
F. Colace, Muhammad Khan, Marco Lombardi, D. Santaniello
Today's society is heavily oriented towards digitalization, which increasingly affects the management of cities and services. This process is performed through the use of the Internet of Things (IoT) paradigm, from which arise problems related to security. In this scenario, based on the continuous exchange of information on the network, an increasingly significant role is played by systems able to guarantee data security. Protecting the modern Computer Networks could be a very complex task. In this paper, a methodology based on three graphic models (Context Dimension Tree, Ontology and Bayesian Network) is proposed. Three different models are used which use context representation and probabilistic approaches to predict cyber-attacks. The paper proposes, in fact, the use of Bayesian networks built through an ontological definition of the problem dropped on a certain context represented by a Context Dimension Tree. The proposed approach has been experimented in a real scenario providing satisfactory results.
{"title":"A Multilayer Graph Approach for Predicting Computer Network Cyber-attacks","authors":"F. Colace, Muhammad Khan, Marco Lombardi, D. Santaniello","doi":"10.18293/jvlc2020-n2-006","DOIUrl":"https://doi.org/10.18293/jvlc2020-n2-006","url":null,"abstract":"Today's society is heavily oriented towards digitalization, which increasingly affects the management of cities and services. This process is performed through the use of the Internet of Things (IoT) paradigm, from which arise problems related to security. In this scenario, based on the continuous exchange of information on the network, an increasingly significant role is played by systems able to guarantee data security. Protecting the modern Computer Networks could be a very complex task. In this paper, a methodology based on three graphic models (Context Dimension Tree, Ontology and Bayesian Network) is proposed. Three different models are used which use context representation and probabilistic approaches to predict cyber-attacks. The paper proposes, in fact, the use of Bayesian networks built through an ontological definition of the problem dropped on a certain context represented by a Context Dimension Tree. The proposed approach has been experimented in a real scenario providing satisfactory results.","PeriodicalId":297195,"journal":{"name":"J. Vis. Lang. Sentient Syst.","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123475256","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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