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.

高效液相色谱法测定菜用大豆鲜籽粒VC含量

为建立菜用大豆鲜籽粒VC含量的高效液相色谱测定方法,采用30 g/L偏磷酸溶液低温提取样品后,进行高效液相色谱分析,色谱柱为Agilent Eclipse XDB-C18柱(4.6 mm×250 mm×5μm),流动相为1 g/L偏磷酸溶液∶甲醇=96∶4(V/V),流速0.8 mL/min,检测波长243 nm,柱温25℃,以保留时间定性,外标法定量。结果表明:VC质量浓度范围为2~40μg/mL时,其与峰面积呈良好的线性关系(R2=1.000),平均加标回收率为108.14%,相对标准偏差为1.70%。所建立的方法操作简便,灵敏度高,分离度好,结果准确,重复性也比较好,适用于测定菜用大豆鲜籽粒VC含量,为优质菜用大豆的选育和生产提供技术支持。

Vc对壳聚糖-纳米硒体系制备后稳定过程中物化性质的影响

以壳聚糖(chitosan,CS)为模板,通过抗坏血酸(ascorbic acid,VC)原位还原亚硒酸法制备壳聚糖-纳米硒体系(chitosan-selenium nanoparticle,CS-SeNPs)现已得到广泛研究,但是Vc在该体系中除还原亚硒酸外,也可能对体系制备后的稳定过程产生影响。以不同分子量(3 kDa和200 kDa)的壳聚糖为模板分别制备CS(l)-SeNPs以及CS(h)-SeNPs,首先表征其微观形貌及化学结构,并在稳定不同天数进行透除Vc处理,测定不同CS-SeNPs的颗粒粒径、ζ-电位、微观形貌及元素组成的变化;进一步借助X-射线衍射(XRD)、傅里叶红外光谱(FTIR)等分析Vc对CS-SeNPs制备后稳定过程中Se的晶型结构及体系化学结构的变化。结果表明:在第1天透除Vc,相比于未透除组不同CS-SeNPs的颗粒粒径均增加且随着稳定时间的延长未发生改变,ζ-电位逐渐降低;稳定14天后,Vc的去除仍造成CS(l)-SeNPs的聚集,而对CS(h)-SeNPs影响较小。除此之外,Vc在CS-SeNPs制备后稳定初期可通过影响体系中糖链分子O-H、N-H氢键的作用,进而影响体系的化学结构及Se的晶形结构。本研究为Vc或其他还原性小分子原位法制备纳米颗粒后稳定过程的解析提供新思路。

基于Fisher判别分析可分性信息融合的马铃薯VC含量高光谱检测方法

为提高马铃薯VC含量检测结果的准确性和可靠性,提出一种基于Fisher判别分析(Fisher discriminant analysis,FDA)可分性数据融合的检测模型输入变量构建方法。首先,利用高光谱成像技术采集200个马铃薯的高光谱信息,通过对比6种预处理方法和原始数据的建模结果,确定多元散射校正为光谱数据的预处理方法;其次,采用竞争性自适应重加权采样(competitive adaptive reweighted sampling,CARS)、连续投影算法(successive projections algorithm,SPA)及CARS-SPA组合算法3种方法提取相应特征波长,通过对比分析最终确定34个有效特征波长;然后,将有效特征波长进行FDA可分性数据融合,根据融合的新变量对样本间差异性判别能力的大小进行筛选,确定构建检测模型的输入变量;最后,分别对FDA融合前后筛选的变量建立偏最小二乘模型和反向传播神经网络(back propagation neural network,BPNN)模型,并对检测结果进行对比分析。结果表明,将CARS算法提取的34个特征波长进行FDA融合,采用前3个融合变量作为构建检测模型的输入变量时,其所建BPNN模型的相关系数由0.9726提高至0.9990,均方根误差由0.7723降低至0.1727,不仅能够极大地降低数据分析维度,而且能够提高检测结果的准确性。因此,基于FDA可分性数据融合构建检测模型输入变量可以提高马铃薯VC含量检测结果的准确性。

液相色谱法测定特殊医学用途婴幼儿配方食品中VC

建立液相色谱法检测特殊医学用途婴幼儿配方食品中VC含量的分析方法。样品还原处理后,经HLB固相萃取柱净化、微孔滤膜过滤后进行亲水作用液相色谱法测定,外标法定量,对检测方法进行验证。结果表明:在质量浓度为0~50μg/mL范围内其线性相关系数≥0.999,定量限为3.0 mg/100 g,加标回收率为95.2%~102.8%,相对标准偏差为1.22%~3.62%;该方法具有操作简单、结果准确和重复性好等特点,适用于特殊医学用途婴幼儿配方食品中VC含量的测定。

黔产刺梨VC的提取及纯化工艺研究

以黔产刺梨汁为原料,采用95%乙醇提取制备刺梨维生素C(VC)粗提液,再经HPD100大孔树脂分离纯化,并以刺梨VC的损失率为指标进行了刺梨VC提取物的浓缩方法、干燥方法筛选,发现减压浓缩法、真空干燥法更加适用于刺梨VC提取物制备;本文所建立的刺梨VC提取物的制备方法简便、有效,可为培育“贵州刺梨”优质产品奠定基础,助力贵州刺梨产业发展。

WC–xVC复合粉的制备及高含量VC对WC–Co基硬质合金微观结构和力学性能的影响

采用两步碳热还原法合成了WC–xVC复合粉,并以此为原料通过真空烧结法制备了不同Co含量(6%和10%,质量分数)的WC–Co–VC硬质合金,研究了烧结温度(1420℃、1440℃和1460℃)对硬质合金致密化过程的影响,分析了Co和VC含量对WC晶粒尺寸以及硬质合金维氏硬度和断裂韧性的影响。结果表明,随着烧结温度的升高,合金的相对密度增大,当烧结温度为1460℃时,所有合金试样的相对密度均大于98.5%。此外,随着VC含量的增加,WC的平均晶粒尺寸减小,这导致样品的硬度提高,断裂韧性降低。当VC质量分数为6%时,WC–6Co硬质合金和WC–10Co硬质合金的硬度均达到最大值,分别为HV301941和HV301838。在烧结温度和VC含量一定的情况下,试样的断裂韧性随着Co含量的增加而增加,试样的硬度随着Co含量的增加而减小。

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.

OBJECT-ORIENTED FINITE ELEMENT ANALYSIS AND PROGRAMMING IN VC++

The design of finite element analysis program using object-oriented programming (OOP) techniques is presented. The objects, classes and the subclasses used in the programming are explained. The system of classes library of finite element analysis program and Windows-type Graphical User Interfaces by VC + + and its MFC are developed. The reliability, reusability and extensibility of program are enhanced. It is a reference to develop the large-scale, versatile and powerful systems of object-oriented finite element software.

氧化三甲胺对皮肤成纤维细胞氧化损伤作用的影响及VC对其干预作用

本实验利用氧化三甲胺(trimethylamine oxide,TMAO)处理人皮肤成纤维细胞(human skin fibroblasts,HSF),通过分析抗氧化性指标、炎症因子分泌水平、细胞胶原蛋白和基质金属蛋白酶水平以及相关基因在mRNA水平的变化规律,研究TMAO对HSF细胞氧化损伤的影响,阐释其对皮肤细胞衰老的作用。结果表明,TMAO处理能够显著升高HSF细胞内活性氧和丙二醛水平(P<0.05),并显著降低还原型谷胱甘肽含量、超氧化物歧化酶活力和总抗氧化能力(P<0.05)。通过逆转录实时荧光定量聚合酶链反应和酶联免疫吸附检测发现,TMAO处理能显著升高炎症因子肿瘤坏死因子-α、白介素-6、基质金属蛋白酶-1的mRNA水平,并降低胶原合成基因和诱导型一氧化氮氧合酶的mRNA转录水平,同时蛋白质免疫印迹分析结果表明p-p65蛋白的表达水平显著增加(P<0.05)。而VC能够干预TMAO诱导的HSF细胞氧化应激,减轻炎症和减少胶原流失。综上,TMAO对HSF细胞产生氧化应激,可能介导激活核因子κB(nuclear factor kappa-B,NF-κB)信号通路,促进HSF细胞NF-κB磷酸化,诱导炎症反应,并降低胶原合成和加速胶原降解,从而可能促进皮肤细胞衰老。

基于VC-OTN的SDH网络改造方案研究

文章详细介绍了VC-OTN技术,并基于VC-OTN的特性和技术优势,提出了一种基于VC-OTN的SDH网络改造方案,该方案可同步实现OTN网络的广域覆盖与SDH核心汇聚层整体退网的网络演进目标,具有一定实用价值。

基于VCS(VM0018)方法学的绿色社区零碳化实施策略研究

社区是城市低碳发展的基础,也是实现建筑业可持续发展的平台和空间载体。在双碳背景下,充分借助碳减排项目方法学赋能社区绿色低碳发展,可以更科学有效地降低社区碳排放强度,实现社区绿色、低碳、零碳、可持续发展。该文基于VCS(Verified Carbon Standard核证碳标准)项目方法学,对绿色社区零碳化实施策略进行创新研究,分析了社区零碳化特征、意义,并对VM0018方法学下的社区零碳化实施及碳资产开发进行了路径分析和框架搭建,提出了绿色社区碳资产展望,为进一步量化绿色社区建设提供参考。

基于VC的测绘空间交会程序设计与实现

文章从空间交会的角度出发,详细介绍了前方交会、侧边交会和后方交会的数学模型及原理。在此基础上,使用VC++编程设计了主界面和3种不同类型的空间交会计算界面,实现了可视化的交互式操作。在满足一定精度要求的前提下,显著提高了工作效率。

基于MIoT.VC软件的生产单元数字化改造与仿真

以轴类产品生产单元为对象,提出了一种基于工业仿真软件(MIoT.VC)的生产单元数字化改造与仿真设计方法。该生产单元由装配单元和仓储单元组成,同时配置AMR、充电桩,安全围栏,SCADA看板等外围装置。在MIoT.VC软件中导入生产单元三维模型进行布局设计,对生产单元中的各模块设置对象的物理属性并进行仿真工艺设计,最后对服务器进行通信设置。在此基础上,利用虚拟控制器对生产单元进行仿真调试,可以优化整体运行逻辑与节拍,并对生产单元布局进行优化,与真实生产单元的控制器建立通讯后,可以实现数字孪生,实现持续的监测和分析。

做一家VC讨厌的赚钱公司

在无锡,藏着一匹软件行业的科技黑马——帆软软件。这家公司带有鲜明的标签:不融资、不上市,多个产品线市场占有率第一、利润共享。我愿称帆软为科技界的“胖东来”。与此同时,它的创始团队十分神秘。除了必要的曝光,网上几乎找不到他们的信息。也是因为他们的神秘与连年增长的业绩,这家公司成了很多VC的“意难平”。那么这家公司究竟为何如此排斥资本?又是靠着怎样的管理哲学,在软件寒冬期,依旧保持高增长?

基于StarGAN-VC的语音风格转换技术

文章基于星型生成式对抗网络-语音转换(Star Generative Adversarial Networks-Voice Conversion,StarGAN-VC)模型,研究了一种先进的语音风格转换技术,旨在实现对语音信号的高效转换。首先,详细阐述了基于StarGAN-VC的语音转换方法的基本原理。其次,深入研究特征提取和基频转换方法,以及StarGAN-VC模型的数学原理。最后,通过在VCC2018数据集上的实验,验证了该方法的性能。实验结果表明,该方法在频谱包络相似度和基频准确度等指标上均取得了令人满意的效果。

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.