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关键词： 程序设计能力   数据结构   实践教学  

摘要： 数据结构是计算机相关专业的核心课程,该课程知识点相对抽象,涉及的算法复杂且多样。传统的教学方式往往导致理论学习和实践环节的不匹配,从而无法满足该课程的教学需要,致使学生的程序设计能力提升有限。基于数据结构教学的现状和存在的问题,结合课程特点,通过优化改革课程教学,提出了有效的教学策略应用于数据结构课程的教学,实践证明该策略效果良好,学生的程序设计能力得到了较大的提升。

关键词： 翻转课堂   大学实验教学   验收通过率  

摘要： 针对计算机学院学生专业课程多,学习难度大的特点,武汉科技大学计算机学院将翻转课堂引入实验教学,进行一系列的实验教学改革探索。在实践探索中,教师根据学生的反馈,对教学设计不断优化,通过先进的教育手段,培养学生的思辨能力、探索精神,并增强学生的知识内化力和社会竞争力。

关键词： 数据结构   思政教育   课程设计  

摘要： 计算机专业的专业课程,理论性相对较强,如何将理论与实际案例相结合,同时恰当地融入思政元素,是近年来课程教学研究探索的热点之一。通过查阅相关资料,结合新时代背景下课程思政在教学中的具体要求,以计算机专业的数据结构课程为例,梳理这门课程的知识架构与知识点,将思政元素融入专业课程,以期帮助学生丰富学识,增长见识,塑造品格,提高其综合素质。

关键词： Dependable software   Soft-error   Error-masking   Reliable data-structures   Fault injection  

摘要： Decreasing the scale of transistors and their voltages and exponential increase in the transistor counts have made the nowadays digital integrated circuits more susceptible to transient hardware errors (soft errors). One of the interesting features of software systems is that a considerable number of soft errors are inherently masked at software level. The likelihood of error masking (error deration) in the software may be influenced by the Algorithm, data structures and programming paradigms used in the software. One of the main research questions in this field of study is that how can software reliability be improved against soft errors without external redundancy and only by selecting appropriate software structures. This paper investigates the inherent effects of the underlying data structures on the rate of error deration and program reliability. To attain this goal, five different benchmark programs were implemented by four different data structures, i.e. Array,Binary-search Tree,One-way linked listandTwo-way linked list;profiling experiments were performed on the benchmarks to identify those features of the data structures which affect the rate of error-deration. Then, in order to quantify and examine the inherent reliability of the data structures, about 5,600,000 faults were injected into the benchmark programs. The results show that about 53.95% of faults in the Array based programs are masked;this figure for Binary-search tree, One-way linked list and Two-way linked list are 40.16%, 44.02% and 42.73%, respectively. We found that Array and BST as two different data structures have the highest and lowest inherent reliability respectively. These findings enable the software developers to select the most reliable data structures for developing reliable programs without external redundancy.

关键词： Data structure invariants   Machine learning   Korat   Learnability  

摘要： Data structure properties are important for many testing and analysis tasks. For example, model checkers use these properties to find program faults. These properties are often written manually which can be error prone and lead to false alarms. This paper presents the results of controlled experiments performed using existing machine learning (ML) models on various data structures. These data structures are dynamic and reside on the program heap. We use ten data structure subjects and ten ML models to evaluate the learnability of data structure properties. The study reveals five key findings. One, most of the ML models perform well in learning data structure properties, but some of the ML models such as quadratic discriminant analysis and Gaussian naive Bayes are not suitable for learning data structure properties. Two, most of the ML models have high performance even when trained on just 1% of data samples. Three, certain data structure properties such as binary heap and red black tree are more learnable than others. Four, there are no significant differences between the learnability of varied-size (i.e., up to a certain size) and fixed-size data structures. Five, there can be significant differences in performance based on the encoding used. These findings show that using machine learning models to learn data structure properties is very promising. We believe that these properties, once learned, can be used to provide a run-time check to see whether a program state at a particular point satisfies the learned property. Learned properties can also be employed in the future to automate static and dynamic analysis, which would enhance software testing and verification techniques.

关键词： Algorithms   Data structures   Spatial databases   Computational geometry   Compact data structures   Convex hull  

摘要： In this paper, we present two algorithms to obtain the convex hull of a set of points that are stored in the compact data structure called k(2)-tree. This problem consists in given a set of points P in the Euclidean space obtaining the smallest convex region (polygon) containing P. Traditional algorithms to compute the convex hull do not scale well for large databases, such as spatial databases, since the data does not reside in main memory. We use the k(2)-tree compact data structure to represent, in main memory, efficiently a binary adjacency matrix representing points over a 2D space. This structure allows an efficient navigation in a compressed form. The experimentations performed over synthetical and real data show that our proposed algorithms are more efficient. In fact they perform over four order of magnitude compared with algorithms with time complexity of O(n log n).

关键词： FM-BIM integration   Linked data   Building automation systems  

摘要： Buildings Automation Systems (BAS) are ubiquitous in contemporary buildings, both monitoring building conditions and managing the building system control points. At present, these controls are prescriptive and predetermined by the design team, rather than responsive to actual building performance. These are further limited by prescribed logic, possess only rudimentary visualizations, and lack broader system integration capabilities. Advances in machine learning, edge analytics, data management systems, and Facility Management-enabled Building Information Models (FM-BIMs) permit a novel approach: cloud-hosted building management. This paper presents an integration technique for mapping the data from a building Internet of Things (IoT) sensor network to an FM-BIM. The sensor data naming convention and time-series analysis strategies integrated into the data structure are discussed and presented, including the use of a 3D nested list to permit time-series data to be mapped to the FM-BIM and readily visualized. The developed approach is presented through a case study describing the scalability of the approach to integrate a building BAS system with a BIM. The resultant data structure and key visualizations are presented to demonstrate the value of this approach, which permits the end user to select the desired timeframe for visualization and readily step through the spatio-temporal building performance data.

标准号: GB/T 20818.12-2020

标准号: GB/T 20818.21-2020

摘要： 本部分规定了：通用数据字典（CDD）中集合了各类自动阀，包括控制阀、自动开/关阀和过程调节器的特性描述；符合IEC 61987-10的最终控制元件的操作属性列表（OLOP）和设备属性列表（DLOP）的通用结构。