Today's software development depends greatly on frameworks and libraries. When their APIs evolve, developers must update their programs accordingly. Existing approaches facilitate the upgrading process by generati...
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ISBN:
(纸本)9780769543987
Today's software development depends greatly on frameworks and libraries. When their APIs evolve, developers must update their programs accordingly. Existing approaches facilitate the upgrading process by generating change-rules based on various input data, such call dependency, text similarity, software metrics, etc. However, existing approaches do not provide 100% precision and recall because of the limited set of input data that they use to generate change-rules. For example, an approach only considering text similarity usually discovers less change-rules then that considering both text similarity and call dependency with similar precision. But adding more input data may increase the complexity of the change-rule generating algorithms and make them unpractical. We propse MOFAE (Multi-Objective Framework API Evolution) by modeling framework API evolution as multi-objective optimization problem to take more input data into account while generating change-rules and to control the algorithmic complexity.
the advent of Business intelligence systems and data mining techniques has helped the business owners to make better decisions in order to increase their profits. Apart from other factors, profits and sales can be inc...
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ISBN:
(纸本)9781538629697
the advent of Business intelligence systems and data mining techniques has helped the business owners to make better decisions in order to increase their profits. Apart from other factors, profits and sales can be increased if an efficient and effective store infrastructure is in place. We propose a framework that uses customers' data to suggest improvements to the store's physical infrastructure by applying machine learning techniques. The research also covers the comparisons of recommendation systems in the retail industry and the application of two different machine learning approaches to achieve our goals.
The analysis of data stored in heterogeneous data sources requires the support of a suitable platform allowing the acquisition and analysis of heterogeneous information. The heterogenity of the data source may concern...
ISBN:
(纸本)9781880843826
The analysis of data stored in heterogeneous data sources requires the support of a suitable platform allowing the acquisition and analysis of heterogeneous information. The heterogenity of the data source may concern the use of different technologies and representation of data representing the same concept and/or concepts to be aggregated in different ways. In order to deal with this research issue, this paper proposes a generalized platform for creating a virtual view of the heterogeneous data sources and allowing the acquisition and analysis of heterogeneous data. The usefulness of the proposed platform is validated through a case study, regarding the acquisition and analysis of healthcare heterogeneous data. Tye acquisition is performed without knowing details regarding each single data source.
Component-based softwareengineering (CBSE) has elicited research interests in recent times in different industrial sectors, including the educational domain because of its perceived advantage over traditional develop...
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ISBN:
(纸本)9781479949984
Component-based softwareengineering (CBSE) has elicited research interests in recent times in different industrial sectors, including the educational domain because of its perceived advantage over traditional development approaches. However, there is need to empirically justify this claim through case study reports from several industrial domains. A university as a complex enterprise needs an Enterprise Resource Planning (ERP) system to automate its complex operational and administrative procedures for efficiency and effectiveness. However, the peculiarity of each university makes it difficult to obtain commercial off-the-shelf ERPS that perfectly suits their requirements. This paper, reports the application of the CBSE paradigm for the development of a university ERP - specifically an e-Administration System. The research provides a basis to empirically compare the merits of CBSE and traditional development approaches. The result of the case study yielded a usable ERP for a Nigerian university, and concrete empirical data that confirmed the superiority of CBSE over traditional software development.
In this article, we investigate the flexible coupling of distributed software components that are required for an optimization process of lightweight structures built from hybrid materials. The software components inc...
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ISBN:
(纸本)9789897580369
In this article, we investigate the flexible coupling of distributed software components that are required for an optimization process of lightweight structures built from hybrid materials. The software components include computationally intensive applications for the simulation of hybrid structures, control applications for implementing the optimization process as well as data-oriented applications for the generation, management, and visualization of simulation data. The participating software components and application programs are described to demonstrate their strongly varying functionalities as well as the diversity of data exchange methods that need to be considered for the data coupling. Furthermore, we present the design and usage of a software library with transparent data coupling mechanisms for software components that are flexibly distributed among different computing resources.
Collecting the data required for quality prediction within a development team is time-consuming and expensive. An alternative to make predictions using data that crosses from other projects or even other companies. We...
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作者：
Sun, YanchunXin, ChaoInstitute of Software
School of Electronics Engineering and Computer Science Peking University Key Laboratory of High Confidence Software Technologies Ministry of Education Beijing100871 China
MOOCs are popular for online education because of their convenience and excellent educational resources. However, online education for softwareengineering on MOOCs faces many challenges: (1) softwareengineering has ...
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According to the World Health Organization(WHO), it is estimated that approximately 1.3 billion people live with some forms of vision impairment globally, of whom 36 million are blind. Due to their disability, engagin...
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ISBN:
(纸本)9781450371216
According to the World Health Organization(WHO), it is estimated that approximately 1.3 billion people live with some forms of vision impairment globally, of whom 36 million are blind. Due to their disability, engaging these minority into the society is a challenging problem. The recent rise of smart mobile phones provides a new solution by enabling blind users' convenient access to the information and service for understanding the world. Users with vision impairment can adopt the screen reader embedded in the mobile operating systems to read the content of each screen within the app, and use gestures to interact with the phone. However, the prerequisite of using screen readers is that developers have to add natural-language labels to the image-based components when they are developing the app. Unfortunately, more than 77% apps have issues of missing labels, according to our analysis of 10,408 Android apps. Most of these issues are caused by developers' lack of awareness and knowledge in considering the minority. And even if developers want to add the labels to UI components, they may not come up with concise and clear description as most of them are of no visual issues. To overcome these challenges, we develop a deep-learning based model, called LabelDroid, to automatically predict the labels of image-based buttons by learning from large-scale commercial apps in Google Play. The experimental results show that our model can make accurate predictions and the generated labels are of higher quality than that from real Android developers.
Mobile Edge Computing (MEC) is a supplement to traditional cloud computing. Its characteristics are low latency and high reliability, and it will be widely used in the future. However, their dense deployment pattern r...
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ISBN:
(纸本)9781538665657
Mobile Edge Computing (MEC) is a supplement to traditional cloud computing. Its characteristics are low latency and high reliability, and it will be widely used in the future. However, their dense deployment pattern raises a big concern on the system-wide energy consumption, Dynamic power management (DPM) method is an important method to solve energy consumption problems, it saves energy by shutting down servers in the EDC that are idle or have low utilization. In this paper, a DPM method based on reinforcement learning was proposed, it achieves the trade-off between EDC service performance and energy consumption by learning the global optimal dynamic timeout threshold power management strategy by trial and error. Experiments have shown that the proposed method saves no less than 6.35% energy consumption compared to the expert-based method.
In order to study VaR calculations, we studied the issue of volatility forecasting for VaR calculations by using high frequency data. Researchers have studied the issue of volatility forecasting for VaR calculations b...
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ISBN:
(纸本)9780769537054
In order to study VaR calculations, we studied the issue of volatility forecasting for VaR calculations by using high frequency data. Researchers have studied the issue of volatility forecasting for VaR calculations by using realized volatility. However, realized volatility isn't a consistent measure for the true volatility due to microstructure effect of the financial market. As a result, we studied the issue of volatility forecasting for VaR calculations by using realized range-based volatility, which is superior to realized volatility. We do the empirical research by using the high frequency data from the Chinese stock market Shanghai stock market.
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