Automatic Generation of Basis Component Path Coverage for Software Architecture Testing

Architecture-centric development is one of the most promising methods for improving software quality, reducing software cost and raising software productivity. Software architecture research not only focuses on the design phase, but also covers every phase of software life cycle. Software architecture has characteristics different from traditional software, conventional testing methods do not apply directly to software architecture. Basis path testing is a very simple and efficient white-box testing method. Traditional methods generate basis path according to the control flow graph, they are not suitable for generating component path when we detect more software architecture errors. This paper presents a new concept - Basis Component Path (BCP) for C2-style architecture, and proposes a method to generate the BCPs. C2-style architecture is represented by components, connectors, and interfaces, and uses an architecture component interaction graph (CIG) to describe interface connection relationship. We also provide an algorithm to generate BCP set. Experiments apply the proposed method in a typical C2-style architecture and the result shows that the proposed method can generate BCP set which contains as many BCPs as possible efficiently, and it meets the requirements of the basis component path testing

Identifying Important Nodes in Complex Networks Based on Multiattribute Evaluation

Assessing and measuring the importance of nodes in a complex network are of great theoretical and practical significance to improve the robustness of the actual system and to design an efficient system structure. The classical local centrality measures of important nodes only take the number of node neighbors into consideration but ignore the topological relations and interactions among neighbors. Due to the complexity of the algorithm itself, the global centrality measure cannot be applied to the analysis of large-scale complex network. The k-shell decomposition method considers the core node located in the center of the network as the most important node, but it only considers the residual degree and neglects the interaction and topological structure between the node and its neighbors. In order to identify the important nodes efficiently and accurately in the network, this paper proposes a local centrality measurement method based on the topological structure and interaction characteristics of the nodes and their neighbors. On the basis of the k-shell decomposition method, the method we proposed introduces two properties of structure hole and degree centrality, which synthetically considers the nodes and their neighbors’ network location information, topological structure, scale characteristics, and the interaction between different nuclear layers of them. In this paper, selective attacks on four real networks are, respectively, carried out. We make comparative analyses of the averagely descending ratio of network efficiency between our approach and other seven indices. The experimental results show that our approach is valid and feasible

Spatial Distribution and Changes of the Realizable Triple Cropping System in China

Exploiting the full potential of the realizable triple cropping system (RTCS) is one of the most effective methods for increasing land productivity, thus promoting food security. However, insufficient attention is paid to the spatial distribution of the RTCS in China. Here, a method is developed to assess the RTCS in China, considering terrain, climatic conditions, crop climatic-ecological suitability, and the spatial changes in the RTCS between 1951 and 2010. Results indicate that a decrease of 19 Mha was caused by topographic correction, while climate change increased the same area by 14 Mha. Based on crop climatic-ecological conditions, the suitability of the RTCS was indicated for 1068 counties. The boundary of the RTCS moved northward by 100–200 km in the Middle-Lower reaches of the Yangtze River, but southward by approximately 250 km in Yunnan Province. The area of the RTCS is 135 Mha distributed across 775 counties in Southern China. These findings are useful for guiding the policy of cultivated land use in Southern China. The approach can be adopted elsewhere to determine the RTCS for sustainable land use and increasing land productivity

Self-Powered Wind Sensor System for Detecting Wind Speed and Direction Based on a Triboelectric Nanogenerator

The development of the Internet of Things has brought new challenges to the corresponding distributed sensor systems. Self-powered sensors that can perceive and respond to environmental stimuli without an external power supply are highly desirable. In this paper, a self-powered wind sensor system based on an anemometer triboelectric nanogenerator (a-TENG, free-standing mode) and a wind vane triboelectric nanogenerator (v-TENG, single-electrode mode) is proposed for simultaneously detecting wind speed and direction. A soft friction mode is adopted instead of a typical rigid friction for largely enhancing the output performance of the TENG. The design parameters including size, unit central angle, and applied materials are optimized to enhance sensitivity, resolution, and wide measurement scale. The optimized a-TENG could deliver an open-circuit voltage of 88 V and short-circuit current of 6.3 μA, corresponding to a maximum power output of 0.47 mW (wind speed of 6.0 m/s), which is capable of driving electronics for data transmission and storage. The current peak value of the a-TENG signal is used for analyzing wind speed for less energy consumption. Moreover, the output characteristics of a v-TENG are further explored, with six actual operation situations, and the v-TENG delivers fast response to the incoming wind and accurately outputs the wind direction data. As a wind sensor system, wind speed ranging from 2.7 to 8.0 m/s can be well detected (consistent with a commercial sensor) and eight regular directions can be monitored. Therefore, the fabricated wind sensor system has great potential in wireless environmental monitoring applications

Self-Powered Wind Sensor System for Detecting Wind Speed and Direction Based on a Triboelectric Nanogenerator

The development of the Internet of Things has brought new challenges to the corresponding distributed sensor systems. Self-powered sensors that can perceive and respond to environmental stimuli without an external power supply are highly desirable. In this paper, a self-powered wind sensor system based on an anemometer triboelectric nanogenerator (a-TENG, free-standing mode) and a wind vane triboelectric nanogenerator (v-TENG, single-electrode mode) is proposed for simultaneously detecting wind speed and direction. A soft friction mode is adopted instead of a typical rigid friction for largely enhancing the output performance of the TENG. The design parameters including size, unit central angle, and applied materials are optimized to enhance sensitivity, resolution, and wide measurement scale. The optimized a-TENG could deliver an open-circuit voltage of 88 V and short-circuit current of 6.3 μA, corresponding to a maximum power output of 0.47 mW (wind speed of 6.0 m/s), which is capable of driving electronics for data transmission and storage. The current peak value of the a-TENG signal is used for analyzing wind speed for less energy consumption. Moreover, the output characteristics of a v-TENG are further explored, with six actual operation situations, and the v-TENG delivers fast response to the incoming wind and accurately outputs the wind direction data. As a wind sensor system, wind speed ranging from 2.7 to 8.0 m/s can be well detected (consistent with a commercial sensor) and eight regular directions can be monitored. Therefore, the fabricated wind sensor system has great potential in wireless environmental monitoring applications

Self-Powered Wind Sensor System for Detecting Wind Speed and Direction Based on a Triboelectric Nanogenerator

The development of the Internet of Things has brought new challenges to the corresponding distributed sensor systems. Self-powered sensors that can perceive and respond to environmental stimuli without an external power supply are highly desirable. In this paper, a self-powered wind sensor system based on an anemometer triboelectric nanogenerator (a-TENG, free-standing mode) and a wind vane triboelectric nanogenerator (v-TENG, single-electrode mode) is proposed for simultaneously detecting wind speed and direction. A soft friction mode is adopted instead of a typical rigid friction for largely enhancing the output performance of the TENG. The design parameters including size, unit central angle, and applied materials are optimized to enhance sensitivity, resolution, and wide measurement scale. The optimized a-TENG could deliver an open-circuit voltage of 88 V and short-circuit current of 6.3 μA, corresponding to a maximum power output of 0.47 mW (wind speed of 6.0 m/s), which is capable of driving electronics for data transmission and storage. The current peak value of the a-TENG signal is used for analyzing wind speed for less energy consumption. Moreover, the output characteristics of a v-TENG are further explored, with six actual operation situations, and the v-TENG delivers fast response to the incoming wind and accurately outputs the wind direction data. As a wind sensor system, wind speed ranging from 2.7 to 8.0 m/s can be well detected (consistent with a commercial sensor) and eight regular directions can be monitored. Therefore, the fabricated wind sensor system has great potential in wireless environmental monitoring applications

Self-Powered Wind Sensor System for Detecting Wind Speed and Direction Based on a Triboelectric Nanogenerator

The development of the Internet of Things has brought new challenges to the corresponding distributed sensor systems. Self-powered sensors that can perceive and respond to environmental stimuli without an external power supply are highly desirable. In this paper, a self-powered wind sensor system based on an anemometer triboelectric nanogenerator (a-TENG, free-standing mode) and a wind vane triboelectric nanogenerator (v-TENG, single-electrode mode) is proposed for simultaneously detecting wind speed and direction. A soft friction mode is adopted instead of a typical rigid friction for largely enhancing the output performance of the TENG. The design parameters including size, unit central angle, and applied materials are optimized to enhance sensitivity, resolution, and wide measurement scale. The optimized a-TENG could deliver an open-circuit voltage of 88 V and short-circuit current of 6.3 μA, corresponding to a maximum power output of 0.47 mW (wind speed of 6.0 m/s), which is capable of driving electronics for data transmission and storage. The current peak value of the a-TENG signal is used for analyzing wind speed for less energy consumption. Moreover, the output characteristics of a v-TENG are further explored, with six actual operation situations, and the v-TENG delivers fast response to the incoming wind and accurately outputs the wind direction data. As a wind sensor system, wind speed ranging from 2.7 to 8.0 m/s can be well detected (consistent with a commercial sensor) and eight regular directions can be monitored. Therefore, the fabricated wind sensor system has great potential in wireless environmental monitoring applications