The Grasper-CL graph management system

Grasper-CL is a system for manipulating and displaying graphs, and for building graph-based user interfaces for application programs. It is implemented in COMMON LISP and CLIM, and has been proven by use in a number of applications. Grasper-CL includes several advances in graph drawing. It contains a graph abstract datatype plus a comprehensive and novel language of operations on that datatype. The appearance of Grasper-CL graphs can be tailored by a wide variety of shape parameters that allow the application to customize the display of nodes and edges for different domains. Default values for shape parameters can be established at several levels. Grasper-CL employs a toolbox approach to graph layout: the system contains a suite of graph layout algorithms that can be applied individually, or in combination to produce hierarchical graph layouts. The system also contains an interactive graph browser.     

一种基于类型传播分析的泛型实例重构方法

重构泛型实例有利于提高软件的复用性和类型安全,但现有重构方法的时间复杂度较高,不适用于即时持续的重构.分析了变量类型传播分析方法在重构中的不足,提出了一种改进的泛型变量类型传播分析方法.该方法通过引入一种可以描述复杂参数化类型关系的泛型类型传播图,以复制节点的方式实现泛型变量属性敏感的类型分析,并通过解决别名问题来提高分析的精度.实例研究表明,可以在与程序规模呈近似线性增长的时间复杂度内实施重构,取得了较满意的效果.     

基于语义关系对的SVG图形搜索引擎

个性化图形搜索打破了传统的查询方式搜索,将基于关键词的查询方式转变为基于图形的查询方式,使图形的查询具有一定的语义关系,查询结果也更加准确。该文给出一种基于语义关系对的SVG图形搜索引擎。目前大多数浏览器不直接支持SVG图形,但通过该文提出的SVG图形解析器和SVG图形显示器可以对网络上的SVG图形进行检索和显示。     

A Shape Graph Logic and A Shape System

Analysis and verification of pointer programs are still difficult problems so far. This paper uses a shape graph logic and a shape system to solve these problems in two stages. First, shape graphs at every program point are constructed using an analysis tool. Then, they are used to support the verification of other properties （e.g., orderedness）. Our prototype supports automatic verification of programs manipulating complex data structures such as splay trees, treaps, AVL trees and AA trees, etc. The proposed shape graph logic, as an extension to Hoare logic, uses shape graphs directly as assertions. It can be used in the analysis and verification of programs manipulating mutable data structures. The benefit using shape graphs as assertions is that it is convenient for acquiring the relations between pointers in the verification stage. The proposed shape system requires programmers to provide lightweight shape declarations in recursive structure type declarations. It can help rule out programs that construct shapes deviating from what programmers expect （reflected in shape declarations） in the analysis stage. As a benefit, programmers need not provide specifications （e.g., pre-/post-conditions, loop invariants） about pointers. Moreover, we present a method doing verification in the second stage using traditional Hoare logic rules directly by eliminating aliasing with the aid of shape graphs. Thus, verification conditions could be discharged by general theorem provers.     

Java泛型研究

2004年2月,Sun公司(2010年10月已被Oracle收购)在它发布的J2SE1.5版中加入了泛型,允许对类型进行抽象,程序员只需声明一个接受可变数目参数的方法,便可得到强类型在编译时刻进行类型检查的好处,简化了程序的开发。阐述了泛型基本概念和作用,介绍了在Java类、接口和方法中使用泛型的方法,通过实例比较使用泛型和不使用泛型的区别,最后指出使用泛型时要注意的问题。     

Study of the diagnosability of automated production systems based on functional graphs

Functional graphs are a convenient representation that we have introduced to model automated production systems. They are useful for the monitoring and the supervision of manufacturing processes or other industrial processes, such as chemical processes. An approach based on relational theory and graph theory is presented in this paper. This approach allows to characterize formally structural properties of a functional graph and to map it into a set of relations translating all the complete paths existing in the initial graph. Two kinds of functional graphs are analyzed and algorithms exploiting their structures are presented. We introduce the concept of diagnosability as a system property that reflects the possibility to observe the behavior of a system with respect to faults. The diagnosability is defined and analyzed by means of computable states and mathematical relations. Propositions explaining causality relations between functions of a functional graph are given.     

Symbolic graphs for attributed graph constraints

In this paper we present a new class of graphs, called symbolic graphs, to define a new class of constraints on attributed graphs. In particular, in the first part of the paper, we study the category of symbolic graphs showing that it satisfies some properties, which are the basis for the work that we present in the second part of the paper, where we study how to reason with attributed graph constraints. More precisely, we define a set of inference rules, which are the instantiation of the inference rules defined in a previous paper, for reasoning about constraints on standard graphs, showing their soundness and (weak) completeness. Moreover, the proof of soundness and completeness is also an instantiation of the corresponding proof for standard graph constraints, using the categorical properties studied in the first part of the paper. Finally, we show that adding a new inference rule makes our system sound and strongly complete.     

Efficient relational calculation for software analysis

Calculating with graphs and relations has many applications in the analysis of software systems, for example, the detection of design patterns or patterns of problematic design and the computation of design metrics. These applications require an expressive query language, in particular, for the detection of graph patterns, and an efficient evaluation of the queries even for large graphs. In this paper, we introduce RML, a simple language for querying and manipulating relations based on predicate calculus, and CrocoPat, an interpreter for RML programs. RML is general because it enables the manipulation not only of graphs (i.e., binary relations), but of relations of arbitrary arity. CrocoPat executes RML programs efficiently because it internally represents relations as binary decision diagrams, a data structure that is well-known as a compact representation of large relations in computer-aided verification. We evaluate RML by giving example programs for several software analyses and CrocoPat by comparing its performance with calculators for binary relations, a Prolog system, and a relational database management system.     

A learning-based module extraction method for object-oriented systems

Developers apply object-oriented (OO) design principles to produce modular, reusable software. Therefore, service-specific groups of related software classes called modules arise in OO systems. Extracting the modules is critical for better software comprehension, efficient architecture recovery, determination of service candidates to migrate legacy software to a service-oriented architecture, and transportation of such services to cloud-based distributed systems. In this study, we propose a novel approach to automatic module extraction to identify services in OO software systems. In our approach, first we create a weighted and directed graph of the software system in which vertices and edges represent the classes and their relations, respectively. Then, we apply a clustering algorithm over the graph to extract the modules. We calculate the weight of an edge by considering its probability of being within a module or between modules. To estimate these positional probabilities, we propose a machine-learning-based classification system that we train with data gathered from a real-world OO reference system. We have implemented an automatic module extraction tool and evaluated the proposed approach on several open-source and industrial projects. The experimental results show that the proposed approach generates highly accurate decompositions that are close to authoritative module structures and outperforms existing methods.     

Graph Classification by Means of Lipschitz Embedding

In pattern recognition and related fields, graph-based representations offer a versatile alternative to the widely used feature vectors. Therefore, an emerging trend of representing objects by graphs can be observed. This trend is intensified by the development of novel approaches in graph-based machine learning, such as graph kernels or graph-embedding techniques. These procedures overcome a major drawback of graphs, which consists of a serious lack of algorithms for classification. This paper is inspired by the idea of representing graphs through dissimilarities and extends our previous work to the more general setting of Lipschitz embeddings. In an experimental evaluation, we empirically confirm that classifiers that rely on the original graph distances can be outperformed by a classification system using the Lipschitz embedded graphs.     

Type-based termination of generic programs

Instances of a polytypic or generic program for a concrete recursive type often exhibit a recursion scheme that is derived from the recursion scheme of the instantiation type. In practice, the programs obtained from a generic program are usually terminating, but the proof of termination cannot be carried out with traditional methods as term orderings alone, since termination often crucially relies on the program type. In this article, it is demonstrated that type-based termination using sized types handles such programs very well. A framework for sized polytypic programming is developed which ensures (type-based) termination of all instances.     

图知识蒸馏综述：算法分类与应用分析

图数据, 如引文网络, 社交网络和交通网络, 广泛地存在现实生活中. 图神经网络凭借强大的表现力受到广泛关注, 在各种各样的图分析应用中表现卓越. 然而, 图神经网络的卓越性能得益于标签数据和复杂的网络模型, 而标签数据获取困难且计算资源代价高昂. 为了解决数据标签的稀疏性和模型计算的高复杂性问题, 知识蒸馏被引入到图神经网络中. 知识蒸馏是一种利用性能更好的大模型(教师模型)的软标签监督信息来训练构建的小模型(学生模型), 以期达到更好的性能和精度. 因此, 如何面向图数据应用知识蒸馏技术成为重大研究挑战, 但目前尚缺乏对于图知识蒸馏研究的综述. 旨在对面向图的知识蒸馏进行全面综述, 首次系统地梳理现有工作, 弥补该领域缺乏综述的空白. 具体而言, 首先介绍图和知识蒸馏背景知识; 然后, 全面梳理3类图知识蒸馏方法, 面向深度神经网络的图知识蒸馏、面向图神经网络的图知识蒸馏和基于图知识的模型自蒸馏方法, 并对每类方法进一步划分为基于输出层、基于中间层和基于构造图知识方法; 随后, 分析比较各类图知识蒸馏算法的设计思路, 结合实验结果总结各类算法的优缺点; 此外, 还列举图知识蒸馏在计算机视觉、自然语言处理、推荐系统等领域的应用; 最后对图知识蒸馏的发展进行总结和展望. 还将整理的图知识蒸馏相关文献公开在GitHub平台上, 具体参见: https://github.com/liujing1023/Graph-based-Knowledge-Distillation.     

Quotients of Gaussian graphs and their application to perfect codes

A graph-based model of perfect two-dimensional codes is presented in this work. This model facilitates the study of the metric properties of the codes. Signal spaces are modeled by means of Cayley graphs defined over the Gaussian integers and denoted as Gaussian graphs. Codewords of perfect codes will be represented by vertices of a quotient graph of the Gaussian graph in which the signal space has been defined. It will be shown that any quotient graph of a Gaussian graph is indeed a Gaussian graph. This makes it possible to apply previously known properties of Gaussian graphs to the analysis of perfect codes. To illustrate the modeling power of this graph-based tool, perfect Lee codes will be analyzed in terms of Gaussian graphs and their quotients.     

A graph-theoretic language extension for an interactive computer graphics environment

A programming language extension, AGILE, for the processing of graphs within an interactive computer graphics environment, is defined. The language is intended to be used for expressing and illustrating graph-theoretic algorithms and applications. However it does not deal with the actual drawing or display of graphs; rather one is able to access an existing general-purpose graphics package. The language then is intended to be used, in conjunction with a graphics package, as a tool for the production of more specialised graphics systems: the language allows one to naturally exploit the underlying graph structure found in a wide class of problems, while a graphics environment permits the elegant display of (and interaction with) such representations.AGILE extends the host language, C, by the addition of a graph database, and operators and control structures to manipulate this database. The graph structure is composed of five basic types: nodes, edges, graphs, sets and bugs (references). A general set of operators and tests are provided, including those for entity creation and deletion, node and edge traversal and tests for equality and containment of sets and graphs. Edges may be treated as being either directed or undirected; also multiple edges between nodes and self-loops are allowed. Arbitrary values and properties may be associated with each of the basic types. In particular, since a node may have a graph as value, a graph hierarchy is possible. Graphics primitives are provided by the GPAC graphics system.Three substantial applications have been programmed in the language: a system for producing diagrams of graphs and a class of data structures, a system for animating four algorithms for finding the maximum flow in a network, and a system for animating and making films of systems dynamics models.Several examples of programmes written in AGILE are included.     

Hard examples for the bounded depth Frege proof system

We prove exponential lower bounds on the size of a bounded depth Frege proof of a Tseitin graph-based contradiction, whenever the underlying graph is an expander. This is the first example of a contradiction, naturally formalized as a 3-CNF, that has no short bounded depth Frege proofs. Previously, lower bounds of this type were known only for the pigeonhole principle and for Tseitin contradictions based on complete graphs.Our proof is a novel reduction of a Tseitin formula of an expander graph to the pigeonhole principle, in a manner resembling that done by Fu and Urquhart for complete graphs.In the proof we introduce a general method for removing extension variables without significantly increasing the proof size, which may be interesting in its own right.     

Hybrid query execution engine for large attributed graphs

Graphs are widely used for modeling complicated data such as social networks, bibliographical networks and knowledge bases. The growing sizes of graph databases motivate the crucial need for developing powerful and scalable graph-based query engines. We propose a SPARQL-like language, G-SPARQL, for querying attributed graphs. The language enables the expression of different types of graph queries that are of large interest in the databases that are modeled as large graph such as pattern matching, reachability and shortest path queries. Each query can combine both structural predicates and value-based predicates (on the attributes of the graph nodes/edges). We describe an algebraic compilation mechanism for our proposed query language which is extended from the relational algebra and based on the basic construct of building SPARQL queries, the Triple Pattern. We describe an efficient hybrid Memory/Disk representation of large attributed graphs where only the topology of the graph is maintained in memory while the data of the graph are stored in a relational database. The execution engine of our proposed query language splits parts of the query plan to be pushed inside the relational database (using SQL) while the execution of other parts of the query plan is processed using memory-based algorithms, as necessary. Experimental results on real and synthetic datasets demonstrate the efficiency and the scalability of our approach and show that our approach outperforms native graph databases by several factors.     

Graph-based representations and techniques for image processing and image analysis

In this paper we will discuss the use of some graph-based representations and techniques for image processing and analysis. Instead of making an extensive review of the graph techniques in this field, we will explain how we are using these techniques in an active vision system for an autonomous mobile robot developed in the Institut de Robòtica i Informàtica Industrial within the project “Active Vision System with Automatic Learning Capacity for Industrial Applications (CICYT TAP98-0473)”. Specifically we will discuss the use of graph-based representations and techniques for image segmentation, image perceptual grouping and object recognition. We first present a generalisation of a graph partitioning greedy algorithm for colour image segmentation. Next we describe a novel fusion of colour-based segmentation and depth from stereo that yields a graph representing every object in the scene. Finally we describe a new representation of a set of attributed graphs (AGs), denominated function-described graphs (FDGs), a distance measure for matching AGs with FDGs and some applications for robot vision.     

基于图的多关系数据挖掘理论研究与方法

在过去的几年,结构化数据挖掘的需求日渐兴起,图是计算机学科和离散数学中最好的结构数据研究之一,基于图的数据挖掘已越来越广泛.本文介绍了基于图的数据挖掘的理论基础及其研究方法.     

Parallel complexity of signed graphs for gene assembly in ciliates

We consider a graph-based model for the study of parallelism in ciliate gene assembly, where a signed graph is associated to each micronuclear gene and the gene assembly is modeled as a graph rewriting process. A natural measure of complexity for gene assembly counts the minimal number of parallel steps needed to reduce the associated signed graph. We investigate the complexity of several classes of the graphs, so far found graphs of parallel complexity up to six. The general problem of whether there exists a finite upper bound for the graph parallel complexity still remains open.