Detecting Bank Conflict of GPU Programs Using Symbolic Execution—Case Study

GPU (Graphics Processing Unit) is used in various areas. Therefore, the demand for the verification of GPU programs is increasing. In this paper, we suggest the method to detect bank conflict by using symbolic execution. Bank conflict is one of the bugs happening in GPU and it leads the performance of programs lower. Bank conflict happens when some processing units in GPU access the same shared memory. Symbolic execution is the method to analysis programs with symbolic values. By using it, we can detect bank conflict on GPU programs which use many threads. We implement a prototype of the detector for bank conflict and evaluate it with some GPU programs. The result states that we can detect bank conflict on the programs with no loop regardless of the number of threads.

Hybrid Methodology for Structural Health Monitoring Based on Immune Algorithms and Symbolic Time Series Analysis

This hybrid methodology for structural health monitoring (SHM) is based on immune algorithms (IAs) and symbolic time series analysis (STSA). Real-valued negative selection (RNS) is used to detect damage detection and adaptive immune clonal selection algorithm (AICSA) is used to localize and quantify the damage. Data symbolization by using STSA alleviates the effects of harmful noise in raw acceleration data. This paper explains the mathematical basis of STSA and the procedure of the hybrid methodology. It also describes the results of an simulation experiment on a five-story shear frame structure that indicated the hybrid strategy can efficiently and precisely detect, localize and quantify damage to civil engineering structures in the presence of measurement noise.

Symbolic Values in Steinbeck's Short Stories

The essay will analyze the symbols created by Steinbeck and disclose the meaning of the most widely used symbols John Steinbeck resorted toin some of his short stories. These interpretations of the symbols may reveal to readers an utterly different system of values. The author will explore those stories that are relevant from this point of view. This paper will highlight,emphasize and interpret different symbols presented in his stories too. And the author will give a possible way of tackling of Steinbeck short stories.

Symbolic Expressions of Differences between Earth Radii

A systematic and comprehensive comparison of the five commonly used earth radii in geodesy and cartography is carried out,and the differences between the most common points of the earth radii,their corresponding maximum values,and the latitudes of equal points between them are derived with the help of computer algebraic systems.The symbolic expressions are expressed as a power series of the first eccentricity.Taking the CGCS2000 ellipsoid as an example,the differences between the commonly used earth radii are clarified to numerical values.The results show that the difference between the commonly used earth radii has a maximum at 90 degrees and a minimum at 0 degree.The difference between the average radius of curvature and the rectifying sphere radius is the biggest,and the difference between the average radius of curvature and the average sphere radius is the smallest.These results can provide a theoretical basis for corresponding research in the geosciences,space science,navigation and positioning.

Current Situation of Fan Symbolic Consumption by Undergraduate

Inspired by consumerism in postmodern consuming society,people's consumption is not the value of products and service,but their symbolic fuction.Consumerism,formed in the western capitalist,has been constantly stimulating people's strong desire to consume as a concept of value and way of life,through the mass media.As a significant and special Youth group,young undergraduate has played a key role in stimulating consumption,especially for those undergraduate fans.As an important phenomenon of Youth Subculture,their idolatry has greatly influenced their ideology and behavior toward consumption,such as idolatry brand consumption and individual consumption.As a new generation,those college students consume rather than survival conditions.More and more are paying attention to behave self-value.They desire a new consumption image and wish to show self identity.

Tuning parallel symbolic execution engine for better performance

Symbolic execution is widely used in many code analysis, testing, and verification tools. As symbolic execu- tion exhaustively explores all feasible paths, it is quite time consuming. To handle the problem, researchers have par- alleled existing symbolic execution tools （e.g., KLEE）. In particular, Cloud9 is a widely used paralleled symbolic exe- cution tool, and researchers have used the tool to analyze real code. However, researchers criticize that tools such as Cloud9 still cannot analyze large scale code. In this paper, we con- duct a field study on Cloud9, in which we use KLEE and Cloud9 to analyze benchmarks in C. Our results confirm the criticism. Based on the results, we identify three bottlenecks that hinder the performance of Cloud9： the communication time gap, the job transfer policy, and the cache management of the solved constraints. To handle these problems, we tune the communication time gap with better parameters, modify the job transfer policy, and implement an approach for cache management of solved constraints. We conduct two evalua- tions on our benchmarks and a real application to understand our improvements. Our results show that our tuned Cloud9 reduces the execution time significantly, both on our bench- marks and the real application. Furthermore, our evaluation results show that our tuning techniques improve the effective- ness on all the devices, and the improvement can be achievedupto five times, depending upon a tuning value of our ap- proach and the behaviour of program under test.

Unit Test Data Generation for C Using Rule-Directed Symbolic Execution

Unit testing is widely used in software development. One important activity in unit testing is automatic test data generation. Constraint-based test data generation is a technique for automatic generation of test data, which uses symbolic execution to generate constraints. Unit testing only tests functions instead of the whole program, where individual functions typically have preconditions imposed on their inputs. Conventional symbolic execution cannot detect these preconditions, let alone converting these preconditions into constraints. To overcome these limitations, we propose a novel unit test data generation approach using rule-directed symbolic execution for dealing with functions with missing input preconditions. Rule-directed symbolic execution uses predefined rules to detect preconditions in the individual function, and generates constraints for inputs based on preconditions. We introduce implicit constraints to represent preconditions, and unify implicit constraints and program constraints into integrated constraints. Test data generated based on integrated constraints can explore previously unreachable code and help developers find more functional faults and logical faults. We have implemented our approach in a tool called CTS-IC, and applied it to real-world projects. The experimental results show that rule-directed symbolic execution can find preconditions (implicit constraints) automatically from an individual function. Moreover, the unit test data generated by our approach achieves higher coverage than similar tools and efficiently mitigates missing input preconditions problems in unit testing for individual functions.

Modified condition/decision coverage(MC/DC)oriented compiler optimization for symbolic execution

Symbolic execution is an effective way of systematically exploring the search space of a program,and is often used for automatic software testing and bug finding.The program to be analyzed is usually compiled into a binary or an intermediate representation,on which symbolic execution is carried out.During this process,compiler optimizations influence the effectiveness and efficiency of symbolic execution.However,to the best of our knowledge,there exists no work on compiler optimization recommendation for symbolic execution with respect to(w.r.t.)modified condition/decision coverage(MC/DC),which is an important testing coverage criterion widely used for mission-critical software.This study describes our use of a state-of-the-art symbolic execution tool to carry out extensive experiments to study the impact of compiler optimizations on symbolic execution w.r.t.MC/DC.The results indicate that instruction combining(IC)optimization is the important and dominant optimization for symbolic execution w.r.t.MC/DC.We designed and implemented a support vector machine based optimization recommendation method w.r.t.IC(denoted as auto).The experiments on two standard benchmarks(Coreutils and NECLA)showed that auto achieves the best MC/DC on 67.47%of Coreutils programs and 78.26%of NECLA programs.

Binary Program Vulnerability Mining Based on Neural Network

Software security analysts typically only have access to the executable program and cannot directly access the source code of the program.This poses significant challenges to security analysis.While it is crucial to identify vulnerabilities in such non-source code programs,there exists a limited set of generalized tools due to the low versatility of current vulnerability mining methods.However,these tools suffer from some shortcomings.In terms of targeted fuzzing,the path searching for target points is not streamlined enough,and the completely random testing leads to an excessively large search space.Additionally,when it comes to code similarity analysis,there are issues with incomplete code feature extraction,which may result in information loss.In this paper,we propose a cross-platform and cross-architecture approach to exploit vulnerabilities using neural network obfuscation techniques.By leveraging the Angr framework,a deobfuscation technique is introduced,along with the adoption of a VEX-IR-based intermediate language conversion method.This combination allows for the unified handling of binary programs across various architectures,compilers,and compilation options.Subsequently,binary programs are processed to extract multi-level spatial features using a combination of a skip-gram model with self-attention mechanism and a bidirectional Long Short-Term Memory(LSTM)network.Finally,the graph embedding network is utilized to evaluate the similarity of program functionalities.Based on these similarity scores,a target function is determined,and symbolic execution is applied to solve the target function.The solved content serves as the initial seed for targeted fuzzing.The binary program is processed by using the de-obfuscation technique and intermediate language transformation method,and then the similarity of program functions is evaluated by using a graph embedding network,and symbolic execution is performed based on these similarity scores.This approach facilitates cross-architecture analysis of executable programs without their source codes and concurrently reduces the risk of symbolic execution path explosion.

商品房消费者执行异议的规则适用——基于最高人民法院裁判分歧的分析与展开

我国实定法优先保护商品房消费者的权利,但基于生存权的考量,这一规则不会导致实践中相冲突利益间的严重失衡。为稳定交易预期,这一规则的适用应予严格把握:首先,只要具备商品房买卖合同必要条款的书面合同均可被认定为“买卖合同”;其次,商住两用房、车位等不动产只要满足当事人及其配偶、未成年子女或其监护人的居住需要,则在保护范围之内;再次,买受人尚须证明已实际支付不动产买卖价金。另外,为提供高效完整的权利保护体系,商品房消费者在排除申请人对不动产的执行后,可以选择继续履行合同,亦可选择参与拍卖不动产的价金分配,如商品房消费者不能继续履行合同,债权人可再次提起诉讼,以争议标的实现债权。

语言符号资本个体价值与社会价值互动研究

语言符号资本体现了个体与社会之间的互动关系。个体通过学习和使用语言,不仅能够满足基本的交流需求,还能增强自身的竞争力和社会地位;而个人的语言能力又反过来影响到语言的发展和社会文化的变迁。从社会层面来看,语言符号资本是人类社会发展的重要动力,它促进了各领域如教育、文化、贸易等的进步。健康的语言市场有助于个体语言符号资本的价值实现,进而促进语言服务业的发展。语言符号资本的个体价值与社会价值是相互依托、交互作用的。因此,关注两者的互动有利于全面认识语言的经济属性,推动语言资本个人价值与社会价值的协调发展,为建构稳定良性的语言环境贡献力量。

网络协议软件漏洞挖掘技术综述

网络协议软件部署和应用非常广泛,在网络空间提供了诸如通信、传输、控制、管理等多样化的功能.近年来,其安全性逐渐受到学术界和工业界的重视,及时发现和修补网络协议软件漏洞,成为一项重要的课题.网络协议软件由于部署形态多样、协议交互过程复杂、相同协议规范的多个协议实现存在功能差异等特点,使得其漏洞挖掘技术面临诸多挑战.首先对网络协议软件漏洞挖掘技术进行分类,对已有关键技术的内涵进行界定.其次,进一步综述网络协议软件漏洞挖掘4个方面的技术进展,包括网络协议描述方法、挖掘对象适配技术、模糊测试技术和基于程序分析的漏洞挖掘方法,通过对比分析归纳不同方法的技术优势及评价维度.最后,总结网络协议软件漏洞挖掘的技术现状和挑战,并提炼5个潜在研究方向.

基于符号执行优化的PDF恶意指标提取技术

恶意PDF文档是APT组织常用的攻击方法,提取分析其内嵌JavaScript代码指标是判定文档恶意性的重要手段,然而攻击者可以采取高度混淆、虚拟机与沙箱检测等逃逸方法。因此,文中创新性地将符号执行方法用于PDF指标提取,提出了一种基于符号执行优化的PDF恶意指标提取技术,并实现了由代码解析、符号执行和指标提取3个模块组成的指标提取系统SYMBPDF。在代码解析模块中实现内嵌JavaScript代码提取与重组。在符号执行模块中设计代码改写方法,通过强制分支转移提高符号执行的代码覆盖率;设计并发策略和两种约束求解优化方法,以提高系统执行效率。在指标提取模块中实现恶意指标整合与记录。对1 271个恶意样本进行了指标提取与评估,指标提取成功率为92.2%,有效性为91.7%,代码覆盖率较优化前提升8.5%,系统性能较优化前提升32.3%。

关键路径预搜索的符号执行智能合约漏洞检测

针对传统符号执行在不必要、不相关的路径上消耗大量时间与资源,效率低等问题,提出了利用静态检测预扫描智能合约关键路径优化符号执行验证,避免非必要路径搜索增加的资源消耗,实现基于关键路径预搜索的符号执行。该方法与现有主流检测工具进行对比实验,结果显示:Gas耗尽拒绝服务漏洞覆盖率达98%,检测准确度为84.3%,远高于均值37.2%;对存储覆盖漏洞合约的全覆盖,检测准确率为86.1%,验证了该方法的高效性与稳定性。

基于行为模式的漏洞检测方法

目前基于符号执行的漏洞检测工作仍存在漏洞类型有限和未能精确描述检测到的漏洞类型等问题。首先,通过深入分析常见内存损坏漏洞的形成原因和行为模式,提出了一种通用的基于行为模式的漏洞检测方法,覆盖更多的漏洞类型,并且在检测到漏洞的同时自动确定漏洞类型。最后,设计并实现了一个自动化漏洞检测框架,并通过实验验证了其有效性。研究成果对于提高网络空间安全能力具有一定的意义和价值。

中国共产党“形象符号价值+受众兴趣符号”国际形象传播路径研究——基于网宣片《CPC》的符号学分析

21世纪以来,中国共产党国际形象传播不断面临着以美国为首的国际社会舆论环形包围与国际媒体机构持续打压的双重阻碍,而培养与强化“受众本位意识”的中国共产党国际形象传播思路不仅能够更好地推动中国共产党国际形象的有效传播,而且能够促进新时期中国共产党国际形象传播模式的建立。基于此,通过借助“皮尔斯+索绪尔”符号融合模式,以中国共产党国际形象网宣片《CPC》为例,分析该片中蕴含的中国共产党国际形象的符号价值并建构属于中国共产党国际形象的三元传播模式,同时基于国际受众生成的兴趣符号内容,探索中国共产党“形象符号价值+受众兴趣符号”定向扩展创新传播路径,推动新时期中国共产党国际形象传播的创新化发展。

高管薪酬、社会责任与价值创造——来自中国资本市场的经验证据

高管薪酬制度设计是能否缓解委托代理问题的重要治理机制,高管薪酬与社会责任履行影响着企业价值创造成效。选取2016-2020年沪深两市A股上市公司作为研究对象,实证探究高管薪酬对价值创造的影响机制,并考察社会责任的中介效应。研究发现:高管薪酬越高,企业价值创造越高,社会责任在高管薪酬与价值创造中具有中介效应。本文将高管薪酬、社会责任与价值创造相结合,在丰富价值创造理论研究的同时,为企业设置合理高管团队薪酬、引导企业动态调整高管薪酬提供依据并提出相关建议:完善管理层激励方式,设置合理的薪酬制度,建立完善的薪酬激励约束机制;完善高管绩效考核制度,关注高管工作效率,健全企业内部监督机制;将社会责任作为高管薪酬考核的标准,完善公司治理结构,将社会责任履行纳入企业战略;积极披露履行社会责任的信息,向各方利益相关者传递积极信号,树立企业的良好形象,增加企业声誉资本。

青少年“符号消费”的伦理问题与对策研究

随着消费文化的日益多元化和深入,青少年群体中的“符号消费”现象引发了广泛关注。文章旨在深入探讨这一现象背后的伦理问题及其对青少年价值观和消费行为的影响。符号消费不只限于物质产品的购买,更体现在对品牌、形象和社会地位象征的追求。这种追求往往导致青少年的消费决策偏离理性,忽视真实需求,从而引发伦理问题,如盲目从众、攀比心理的加剧、资源的过度消费以及对个人和社会责任的忽视。这些问题不仅影响青少年的健康成长,还对社会的可持续发展构成威胁。因此,文章着重分析这些伦理问题,并提出相应的对策,目的是促进青少年形成健康的价值观和消费行为,为社会的可持续发展贡献力量。

面向区域能量调控的信息时效性保障与数据价值提升策略

针对新型电力系统中区域能量调控业务的传输与处理问题,首先,介绍新型电力系统多流融合模型,以信息流的高效传输与价值流的及时释放促进能源流的有序配置。其次,建立电力通信耦合网络以及电力弹性光网络系统模型,并设置在保障信息时效性前提下最大化数据价值的优化问题。最后,提出可在线执行的信息时效性保障与数据价值提升策略,结合Lyapunov优化、匹配理论与交替方向乘子法算法,实现电力弹性光网络频谱资源与调控主站计算资源的联合优化配置。仿真结果表明,所提方法可在保障调控信息时效性的前提下,通过网络资源的优化配置提升调控业务数据价值。

高管性别多样性、ESG表现与企业价值

为探究高管性别多样性与企业价值的关系以及ESG表现在两者之间的中介效应,基于2015—2021年中国沪深两市A股上市公司数据,采用实证分析方法对固定效应模型进行检验。研究发现,高管性别多样性与企业价值存在正向相关关系,ESG表现在两者之间发挥了部分中介效应,即高管性别多样性—ESG表现—企业价值这一链条关系得以证明。通过异质性进一步分析发现,高管性别多样性—ESG表现—企业价值链条关系存在产权异质性和行业竞争强度异质性,即对比非国有企业,国有企业高管性别多样性与ESG表现关系的显著性较强,但高管性别多样性—ESG表现—企业价值这一链条关系在这一分组中并未得到证明;全样本的研究结论在处于高市场竞争状态下的企业样本中得以证明,在低市场竞争强度下的企业样本中,未能得到证实。在此基础上,进行了内生性检验与稳健性检验,上述结论依旧成立。