Ada System Dependency Analyzer tool

A major thrust of modern software engineering methods, languages, and tools is to promote software visibility and to present information about the underlying software architecture. With large, complex software systems, automated tools are indispensable for identifying the architectural components, the structure that interconnects them, and other subtle dependencies. This article describes the construction of an Ada System Dependency Analyzer (SDA), a software architecture analysis tool that generates a quantitative snapshot of an Ada application's software architecture. The SDA can process thousands of Ada source files during a single run and report on them as a group of files comprising a single Ada system. Our SDA tool identifies Ada source code dependencies on COTS products such as operating systems, compilers, the X Window System, and on routines written in other languages, and can thus predict software portability and reliability problems. It rapidly and accurately processes 24,000 lines of code per minute (a time-consuming, if not impossible, operation if done manually) and has successfully processed more than seven million lines of code in eight complex systems. Although originally developed for Ada, our methods and the technology we adopted will let us construct analogous tools for other programming languages such as C, C++, Cobol; and PL/I     

Metamorphic code generation from LLVM bytecode

Metamorphic software changes its internal structure across generations with its functionality remaining unchanged. Metamorphism has been employed by malware writers as a means of evading signature detection and other advanced detection strategies. However, code morphing also has potential security benefits, since it can serve to increase the “genetic diversity” of software. We have created a metamorphic code generator within the LLVM compiler framework. LLVM is a three-phase compiler that supports multiple source languages and target architectures. It uses a common intermediate representation (IR) bytecode in its optimizer. Consequently, any supported high-level programming language is transformed to this IR bytecode as part of the LLVM compilation process. Our metamorphic generator functions at the IR bytecode level, which provides many advantages over morphing at the assembly or source code level. The morphing techniques that we employ include dead code insertion and transposition, where the dead code is actually executed within the morphed code, making its detection and removal more challenging. We have verified the effectiveness of our code morphing using hidden Markov model analysis.     

从源码中抽取设计模式技术研究综述

从源码中抽取设计模式对于提高软件可理解性和可维护性、软件设计重用以及软件重构具有重要意义。研究设计模式抽取技术的方法框架,并根据该框架对目前流行的几种设计模式抽取方法进行分类和比较,分析这些技术的优缺点,探讨该领域未来的研究方向和趋势。     

AFID: an automated approach to collecting software faults

We present a new approach for creating repositories of real software faults. We have developed a tool, the Automatic Fault IDentification Tool (AFID), that implements this approach. AFID records both a fault revealing test case and a faulty version of the source code for any crashing faults that the developer discovers and a fault correcting source code change for any crashing faults that the developer corrects. The test cases are a significant contribution, because they enable new research that explores the dynamic behaviors of the software faults. AFID uses an operating system level monitoring mechanism to monitor both the compilation and execution of the application. This technique makes it straightforward for AFID to support a wide range of programming languages and compilers.     

基于设计模式的软件设计恢复方法研究

从源码中抽取设计模式对于提高软件可理解性和可维护性、软件设计重用以及软件重构具有重要意义.本文研究基于设计模式的软件设计恢复方法框架,并根据该框架对设计模式实例查找过程可能遇到的关键问题予以分析解答,探讨该领域未来的研究方向和趋势.     

一种基于国产异构众核处理器的C++智能源码转换框架

国产异构众核处理器是我国打破国际技术壁垒,在高性能计算领域取得突破的关键环节.围绕国产超算的软件生态环境建设,采用智能源码转换的方法盘活海量多核架构的遗产代码是加速软件研发效率,推动领域发展的重要途径.针对国产运算核心不支持C++编译的现状,基于开源的ANTLR语言翻译工具,提出了一种面向异构众核处理器的智能化C++语...     

基于关联度和特征约束的软件设计模式识别方法

在程序理解和软件逆向工程研究中,找到准确和快速地描述软件的设计模式和待识别源代码的方法,对于构建合理的设计模式识别框架和高效的识别算法是至关重要的。运用无向图的邻接表和连通分量的原理,提出类与类之间关联度的概念,由待识别源代码构建一个关联类集合,旨在减小设计模式识别算法的搜索空间;根据设计模式的特征,提出基于关联度和特征约束的设计模式识别算法。对Junit、JHotDraw和JreFactory 3个开源应用程序进行的设计模式识别表明,该算法能够准确高效地完成对源代码设计模式的识别。     

基于模式匹配的安全漏洞检测方法

针对现存的大部分软件漏洞静态检测工具无法灵活检测用户关心的漏洞的情况,提出了一种基于模式匹配的漏洞检测方法。首先,对待测程序源码进行解析,将其转化为中间表示并存放在自定义的数据结构中;然后,用安全规则语言描述漏洞并解析安全规则,将其转换成对应的自动机模型存放在内存中;最后,将源代码的中间表示与安全规则进行模式匹配,并跟踪自动机的状态转化,根据自动机状态向用户提交漏洞报告。实验结果表明,该方法的漏报率低、扩展性好。     

Struts框架及Spring框架的模式分析

Struts框架及Spring框架提供了预备的软件架构和相关的软件包,可融合使用开发层次划分清晰并易于复用的Web应用。通过分析Struts框架控制器源码所使用的经典设计模式和J2EE模式阐明了Struts框架的工作原理及设计思想。阐述了Spring框架的反转控制模式的实现思想。     

Sourcerer: An infrastructure for large-scale collection and analysis of open-source code

A large amount of open source code is now available online, presenting a great potential resource for software developers. This has motivated software engineering researchers to develop tools and techniques to allow developers to reap the benefits of these billions of lines of source code. However, collecting and analyzing such a large quantity of source code presents a number of challenges. Although the current generation of open source code search engines provides access to the source code in an aggregated repository, they generally fail to take advantage of the rich structural information contained in the code they index. This makes them significantly less useful than Sourcerer for building state-of-the-art software engineering tools, as these tools often require access to both the structural and textual information available in source code.We have developed Sourcerer, an infrastructure for large-scale collection and analysis of open source code. By taking full advantage of the structural information extracted from source code in its repository, Sourcerer provides a foundation upon which state-of-the-art search engines and related tools can easily be built. We describe the Sourcerer infrastructure, present the applications that we have built on top of it, and discuss how existing tools could benefit from using Sourcerer.     

Static generation of UML sequence diagrams

UML sequence diagrams are visual representations of object interactions in a system and can provide valuable information for program comprehension, debugging, maintenance, and software archeology. Sequence diagrams generated from legacy code are independent of existing documentation that may have eroded. We present a framework for static generation of UML sequence diagrams from object-oriented source code. The framework provides a query refinement system to guide the user to interesting interactions in the source code. Our technique involves constructing a hypergraph representation of the source code, traversing the hypergraph with respect to a user-defined query, and generating the corresponding set of sequence diagrams. We implemented our framework as a tool, StaticGen (supporting software: StaticGen), analyzing a corpus of 30 Android applications. We provide experimental results demonstrating the efficacy of our technique (originally appeared in the Proceedings of Fundamental Approaches to Software Engineering—20th International Conference, FASE 2017, Held as Part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2017, Uppsala, Sweden, April 22–29, 2017).

     

面向代码相似性检测的相似哈希改进方法

代码相似性检测(code similarity detection)是软件工程领域的基本任务之一,其在剽窃检测、许可证违反检测、软件复用分析以及漏洞发现等方向均起着重要作用.随着软件开源化的普及以及开源代码量的高速增长,开源代码在各个领域的应用日益频繁,给传统的代码相似性检测方法带来了新的挑战.现有的一些基于词法、语法...     

基于多模态对比学习的代码表征增强预训练方法

代码表征旨在融合源代码的特征,以获取其语义向量,在基于深度学习的代码智能中扮演着重要角色.传统基于手工的代码表征依赖领域专家的标注,繁重耗时,且无法灵活地复用于特定下游任务,这与绿色低碳的发展理念极不相符.因此,近年来,许多自监督学习的编程语言大规模预训练模型(如CodeBERT)应运而生,为获取通用代码表征提供了有效途径.这些模型通过预训练获得通用的代码表征,然后在具体任务上进行微调,取得了显著成果.但是,要准确表示代码的语义信息,需要融合所有抽象层次的特征(文本级、语义级、功能级和结构级).然而,现有模型将编程语言仅视为类似于自然语言的普通文本序列,忽略了它的功能级和结构级特征.因此,旨在进一步提高代码表征的准确性,提出了基于多模态对比学习的代码表征增强的预训练模型(representation enhanced contrastive multimodal pretraining, REcomp). REcomp设计了新的语义级-结构级特征融合算法,将它用于序列化抽象语法树,并通过多模态对比学习的方法将该复合特征与编程语言的文本级和功能级特征相融合,以实现更精准的语义建模.最后,...     

A query algebra for program databases

Querying source code is an essential aspect of a variety of software engineering tasks such as program understanding, reverse engineering, program structure analysis and program flow analysis. In this paper, we present and demonstrate the use of an algebraic source code query technique that blends expressive power with query compactness. The query framework of Source Code Algebra (SCA) permits users to express complex source code queries and views as algebraic expressions. Queries are expressed on an extensible, object-oriented database that stores program source code. The SCA algebraic approach offers multiple benefits such as an applicative query language, high expressive power, seamless handling of structural and flow information, clean formalism and potential for query optimization. We present a case study where SCA expressions are used to query a program in terms of program organization, resource flow, control flow, metrics and syntactic structure. Our experience with an SCA-based prototype query processor indicates that an algebraic approach to source code queries combines the benefits of expressive power and compact query formulation     

Integration of a security type system into a program logic

Type systems and program logics are often thought to be at opposing ends of the spectrum of formal software analyses. In this paper we show that a flow-sensitive type system ensuring non-interference in a simple while-language can be expressed through specialised rules of a program logic. In our framework, the structure of non-interference proofs resembles the corresponding derivations in a state-of-the-art security type system, meaning that the algorithmic version of the type system can be used as a proof procedure for the logic. We argue that this is important for obtaining uniform proof certificates in a proof-carrying code framework. We discuss in which cases the interleaving of approximative and precise reasoning allows us to deal with delimited information release. Finally, we present ideas on how our results can be extended to encompass features of realistic programming languages such as Java.     

Software assessment using metrics: A comparison across large C++ and Java systems

This paper presents an assessment method to evaluate the quality of object oriented software systems. The assessment method is based on source code abstraction, object–oriented metrics and graphical representation. The metrics used and the underlying model representing the software are presented. The assessment method experiment is part of an industrial research effort with the Bell Canada Quality Engineering and Research Group. It helps evaluators assess the quality and risks associated with software by identifying code fragments presenting unusual characteristics. The assessment method evaluates object–oriented software systems at three levels of granularity: system level, class level and method level. One large C++ and eight Java software systems, for a total of over one million lines of code, are presented as case studies. A critical analysis of the results is presented comparing the systems and the two languages.     

A language-independent approach to the extraction of dependencies between source code entities

ContextSoftware networks are directed graphs of static dependencies between source code entities (functions, classes, modules, etc.). These structures can be used to investigate the complexity and evolution of large-scale software systems and to compute metrics associated with software design. The extraction of software networks is also the first step in reverse engineering activities.ObjectiveThe aim of this paper is to present SNEIPL, a novel approach to the extraction of software networks that is based on a language-independent, enriched concrete syntax tree representation of the source code.MethodThe applicability of the approach is demonstrated by the extraction of software networks representing real-world, medium to large software systems written in different languages which belong to different programming paradigms. To investigate the completeness and correctness of the approach, class collaboration networks (CCNs) extracted from real-world Java software systems are compared to CCNs obtained by other tools. Namely, we used Dependency Finder which extracts entity-level dependencies from Java bytecode, and Doxygen which realizes language-independent fuzzy parsing approach to dependency extraction. We also compared SNEIPL to fact extractors present in language-independent reverse engineering tools.ResultsOur approach to dependency extraction is validated on six real-world medium to large-scale software systems written in Java, Modula-2, and Delphi. The results of the comparative analysis involving ten Java software systems show that the networks formed by SNEIPL are highly similar to those formed by Dependency Finder and more precise than the comparable networks formed with the help of Doxygen. Regarding the comparison with language-independent reverse engineering tools, SNEIPL provides both language-independent extraction and representation of fact bases.ConclusionSNEIPL is a language-independent extractor of software networks and consequently enables language-independent network-based analysis of software systems, computation of design software metrics, and extraction of fact bases for reverse engineering activities.     

Software assessment using metrics: A comparison across large C++ and Java systems

This paper presents an assessment method to evaluate the quality of object oriented software systems. The assessment method is based on source code abstraction, object–oriented metrics and graphical representation. The metrics used and the underlying model representing the software are presented. The assessment method experiment is part of an industrial research effort with the Bell Canada Quality Engineering and Research Group. It helps evaluators assess the quality and risks associated with software by identifying code fragments presenting unusual characteristics. The assessment method evaluates object–oriented software systems at three levels of granularity: system level, class level and method level. One large C++ and eight Java software systems, for a total of over one million lines of code, are presented as case studies. A critical analysis of the results is presented comparing the systems and the two languages. This revised version was published online in June 2006 with corrections to the Cover Date.     

基于源代码挖掘的软件质量改进方法研究

代码搜索引擎（code search engines,CSE）产生和互联网上日益增加的开源代码工程,使得软件开发人员在软件开发的过程中可以大量的重用已有的源代码。然而大部分开发人员使用CSEs只是简单完成相关代码搜索。该文给出了一种通用的范型挖掘过程模型,能够充分利用CSEs,通过挖掘源代码范型保证重用代码的质量,并详细的说明了该范型挖掘过程模型在三个方面辅助软件质量改进。