An Approach to Detect Structural Development Defects in Object-Oriented Programs

Structural development defects essentially refer to code structure that violates object-oriented design principles. They make program maintenance challenging and deteriorate software quality over time. Various detection approaches, ranging from traditional heuristic algorithms to machine learning methods, are used to identify these defects. Ensemble learning methods have strengthened the detection of these defects. However, existing approaches do not simultaneously exploit the capabilities of extracting relevant features from pre-trained models and the performance of neural networks for the classification task. Therefore, our goal has been to design a model that combines a pre-trained model to extract relevant features from code excerpts through transfer learning and a bagging method with a base estimator, a dense neural network, for defect classification. To achieve this, we composed multiple samples of the same size with replacements from the imbalanced dataset MLCQ1. For all the samples, we used the CodeT5-small variant to extract features and trained a bagging method with the neural network Roberta Classification Head to classify defects based on these features. We then compared this model to RandomForest, one of the ensemble methods that yields good results. Our experiments showed that the number of base estimators to use for bagging depends on the defect to be detected. Next, we observed that it was not necessary to use a data balancing technique with our model when the imbalance rate was 23%. Finally, for blob detection, RandomForest had a median MCC value of 0.36 compared to 0.12 for our method. However, our method was predominant in Long Method detection with a median MCC value of 0.53 compared to 0.42 for RandomForest. These results suggest that the performance of ensemble methods in detecting structural development defects is dependent on specific defects.

“ASP.NET应用开发技术”课程思政探索与实践

作为软件工程专业的核心技术课程,“ASP.NET应用开发技术”在2022年被立项为河南中医药大学(以下简称“我校”)的课程思政样板课。教学团队始终坚持“知识传授与价值引领”相结合的原则进行课程建设,分别从课程内容、课程资源、教学活动、日常管理等方面对思政元素进行了深入挖掘,以全面融入人文素养,进而引领学生树立科学的世界观和人生观。

基于ASP-SAC算法的列车自动驾驶速度控制

随着经济建设的绿色转型以及人工智能的快速发展,城市轨道交通已成为居民日常出行的重要方式,在保障安全性、高效性和准点性的前提下,列车运行的节能性和舒适性需求也越来越被关注。合理的运行策略能够有效实现多种目标需求下的列车自动驾驶速度控制,强化学习作为一种智能决策方法,能够有效解决这一控制问题。首先,通过综合分析技术、安全性和乘客体验等方面的因素,基于专家经验动作划分和状态信息熵将软演员-评论家(SAC)改进为动作状态经验优先软演员-评论家(ASP-SAC)方法,用于研究列车自动驾驶速度控制问题。其次,将问题马尔可夫形式化,搭建了列车运行环境,确定了状态空间、动作空间以及基于目标控制的奖励函数。最后,以北京地铁亦庄线的一段区间数据为例进行试验,对ASP-SAC方法进行验证并与其他一些算法在相同环境下进行性能优劣比较。研究结果表明:该方法对于多目标控制需求下的列车自动驾驶速度控制问题具有可行性,与未改进前相比算法效率提高22.73%,与PPO算法相比提高29.17%,改进效果良好。同时,列车运行时在安全性、舒适性无误的情况下,准时性、精确性和节能性都强于SAC、DQN、PPO以及PID算法,其中能耗分别减少3.64%、5.62%、4.38%、7.35%,控制效果良好。此外,该方法亦具备鲁棒性,在列车自动驾驶速度控制方面具有一定的优越性和可参考性。

基于ASP.NET的在线音乐网站设计

拥有独立服务器的音乐网站,由于网络广告、版权等问题,增加了用户的开支成本。研究一种免费、方便使用的音乐分享网站显得十分必要。本文基于一种脚本语言(active server page.NET,ASP.NET)技术设计了在线音乐网站。首先分析了所用的关键技术和功能需求,其次完成了数据库的设计,最后实现了注册登录功能、界面设计、播放音乐、后台管理模块、测试模块等设计。经测试,该音乐分享网站设计基本达到了预期的目标。

基于ASP.NET技术、量子遗传算法的物流调度管理系统设计与实现

随着大数据及云计算技术、人工智能技术在国内的迅猛发展,物流行业也广泛应用ASP.NET软件开发技术、B/S(browser/server)系统结构、SQL Server数据库等软硬件开发出符合物流企业车辆运输调度、物流信息管理的数字化服务系统。基于此,利用Web应用程序的ASP.NET分布式框架、B/S结构、SQL Server关系型数据库、IIS8服务器、COM组件等软硬件工具,建构起可用于物流企业客户订单管理、出库/入库管理、车辆调度管理的信息化服务系统,运用量子遗传算法建立物流企业的配送车辆路径规划模型、车辆优化调度寻优方案,进而提升物流企业配送车辆调度、物流信息资源管理的效率与质量。

Exploration on 5E Teaching Principle-based Education for the Object-oriented Software Construction Course

Most current object-oriented programming courses offered by domestic colleges and universities generally focus on the object-oriented programming language itself,i.e.,the programming grammar of the language,but ignore the design pattern.However,design patterns are essential to software engineering because they can solve common problems in software design and improve code reuse,readability,extensibility,and reliability.Our Object-oriented Software Construction Course is creative since it aims at cultivating students’object-oriented thinking as well as basic abilities required to construct high-quality,object-oriented software.Specifically,we exploit the 5E teaching principle during the education of this course,and present the whole pipeline in the paper.We also provide one case of the factory pattern to further demonstrate the implementation of the 5E teaching principle in the course.The effect of the 5E teaching principle has also been demonstrated.

An Edge-assisted, Object-oriented Random Forest Approach for Refined Extraction of Tea Plantations Using Multi-temporal Sentinel-2 and High-resolution Gaofen-2 Imagery

As a consumed and influential natural plant beverage,tea is widely planted in subtropical and tropical areas all over the world.Affected by(sub)tropical climate characteristics,the underlying surface of the tea distribution area is extremely complex,with a variety of vegetation types.In addition,tea distribution is scattered and fragmentized in most of China.Therefore,it is difficult to obtain accurate tea information based on coarse resolution remote sensing data and existing feature extraction methods.This study proposed a boundary-enhanced,object-oriented random forest method on the basis of high-resolution GF-2 and multi-temporal Sentinel-2 data.This method uses multispectral indexes,textures,vegetable indices,and variation characteristics of time-series NDVI from the multi-temporal Sentinel-2 imageries to obtain abundant features related to the growth of tea plantations.To reduce feature redundancy and computation time,the feature elimination algorithm based on Mean Decrease Accuracy(MDA)was used to generate the optimal feature set.Considering the serious boundary inconsistency problem caused by the complex and fragmented land cover types,high resolution GF-2 image was segmented based on the MultiResolution Segmentation(MRS)algorithm to assist the segmentation of Sentinel-2,which contributes to delineating meaningful objects and enhancing the reliability of the boundary for tea plantations.Finally,the object-oriented random forest method was utilized to extract the tea information based on the optimal feature combination in the Jingmai Mountain,Yunnan Province.The resulting tea plantation map had high accuracy,with a 95.38%overall accuracy and 0.91 kappa coefficient.We conclude that the proposed method is effective for mapping tea plantations in high heterogeneity mountainous areas and has the potential for mapping tea plantations in large areas.

Object-Oriented Modeling of the Variation of Acceleration and Deceleration Characteristics in Relation to Speed Bands for Railway Vehicles

Automated operation and artificial intelligence technology have become essential for ensuring the safety, efficiency, and punctuality of railways, with applications such as ATO (Automatic Train Operation). In this study, the authors propose a method to efficiently simulate the kinematic characteristics of railroad vehicles depending on their speed zone. They utilized the function overloading function supported by a programming language and applied the fourth-order Lunge-Kutta method for dynamic simulation. By constructing an object model, the authors calculated vehicle characteristics and TPS and compared them with actual values, verifying that the developed model represents the real-life vehicle characteristics accurately. The study highlights potential improvements in automated driving and energy consumption optimization in the railway industry.

基于ASP.NET MVC架构在精炼炉RH二级客户端设计与实现

为了实现基于B/S框架的精炼炉RH二级客户端系统,采用基于.NET平台的ASP.NET MVC的Web开发框架,使用了MVC(Model-View-Controller)三层模式,利用基于ADO.NET为基础的Entity Framework对象关系映射器(简称ORM)框架技术,与数据库之间进行交互,Web界面采用Razor视图引擎,使得代码开发更加简洁、规范。基于MVC分层模式开发的精炼炉RH二级客户端系统,具有较好的可复用性、可扩展性,并且易于部署和维护。

基于UML和ASP的艺术类考试成绩查询系统设计与实现

本文采用统一建模语言UML对考试成绩查询系统进行建模,设计了基于UML的艺术类考试成绩查询系统模型,利用ASP技术实现考试成绩查询系统,大大提高艺术类考试成绩管理工作的效率和质量。

基于ASP.NET的高校毕业论文管理系统设计与实现

针对高校毕业论文传统管理方法存在的问题,以昆明幼儿师范高等专科学校为例,分析了毕业论文管理上的难点,并提出了相应的解决方案。使用用例图设计了系统的主要功能,使用状态图设计了系统的主要流程,同时构建了系统数据库。使用ASP.NET语言实现了高校毕业论文管理系统中指导教师出题和学院审核模块、上传开题报告和论文模块、学院分配评审教师模块和教师审核论文模块。系统的应用能够规范高校毕业论文的管理,提高工作效率。

基于ASP.NET的藏文文献数字化建设平台

藏文文献作为藏学研究的珍贵材料,具有极高的文物价值,传承了藏族人民的历史、文化、传统和智慧。然而,由于保存条件、传承方式、语言障碍等诸多因素,藏文文献的保护和传承面临许多困难和挑战。为了更好地保护和传承藏文文献,本文设计了数字化建设平台,方便人们在网络上进行查阅、学习和研究。藏文文献数字化建设的背景是多种因素共同作用的结果。

基于Asp.Net高速公路桥梁养护管理系统设计与实现

以高速公路桥梁养护为研究对象,介绍了基于Asp.Net的高速公路桥梁养护管理系统的设计与实现,旨在通过信息化手段提高桥梁养护工作的效率和准确性。系统包括桥梁信息录入、查询、更新和删除功能,并涵盖用户管理、桥梁信息管理、养护计划管理和报告生成等模块。通过实际应用案例,验证了该系统在提升养护管理水平和保障桥梁安全方面的有效性,此举有效地为相关部门提供了基于科学的决策支持,助力其做出更为精准和合理的决策。

Multi-Plate Microbial Monitoring Terminal Based on Raspberry Pi 4B

We utilized Raspberry Pi 4B to develop a microbial monitoring system to simplify the microbial image-capturing process and facilitate the informatization of microbial observation results.The Raspberry Pi 4B firmware,developed under Python on the Linux platform,achieves sum verification of serial data,file upload based on TCP protocol,control of sequence light source and light valve,real-time self-test based on multithreading,and an experiment-oriented file management method.The system demonstrated improved code logic,scheduling,exception handling,and code readability.

基于ASP.NET的高职院校毕业设计选题系统设计

针对高职院校毕业设计选题现状,文章设计了基于ASP.NET的毕业设计选题系统。该系统采用浏览器/服务器(Browser/Server,B/S)构架,使用SQL Server数据库进行开发,以模块化、功能化为原则,包括管理员模块、教师模块和学生模块,经过调试和验证,实现了系统要求的全部功能。

基于ASP.NET的C语言练习系统的设计与实现

当前,网络技术迅速发展,在线系统的应用逐渐普及。然而,一些高校在C语言程序设计课后练习方面仍采用传统的人工出题和批改方式,效率较低。为了提高学生的学习效率并减轻教师的批改压力,文章开发了一款基于ASP.NET的C语言练习系统。该系统运用了HTML、Ajax等技术,并采用SQLServer数据库设计了在线练习系统网站。该系统的核心功能在于教师能够通过后台管理学生信息、编辑和添加题目、查看学生成绩及题目练习情况。经过严格的测试,该系统运行稳定,能显著提高学生的学习效率,减轻教师的批改压力。

基于ASP.NET MVC框架的绿色建筑协会网站的设计与实现

基于ASP.NET MVC框架、Bootstrap前端框架和MySQL数据库等技术,研究某市绿色建筑与建筑节能行业协会网站的设计与实现。通过分析协会网站的需求,设计其整体架构、数据模型和功能实现,利用Bootstrap前端开发框架,采用响应式设计,确保网站能够在不同设备上自适应显示。

OBJECT-ORIENTED IMPLEMENTATION OF EXPERT SYSTEMS FOR ENGINE LUBRICATING OIL INSPECTION

The inspection of engine lubricating oil can give an indication of the internal condition of an engine. By means of the Object-Oriented Programming (OOP), an expert system is developed in this paper to computerize the inspection. The traditional components of an expert system, such us knowledge base, inference engine and user interface are reconstructed and integrated, based on the Microsoft Foundation Class (MFC) library. To testify the expert system, an inspection example is given at the end of this paper.

Meta-analysis of potentially confounding effect of class size on associations between object-oriented metrics and maintainability

This paper uses three size metrics,which are collectable during the design phase,to analyze the potentially confounding effect of class size on the associations between object-oriented（OO）metrics and maintainability.To draw as many general conclusions as possible,the confounding effect of class size is analyzed on 127 C＋＋ systems and 113 Java systems.For each OO metric,the indirect effect that represents the distortion of the association caused by class size and its variance for individual systems is first computed.Then,a statistical meta-analysis technique is used to compute the average indirect effect over all the systems and to determine if it is significantly different from zero.The experimental results show that the confounding effects of class size on the associations between OO metrics and maintainability generally exist,regardless of whatever size metric is used.Therefore,empirical studies validating OO metrics on maintainability should consider class size as a confounding variable.

REALIZATION OF OBJECT-ORIENTED RULE-TYPE EXPERT SYSTEM TEMPLATE

Expert systems (ESs) are being increasingly applied to the fault diagnosis of engines. Based on the idea of ES template (EST), an object-oriented rule-type EST is emphatically studied on such aspects as the object-oriented knowledge representation, the heuristic inference engine with an improved depth-first search (DFS) and the graphical user interface. A diagnositic ES instance for debris on magnetic chip detectors (MCDs) is then created with the EST. The spot running shows that the rule-type EST enhances the abilities of knowledge representation and heuristic inference, and breaks a new way for the rapid construction and implementation of ES.