Detection of design patterns by combining static and dynamic analyses

Design patterns are micro architectures that have proved to be reliable, robust and easy to implement. Detecting design pattern from source code of object-oriented system can help a designer, a developer or a maintainer to understand the software system. In this paper, a new method is provided which can detect design patterns from source code combining both static and dynamic analysis. To acquire the run-time dynamic information of software systems, a code instrumentation method is adopted. At the same time, all static and dynamic information is presented in UML diagrams format. The pattern detection process and its detection results are visual and interactive. This method is tested on a call center and a traffic simulation system. Experimental results prove that the method is effective in design patterns detection.

Matching authority and VGI road networks using an extended node-based matching algorithm

The amount of volunteered geographic information(VGI)has increased over the past decade,and several studies have been conducted to evaluate the quality of VGI data.In this study,we evaluate the completeness of the road network in the VGI data set OpenStreetMap(OSM).The evaluation is based on an accurate and efficient network-matching algorithm.The study begins with a comparison of the two main strategies for network matching:segment-based and nodebased matching.The comparison shows that the result quality is comparable for the two strategies,but the node-based result is considerably more computationally efficient.Therefore,we improve the accuracy of node-based algorithm by handling topological relationships and detecting patterns of complicated network components.Finally,we conduct a case study on the extended node-based algorithm in which we match OSM to the Swedish National Road Database(NVDB)in Scania,Sweden.The case study reveals that OSM has a completeness of 87%in the urban areas and 69%in the rural areas of Scania.The accuracy of the matching process is approximately 95%.The conclusion is that the extended node-based algorithm is sufficiently accurate and efficient for conducting surveys of the quality of OSM and other VGI road data sets in large geographic regions.

Data-Driven Approaches for Spatio-Temporal Analysis:A Survey of the State-of-the-Arts

With the advancement of telecommunications,sensor networks,crowd sourcing,and remote sensing technology in present days,there has been a tremendous growth in the volume of data having both spatial and temporal references.This huge volume of available spatio-temporal(ST)data along with the recent development of machine learning and computational intelligence techniques has incited the current research concerns in developing various data-driven models for extracting useful and interesting patterns,relationships,and knowledge embedded in such large ST datasets.In this survey,we provide a structured and systematic overview of the research on data-driven approaches for spatio-temporal data analysis.The focus is on outlining various state-of-the-art spatio-temporal data mining techniques,and their applications in various domains.We start with a brief overview of spatio-temporal data and various challenges in analyzing such data,and conclude by listing the current trends and future scopes of research in this multi-disciplinary area.Compared with other relevant surveys,this paper provides a comprehensive coverage of the techniques from both computational/methodological and application perspectives.We anticipate that the present survey will help in better understanding various directions in which research has been conducted to explore data-driven modeling for analyzing spatio-temporal data.