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.

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.

A Comprehensive Review on Pixel Oriented and Object Oriented Methods for Information Extraction from Remotely Sensed Satellite Images with a Special Emphasis on Cryospheric Applications

Image classification is one of the most basic operations of digital image processing. The present review focuses on the strengths and weaknesses of traditional pixel-based classification (PBC) and the advances of object-oriented classification (OOC) algorithms employed for the extraction of information from remotely sensed satellite imageries. The state-of-the-art classifiers are reviewed for their potential usage in urban remote sensing (RS), with a special focus on cryospheric applications. Generally, classifiers for information extraction can be divided into three catalogues: 1) based on the type of learning (supervised and unsupervised), 2) based on assumptions on data distribution (parametric and non-parametric) and, 3) based on the number of outputs for each spatial unit (hard and soft). The classification methods are broadly based on the PBC or the OOC approaches. Both methods have their own advantages and disadvantages depending upon their area of application and most importantly the RS datasets that are used for information extraction. Classification algorithms are variedly explored in the cryosphere for extracting geospatial information for various logistic and scientific applications, such as to understand temporal changes in geographical phenomena. Information extraction in cryospheric regions is challenging, accounting to the very similar and conflicting spectral responses of the features present in the region. The spectral responses of snow and ice, water, and blue ice, rock and shadow are a big challenge for the pixel-based classifiers. Thus, in such cases, OOC approach is superior for extracting information from the cryospheric regions. Also, ensemble classifiers and customized spectral index ratios (CSIR) proved extremely good approaches for information extraction from cryospheric regions. The present review would be beneficial for developing new classifiers in the cryospheric environment for better understanding of spatial-temporal changes over long time scales.

Analysis and Design of Soils and Terrain Digital Database (SOTER) Management System Based on Object-Oriented Method

A SOTER management system was developed by analyzing, designing, programming, testing, repeated proceeding and progressing based on the object-oriented method. The function of the attribute database management is inherited and expanded in the new system. The integrity and security of the SOTER database are enhanced. The attribute database management, the spatial database management and the model base are integrated into SOTER based on the component object model (COM), and the graphical user interface (GUI) for Windows is used to interact with clients, thus being easy to create and maintain the SOTER, and convenient to promote the quantification and automation of soil information application.

NDVI-Based Lacunarity Texture for Improving Identification of Torreya Using Object-Oriented Method

Normalized Difference Vegetation Index （NDVI） is a very useful feature for differentiating vegetation and non-vegetation in remote sensed imagery. In the light of the function of NDVI and the spatial patterns of the vegetation landscapes, we proposed the lacunarity texture derived from NDVI to characterize the spatial patterns of vegetation landscapes concerning the ＂gappiness＂ or ＂emptiness＂ characteristics. The NDVI-based lacunarity texture was incorporated into object-oriented classification for improving the identification of vegetation categories, especially Torreya which was the targeted tree species in the present research. A three-level hierarchical network of image objects was defined and the proposed texture was integrated as potential sources of information in the rules base. A knowledge base of rules created by classifier C5.0 indicated that the texture could potentially be applied in object-oriented classification. It was found that the addition of such texture improved the identification of every vegetation category. The results demonstrated that the texture could characterize the spatial patterns of vegetation structures, which could be a promising approach for vegetation identification.

Modeling Method of Automotive Body CAN/LIN Nets Application Protocol Based on Object-oriented Colored Petri Net

Recently automotive nets are adopted to solve increasing problems in automotive electronic systems.Technologies of automotive local area network from CAN and LIN can solve the problems of the increasing of wire bunch weight and lack in module installation space.However,the multilayer automotive nets software becomes more and more complex,and the development expense is difficult to predict and to keep in check.In this paper,the modeling method of hierarchical automotive nets and the substitution operation based on object-oriented colored Petri net(OOCPN) are proposed.The OOCPN model which analyzes the software structure and validates the collision mechanism of CAN/LIN bus can speed the automobile system development.First,the subsystems are divided and modeled by object-oriented Petri net(OOPN).According to the sets of message sharing relations,the message ports among them are set and the communication gate transitions are defined.Second,the OOPN model is substituted step by step until the inner objects in the automotive body control modules(BCM) are indivisible and colored by colored Petri net(CPN).And the color subsets mark the node messages for the collision mechanism.Third,the OOCPN model of the automotive body CAN/LIN nets is assembled,which keeps the message sets and the system can be expanded.The proposed model is used to analyze features of information sharing among the objects,and it is also used to describe each subsystem real-time behavior of processing messages and implemental device controllers operating,and puts forward a reasonable software framework for the automotive body control subsystem.The research can help to design the communication model in the automotive body system effectively and provide a convenient and rapid way for developing the logical hierarchy software.

Integrating object-oriented methods and formal methods for requirement engineering

High quality software requirement specification is crucial for a software development. Although much efforts and research works have been done to address the problem, the errors in user requirement are still prevent us from developing high quality software. To address the problem, this paper proposes integrating graphical specification technique UML with formal specification technique to construct user requirement specification. We also present a prototype tool to perform the automatic translation from UML specification into Object-Z specification.

Artificial Intelligence Embedded Object-Oriented Methodology For Model Based

The paper presents the coupling of artificial intelligence-AI and Object-oriented methodology applied for the construction of the model-based decision support system MBDSS.The MBDSS is designed for support the strategic decision making lead to the achievemellt of optimal path towardsmarket economy from the central planning situation in China. To meet user's various requirements,a series of innovations in software development have been carried out, such as system formalization with OBFRAMEs in an object-oriented paradigm for problem solving automation and techniques of modules intelligent cooperation, hybrid system of reasoning, connectionist framework utilization,etc. Integration technology has been highly emphasized and discussed in this article and an outlook to future software engineering is given in the conclusion section.

A Shortcut for Extricating System Development from Predicament－by Means of Object－oriented Methods

ＡＳｈｏｒｔｃｕｔｆｏｒＥｘｔｒｉｃａｔｉｎｇＳｙｓｔｅｍＤｅｖｅｌｏｐｍｅｎｔ ｆｒｏｍＰｒｅｄｉｃａｍｅｎｔ－ｂｙＭｅａｎｓｏｆＯｂｊｅｃｔ－ｏｒｉｅｎｔｅｄＭｅｔｈｏｄｓＰＡＮＱｉｓｈｕ；ＡＮＳｈｉ；ＷＡＮＧＦｕｓｈｅｎｇ；ＺＨＡＮＧＢａｏｘｉ...

Implementation of Heat Treatment Process Simulation with Object-Oriented Method

In this paper, mathematical models and FEA formulation for implementing heat treatment process simulation were given out. The various coupling effects were treated. The object-oriented methodology of developing heat treatment simulation was explored. The framework of simulating programs was outlined. The main C++ classes were developed, some important member functions were implemented. The present research work shows that using object-oriented method can greatly reduce the amount of coding. The programs are clear in conception, easy to test, modify and expand. By using the methodology introduced in this paper, one heat treatment process three dimensional simulation tool was developed.

ORDERED-OBJECT-ORIENTED METHOD:A NEW APPROACH OF SAMPLE PART CALCULATION AND DESIGN

This paper proposed a new approach of sample part classification and design, a so called Or-dered-object-oriented method (O-O-O method). Based on the theory of neural networks, fuzzy clustering algorithm and adaptive pattern recognition, O-O-O method can be used to classify and design the sample parts automatically. The basic theory, the main step as well as the characteristics of the method are analysed. The construction of the ordered object in application is also presented in this paper.

Product Family Design Methodology Using Object-Oriented Approach

The serious competition environment of global marke t requests the enterprise to change traditional product development strategy and a dopt new theory in order to meet diverse customer needs while maintaining near m ass production efficiency, which is the main philosophy of mass customization. P roduct family design is research focus at present and also is the core technolog y of DFMC (design for mass customization). Firstly, this paper explores the fund amental issues of product family, such as concepts of modularity, commonality/di versity, product platform and product family architecture etc. We compare the te rminology between product family and object-oriented approach in the next step. Thirdly, this paper puts forwards one product family design methodology based o n product platform and under different phase of product life cycle constrains, f or example, functional, assembly and service etc. At the end section of this pap er, we applied, the object-oriented approach in above mentioned product family design methodology to realize the design process. In one word, this paper propos ed one product family design methodology based on object oriented approach and p roduct life cycle consideration, especially the conjointness of characteristic o f OOA and concepts of product family. The main property of OOA are encapsulation , inherence and polymorphism. Encapsulation can represent the module or building blocks of product family. Inherence can be extended to describe the modularity and commonality, and also be used to construct variant space. Alternative specif ic of product family architecture can be embodied with polymorphism. And fin aly, we give the future work contents. In order to derive the product platform a nd achieve modularity and commonality/diversity, interface management between bu ilding block is necessary. The question is how the OOA can be applied in interfa ce management to get our aim OOA is the basis of many information management sy stem, then the question is how to build one system to manage the information of product family and support mass customization The third question is how to deve lop one computer aided tool to facilitate the application of OOA for product fam ily design, even be used to category of design for mass customization.

Research on object-oriented SOC design methodology

The growing complexity of System on Chip (SOC) requires a system level specification and design approach. High-level languages such as C+ +/SystemC can play multiple roles in system design as target languages. There are many practical problems in the application of object-oriented methods for this goal. Based on the analysis of traditional and system-level design methodology, a new object-oriented SOC design methodology with object-oriented design patterns is proposed, which emphasizes high-level design and verification. Aiming at the final goal of developing design patterns specific to SOC design, the reuse of design patterns in SOC systems and the capability of new SOC design patterns are discussed. With the illustration of some concrete examples of SOC design patterns, the application of object-oriented design methodology in the SOC design process is presented.

Object oriented land cover classification using ALS and GeoEye imagery over mining area

An object oriented coal mining land cover classification method based on semantically meaningful image segmentation and image combination of GeoEye imagery and airborne laser scanning (ALS) data was presented. First, DEM, DSM and nDSM (normalized Digital Surface Model, nDSM) were extracted from ALS data. The GeoEye imagery and DSM data were combined to create segmented objects based on neighbor regions merge method. Then 10 kinds of objects were extracted. Different kinds of vegetation objects, including crop, grass, shrub and tree, can be extracted by using NDVI and height value of nDSM. Water and coal pile field was extracted by using NDWI and the standard deviation of DSM method. Height differences also can be used to distinguish buildings from road and vacant land, and accurate building contour information can be extracted by using relationship of neighbor objects and morphological method. The test result shows that the total classification accuracy of the presented method is 90.78% and the kappa coefficient is 0.891 4.

A Study on the Design for Object-Oriented Adaptive Decision-Making Teams

The modern war features a highly distributed coordination. In the face of great time constrains, it is important to change command organizations to adapt to the real environment. Therefore it's a key step to set up adaptive C2 teams. In this paper, the relational problems about distributed C2 organizational structure adaptation are discussed, and the methodology for team decision making design based on the object oriented technique is studied.

Object-oriented Urban Dynamic Monitoring——A Case Study of Haidian District of Beijing

It is crucial to conduct the land use/cover research to obtain the global change information.Urban area is one of the most sensitive areas in land use/cover change.Therefore land use/cover change in urban areas is very im-portant in global change.It is vital to incorporate the information of urban land use/cover change into the process of decision-making about urban area development.In this paper,a new urban change detection approach,urban dynamic monitoring based on objects,is introduced.This approach includes four steps:1)producing multi-scale objects from multi-temporal remotely sensed images with spectrum,texture and context information;2)extracting possible changed objects adopting object-oriented classification;3)obtaining shared objects as the basic units for urban change detection;4)determining the threshold to segment the changed objects from the possible changed objects using Otsu method.In this paper,the object-based approach was applied to detecting the urban expansion in Haidian District,Beijing,China with two Landsat Thematic Mapper(TM)data in 1997 and 2004.The results indicated that the overall accuracy was about 84.83%,and Kappa about 0.785.Compared with other conventional approaches,the object-based approach was advantageous in reducing the error accumulation of image classification of each datum and in independence to the radiometric correction and image registration accuracy.

Review of Remotely Sensed Imagery Classification Patterns Based on Object-oriented Image Analysis

With the wide use of high-resolution remotely sensed imagery, the object-oriented remotely sensed informa- tion classification pattern has been intensively studied. Starting with the definition of object-oriented remotely sensed information classification pattern and a literature review of related research progress, this paper sums up 4 developing phases of object-oriented classification pattern during the past 20 years. Then, we discuss the three aspects of method- ology in detail, namely remotely sensed imagery segmentation, feature analysis and feature selection, and classification rule generation, through comparing them with remotely sensed information classification method based on per-pixel. At last, this paper presents several points that need to be paid attention to in the future studies on object-oriented RS in- formation classification pattern: 1) developing robust and highly effective image segmentation algorithm for multi-spectral RS imagery; 2) improving the feature-set including edge, spatial-adjacent and temporal characteristics; 3) discussing the classification rule generation classifier based on the decision tree; 4) presenting evaluation methods for classification result by object-oriented classification pattern.

The IRIS Development Platform and Proposed Object-Oriented Data Base

Various code development platforms, such as the ATHENA Framework [1] of the ATLAS [2] experiment encounter lengthy compilation/linking times. To augment this situation, the IRIS Development Platform was built as a software development framework acting as compiler, cross-project linker and data fetcher, which allow hot-swaps in order to compare various versions of software under test. The flexibility fostered by IRIS allowed modular exchange of software libraries among developers, making it a powerful development tool. The IRIS platform used input data ROOT-ntuples [3];however a new data model is sought, in line with the facilities offered by IRIS. The schematic of a possible new data structuring—as a user implemented object oriented data base, is presented.

VISUAL SIMULATION OF COLD ROLL-FORMING BASED ON OBJECT ORIENTED PROGRAMMING

To simulate the process of cold roll-forming process, a new method isadopted. The theoretical foundation of this method is an elastic-plastic large deformation splinefinite strip method based on object-oriented programming. Combined with the computer graphicstechnology, the visual simulation of cold roll-forming is completed and the system is established.By analyzing common channel steel, the process is shown and explained including theory method, modeland result display. So the simulation system is already a kind of mature and effective tool toanalyze the process of cold roll forming.