Developing a Clang Libtooling-Based Refactoring Tool for CUDA GPU Programming

Refactoring tools, whether fully automated or semi-automated, are essential components of the software development life cycle. As software libraries and frameworks evolve over time, it’s crucial for programs utilizing them to also evolve to remain compatible with modern advancements. Take, for example, NVIDIA CUDA’s platform for general-purpose GPU programming. Embracing the more contemporary unified memory architecture offers several benefits, such as simplifying program source code, reducing bugs stemming from manual memory management between host and device memory, and optimizing memory transfer through automated memory handling. This paper describes our development of a refactoring tool based on Clang’s Libtooling to facilitate this transition automatically, thereby relieving developers from the burden and risks associated with manually refactoring large code bases.

用Refactoring来改善设计

面向对象的技术提高了软件重用能力 ,人们经验的不断总结也不断地改善了设计方法。如何去改善我们原有的系统是一个比较复杂的课题 ,也是一个不可回避的问题。这篇论文论述了如何使用Refactoring技术来改善原有设计。

Application of Refactoring and Design Pattern in Land Information System Development

The unceasing change problem of land information systems can be resolved through the refactoring and design pattern. To promote the implementation of design pattern and refactoring methods in developing land information systems reusing software design, applying refactoring methods to the abstract factory and decorator design patterns in land information system development is discussed.

Automated pattern-directed refactoring for complex conditional statements

Complex conditional statement is one of the bad code smells, which affects the quality of the code and design of software. In the proposed approach, two commonly-used design patterns for handling complex conditional statements are selected, and they are the factory method pattern and the strategy pattem. Two pattern-directed refactoring approaches based on the two design patterns are proposed. Each approach contains a refactoring opportunities identification algorithm and an automated refactoring algorithm. After parsing the abstract syntax tree generated from source code, the refactoring opportunities are identified effectively and automatically. Then, for candidate code, refactoring algorithms are executed automatically, which are used to simplify or remove complex conditional statements. By empirical analysis and quality assessment, the code after refactoring has better maintainability and extensibility, and the proposed approach for automated pattern-directed refactoring succeeds to reduce code size and complexity of classes.

A Recommendation Approach Based on Bayesian Networks for Clone Refactor

Reusing code fragments by copying and pasting them with or without minor adaptation is a common activity in software development.As a result,software systems often contain sections of code that are very similar,called code clones.Code clones are beneficial in reducing software development costs and development risks.However,recent studies have indicated some negative impacts as a result.In order to effectively manage and utilize the clones,we design an approach for recommending refactoring clones based on a Bayesian network.Firstly,clone codes are detected from the source code.Secondly,the clones that need to be refactored are identified,and the static and evolutions features are extracted to build the feature database.Finally,the Bayesian network classifier is used for training and evaluating the classification results.Based on more than 640 refactor examples of five open source software developed in C,we observe a considerable enhancement.The results show that the accuracy of the approach is larger than 90%.We believe our approach will provide a more accurate and reasonable code refactoring and maintenance advice for software developers.

Identification of refactoring opportunities for source code based on class association relationships

In order to deal with the complex association relationships between classes in an object-oriented software system,a novel approach for identifying refactoring opportunities is proposed.The approach can be used to detect complex and duplicated many-to-many association relationships in source code,and to provide guidance for further refactoring.In the approach,source code is first transformed to an abstract syntax tree from which all data members of each class are extracted,then each class is characterized in connection with a set of association classes saving its data members.Next,classes in common associations are obtained by comparing different association classes sets in integrated analysis.Finally,on condition of pre-defined thresholds,all class sets in candidate for refactoring and their common association classes are saved and exported.This approach is tested on 4 projects.The results show that the precision is over 96%when the threshold is 3,and 100%when the threshold is 4.Meanwhile,this approach has good execution efficiency as the execution time taken for a project with more than 500 classes is less than 4 s,which also indicates that it can be applied to projects of different scales to identify their refactoring opportunities effectively.

Source-to-Source Refactoring and Elimination of Global Variables in C Programs

A global variable in C/C++ is one that is declared outside a function, and whose scope extends the lifetime of the entire program. Global variables cause problems for program dependability, maintainability, extensibility, verification, and thread-safety. However, global variables can also make coding more convenient and improve program performance. We have found the use of global variables to remain unabated and extensive in real-world software. In this paper we present a source-to-source refactoring tool to automatically detect and localize global variables in a program. We implement a compiler based transformation to find the best location to redefine each global variable as a local. For each global, our algorithm initializes the corresponding new local variable, passes it as an argument to necessary functions, and updates the source lines that used the global to now instead use the corresponding local or argument. We also characterize the use of global variables in standard benchmark programs. We study the effect of our transformation on static program properties, such as change in the number of function arguments and program state visibility. Additionally, we quantify dynamic program features, including memory and runtime performance, before and after our localizing transformation.

Refactoring Software Packages via Community Detection in Complex Software Networks

An intrinsic property of software in a real-world environment is its need to evolve, which is usually accompanied by the increase of software complexity and deterioration of software quality, making software maintenance a tough problem. Refactoring is regarded as an effective way to address this problem. Many refactoring approaches at the method and class level have been proposed. But the research on software refactoring at the package level is very little. This paper presents a novel approach to refactor the package structures of object oriented software. It uses software networks to represent classes and their dependencies. It proposes a constrained community detection algorithm to obtain the optimized community structures in software networks, which also correspond to the optimized package structures. And it finally provides a list of classes as refactoring candidates by comparing the optimized package structures with the real package structures. The empirical evaluation of the proposed approach has been performed in two open source Java projects, and the benefits of our approach are illustrated in comparison with the other three approaches.

A Feature Model Based Framework for Refactoring Software Product Line Architecture

Software product line （SPL） is an approach used to develop a range of software products with a high degree of similarity. In this approach, a feature model is usually used to keep track of similarities and differences. Over time, as modifications are made to the SPL, inconsistencies with the feature model could arise. The first approach to dealing with these inconsistencies is refactoring. Refactoring consists of small steps which, when accumulated, may lead to large-scale changes in the SPL, resulting in features being added to or eliminated from the SPL. In this paper, we propose a framework for refactoring SPLs, which helps keep SPLs consistent with the feature model. After some introductory remarks, we describe a formal model for representing the feature model. We express various refactoring patterns applicable to the feature model and the SPL formally, and then introduce an algorithm for finding them in the SPL. In the end, we use a real-world case study of an SPL to illustrate the applicability of the framework introduced in the paper.

Experimental study on surface integrity refactoring changes of Ti-17 under milling-ultrasonic rolling composite process

Ultrasonic rolling is an advanced non-cutting surface strengthening method that combines traditional rolling with ultrasonic vibration.In this research,the experiment of orthogonal end milling-ultrasonic rolling composite process has been carried out.The surface integrity refactoring changes and its mechanism of Ti-17 titanium alloy during the milling-ultrasonic rolling composite process has been studied and analyzed by the test and analysis of the surface geometric characteristics,residual stress,microhardness and microstructure before and after ultrasonic rolling.The residual stress and microhardness gradient distribution were characterized by cosine decay function and exponential decay function.All indicators of surface integrity were significantly improved after ultrasonic rolling.The study demonstrates that the reduction effect of the surface roughness by ultrasonic rolling process is inversely proportional to the initial surface roughness value.The ultrasonic rolling can only change the distribution form of the surface topography when the initial surface roughness is small.In addition,the improvement effect of ultrasonic rolling on surface compressive residual stress and microhardness decreased with the increase of initial milled surface roughness and surface compressive residual stress due to the factors such as energy absorption efficiency and mechanical properties changes of surface materials.A better ultrasonic rolled surface can be obtained by controlling the roughness and residual compressive stress of the initial milling surface to a small level.

Major motivations for extract method refactorings： analysis based on interviews and change histories

Extract method is one of the most popular soft- ware refactorings. However, little work has been done to investigate or validate the major motivations for such refactorings. Digging into this issue might help researchers to improve tool support for extract method refactorings, e.g., proposing better tools to recommend refactoring opportunities, and to select fragments to be extracted. To this end, we conducted an interview with 25 developers, and our results suggest that current reuse, decomposition of long methods, clone resolution, and future reuse are the major motivations for extract method refactorings. We also validated the results by analyzing the refactoring history of seven open-source applications. Analysis results suggest that current reuse was the primary motivation for 56% of extract method refactorings, decomposition of methods was the primary motivation for 28% of extract method refactorings, and clone resolution was the primary motivation for 16% of extract method refactorings. These findings might suggest that recommending extract method opportunities by analyzing only the inner structure （e.g., complexity and length） of methods alone would miss many extract method opportunities. These findings also suggest that extract method refactorings are often driven by current and immediate reuse. Consequently, how to recognize or predict reuse requirements timely during software evolution may play a key role in the recommendation and automation of extract method refactorings. We also investigated the likelihood for the extracted methods to be reused in future, and our results suggest that such methods have a small chance （12%） to be reused in future unless the extracted fragment could be reused immediately in software evolution and extracting such a fragment can resolve existing clones at the same time.

A splitting-after-merging approach to multi-FIB compression and fast refactoring in virtual routers

Virtual routers are gaining increasing attention in the research field of future networks. As the core network device to achieve network virtualization, virtual routers have multiple virtual instances coexisting on a physical router platform, and each instance retains its own forwarding information base （FIB）. Thus, memory scalability suffers from the limited on-chip memory. In this paper, we present a splitting-after-merging approach to compress the FIBs, which not only improves the memory efficiency but also offers an ideal split position to achieve system refactoring. Moreover, we propose an improved strategy to save the time used for system rebuilding to achieve fast refactoring. Experiments with 14 real-world routing data sets show that our approach needs only a unibit trie holding 134 188 nodes, while the original number of nodes is 4 569 133. Moreover, our approach has a good performance in scalability, guaranteeing 90 000 000 prefixes and 65 600 FIBs.

Pragmatic model transformations for refactoring in Scilab/Xcos

Model-Based Development has become an industry wide standard paradigm.As an open source alternative,Scilab/Xcos is being widely employed as a hybrid dynamic systems modeling tool.With the increasing efficiency in implementation using graphical model development and code generation,the modeling and simulation community is struggling with assuring quality as well as maintainability and extendibility.Refactoring is defined as an evolutionary modernization activity where,most of the time,the structure of the artifact is changed to alter its quality characteristics,while keeping its behavior unchanged.It has been widely established as a technique for textual programming languages to improve the code structure and quality.While refactoring is also regarded as one of the key practices of model engineering,the methodologies and approaches for model refactoring are still under development.Architecture-Driven Modernization(ADM)has been introduced by the software engineering community as a model-based approach to software modernization,in which the implicit information that lies in software artifacts is extracted to models and model transformations are applied for modernization tasks.Regarding refactoring as a low level modernization task,the practices from ADM are adaptable.Accordingly,this paper proposes a model-based approach for model refactoring in order to come up with more efficient and effective model refactoring methodology that is accessible and extendable by modelers.Like other graphical modeling tools,Scilab/Xcos also possesses a formalized model specification conforming to its implicit metamodel.Rather than proposing another metamodel for knowledge extraction,this pragmatic approach proposes to conduct in place model-to-model transformations for refactoring employing the Scilab/Xcos model specification.To construct a structured model-based approach,the implicit Scilab/Xcos metamodel is explicitly presented utilizing ECORE as a meta-metamodel.Then a practical model transformation approach is established based on Scilab scripting.A Scilab toolset is provided to the modeler for in-place model-to-model transformations.Using a sample case study,it is demonstrated that proposed model transformation functions in Scilab provide a valuable refactoring tool.

基于生成对抗Transformer的电力负荷数据异常检测

电力负荷异常数据将给电力系统规划、负荷预测以及用能分析等带来较大的负面影响,因此亟须对负荷数据异常进行检测与识别。首先,针对电力负荷数据异常分类、原因及其特征开展分析。其次,改进传统Transformer编码器结构,采用多头注意力层代替掩码多头注意力层,同时移除前馈网络,以提高模型对负荷时序序列的全局注意力。基于生成对抗网络(generative adversarial networks,GAN)生成器与判别器的博弈结构,提出一种改进的GAN-Transformer模型,以更好地捕捉趋势性特征并加速模型收敛。然后,引入多阶段映射与训练方法,综合焦点分数打分机制,通过分阶段负荷序列重构帮助模型更好地提取负荷数据异常特征。最后,算例分析结果表明,GAN-Transformer模型在负荷数据异常检测精确率、召回率、F_(1)值以及训练时间方面均具有更优的性能,验证了所提方法的有效性和优越性。文中研究工作为基于深度学习进一步实现电力负荷数据异常分类与数据修复提供了有益参考。

异构平台要素协同理论方法研究

要素协同是协同作战发展的必经之路,杀伤链的动态重构是其典型特征.本文针对平台协同难以满足复杂作战任务需求的问题,提出了异构平台要素协同的解决思路和理论方法.首先分析了要素协同关系复杂性、协同能力不确定性两个难点问题;其次基于反馈机制的可重构架构对复杂作战网络进行建模,提出了杀伤链算子的要素动态重构、协同序参量的效能定量评估方法;最后基于仿真场景实现杀伤链的动态构建与重构,可指导要素协同的算法设计与工程实践.

Bagging异构集成的代码异味检测与重构优先级划分

代码异味是不良的设计和代码实现的症状,可能阻碍代码理解、增加代码更改和出错的可能性。以前的研究专注于单一模型在代码异味上的检测,并且无法为开发人员提供重构建议。针对上述问题,提出一种基于Bagging异构集成模型的代码异味检测与重构优先级划分方法,该方法利用分类器间的异质性,通过F1集成策略来检测Complex Class、Long Method、Spaghetti Code等三种代码异味,并将模型输出的异味概率转化为可能性分布后,为开发人员提供重构意见。实验在6个开源系统的32个版本上验证、评估:(1)基分类器的稳定性以及与代码异味的关系;(2)Bagging异构集成模型检测上述代码异味的性能;(3)将异味概率转化为可能性分布并作为重构优先级的有效性。实验结果表明,最佳基分类器因代码异味类型而异。同时,Bagging异构集成模型相较于基分类器,F1提高0.06~40.51个百分点,AUC提高0.45~28.37个百分点。最后将Bagging异构集成模型的重构优先级与6名受访者的重构优先级进行Kappa一致性检验,两者具有高度一致性。

高校智慧党建数据治理体系构建与实践路径研究

从智慧党建数据治理工作面临缺少顶层的统筹规划、数据标准不统一、数据集成度不高、数据分析能力不足等问题出发,初步构建智慧党建数据治理体系架构,并提出一套切实可行的智慧党建数据治理的实施路径解决方案。在此基础上,按照“数据汇聚-业务打散-流程重构”建设思路优化实践路径,为智慧党建数据治理、促进高校数字化转型提供参考价值。经过实践案例验证,该研究对于高校如何进行党建数据治理以及如何开展各类党建应用建设提供了范例。

无托槽牙齿矫治器个性化设计与3D成型

目的 对牙齿矫治器开展有限元仿真分析以确定不同工况的矫正量,制定无托槽牙齿矫治器的设计方案,使熔融沉积工艺成型的矫治器具备个性化的矫治效果。方法 结合患者CT数据逆向重构牙齿模型,通过有限元方法确立牙齿在倾斜、扭转、平移3种工况下的矫治量。选择不同弹性模量的材料3D成型不同矫治类型无托槽牙齿矫治器,并测量正畸力。结果 针对不同工况可设计不同的矫治偏移量,从而使矫治器具备个性化治疗效果。无托槽牙齿矫治器的正畸力随着弹性模量和厚度的增加而增大。在给定工况下,当矫治器材料为热可塑性聚氨酯(TPU)时正畸力最小(90 mN);当矫治器材料为聚乳酸(PLA)时正畸力最大(61.66 N)。结论 设计应根据患者的牙齿情况,在整个矫治过程中每一步矫治所需要正畸力的大小,选择不同弹性模量和不同厚度的无托槽牙齿矫治器对患者畸形牙齿进行治疗,从而实现分阶段矫治效果。

镂空重构手法在服装设计中的创新应用

为了打破镂空工艺对材料、技术的使用界限,丰富其在服装设计中的创新应用,通过梳理服装中镂空构型的起源与发展,在镂空重构概念界定的基础上,结合已有案例归纳分析镂空重构的3类实现手法:连接点式镂空、重塑线式镂空以及剪切面式镂空。以连接点式镂空手法为例,进一步探究镂空重构手法在服装设计中的创新实践:一是镂空构型材料层面的创新,将环保理念融入服装设计,实现废弃物升级利用;二是造型表现技术层面的创新,结合立体塑形进行服装造型表现的拓展实践,并对镂空重构手法在服装设计领域的应用前景作了展望。

Script-Based GPU-Ready ELM Development for Continuous Code Integration

Designing and optimizing complex scientific code for new computing architectures is a challenging task. To address this issue in the E3SM land model (ELM) development, we developed a software tool called SPEL, which facilitates code generation, verification, and performance tuning using compiler directives within a Function Unit Test framework. In this paper, we present a SPEL extension that leverages the version control system (e.g., Git) to autonomous code generation and demonstrate its application to continuous code integration and development of the ELM software system. The study can benefit the scientific software development community.