基于语法和语义结合的源代码精确搜索方法

针对在编写软件、复用源代码的过程中仅依靠关键词无法精准搜索到适用源代码的问题,提出一种将语法和语义结合的源代码精准搜索方法。首先依据源代码语法语义的客观和唯一性,增加语法结构和"输入/输出"语义作为用户录入请求的一部分,并规范了具体的请求格式;然后在此基础上分别设计源代码语法匹配算法、"输入/输出"语义匹配算法、关键词兼容匹配,以及源代码搜索结果可信度计算算法;最后综合上述算法实现对源代码的精准搜索。测试结果表明：与单纯的关键词搜索相比,提出的方法对搜索的平均排序倒数（MRR）有超过62%的提升,有助于实现源代码的精准搜索。     

语义搜索：下一代搜索技术？

在目前的互联网应用中,搜索引擎肯定是排名前列的应用之一,几乎每一个上网的人都会使用搜索引擎。因此,围绕搜索引擎形成了一个贯穿行业上下游的产业链。而随着技术的发展,传统的关键词搜索已经逐渐不能满足人们的使用,于是,新一代的搜索技术——语义搜索开始被人们重视起来。     

基于语法与语义分析的代码搜索结果优化

通过示例代码学习简单算法的实现和具体API的使用方式是程序开发人员在软件开发中进行软件复用的高效手段,也是使用代码搜索引擎的主要目的.代码搜索引擎从网页搜索技术发展而来,提供对网络上源代码资源的检索功能,能够有效定位与搜索内容相关的代码,为程序开发人员提供帮助.但现有的代码搜索引擎没有在搜索结果中区别API的实现代码与使用代码,搜索结果存在冗余,导致用户无法快速有效地找到提供有用信息的代码片段.为了使用户更好更快地找到代码搜索目标,阐述了应用语法与语义分析技术从区分API实现代码和使用代码、相似代码聚类、搜索结果摘要3个方面对代码搜索结果进行优化的方法,给出了一个代码搜索引擎的实现,并在实例研究中展示了该方法的有效性.     

基于本体的语义搜索研究综述

基于本体的语义搜索将Web搜索带入一个新时代。它使我们能够在浩瀚的网页中更加快速准确地找到想要的信息。本体具有明确的概念描述,基于本体的搜索能够评测关键词之间的语义差异,从而在文档或者查询中找到更准确的结果。因为所选本体的不同,基于本体的语义搜索方法也会不同。该文总结了多种不同的研究方法,并根据搜索相关技术的分类标准进行了比较。最后通过这些比较,找到今后进一步研究的方向。     

一种语义增强的空间关键词搜索方法

空间关键词搜索立足于查找满足用户查询意图且空间距离相近的兴趣点(point of interest, POI),在地图搜索等领域有着广泛的应用.传统的空间关键词搜索方法仅考虑关键词与POI点在文本上的匹配程度,忽略了查询的语义信息,因而会导致相关结果丢失以及无关结果引入等问题.针对传统方法的局限,提出了语义增强的空间关键词搜索方法S3(semantic-enhanced spatial keyword search).该方法对查询关键词中包含的语义信息进行分析,并结合语义相关性和空间距离对POI点进行有效的排序.S3方法主要有以下2个技术挑战：1)如何对语义信息进行分析.为此,S3引入了知识库对POI数据进行语义扩充,并提出了一种基于图的语义距离度量方式.结合语义距离和空间距离,S3给出POI点的综合排序方案.2)如何在大规模数据上即时地返回top-k搜索结果.针对这一挑战,提出了一种新型的语义-空间混合索引结构GRTree(graph rectangle tree),并研究了有效的剪枝策略.在大规模真实数据集上的实验表明,S3不仅能够返回更为相关的结果,而且有着很好的效率和可扩展性.     

基于开源软件的软件工程实施系统研究

文章介绍了开源软件对软件工程实施各阶段提供的支持,并根据软件工程实施的实际需求,建立了一个基于开源软件的软件工程实施系统.系统采用了基于SOA模式的系统架构,并采用XML中间件实现异构数据的集成.     

复杂语义可搜索加密研究

可搜索加密是一种支持用户在密文上进行关键词检索的密码学原语,能够为用户节省大量的网络和计算开销.进一步地,复杂语义可搜索加密,主要包括通配符可搜索加密、模糊关键词可搜索加密和多关键词可搜索加密,能够支持用户对密文进行各种形式多样化的搜索,而不局限于完整的单关键词搜索,更切合用户的实际搜索情形.本文主要从上述三类复杂语义可搜索加密的研究现状、典型构造、三者关系等方面展开研究,提出一种新的关键词特征提取方式,使得通配符可搜索加密可转化为一般的多关键词可搜索加密,最后讨论了现阶段复杂语义可搜索加密需要解决的问题及未来的研究思路.     

对垂直搜索技术的分析

垂直搜索是针对某一个行业的专业搜索引擎,是搜索引擎的细分和延伸,是对网页库中的某类专门的信息进行一次整合．定向分字段抽取出需要的数据进行处理后再以某种形式返回给用户。相对通用搜索引擎的信息量大、查询不准确、深度不够等提出来的新的搜索引擎服务模式。通过针对某一特定领域、某一特定人群或某一特定需求提供的有一定价值的信息和相关服务。     

基于Petri网可达分析的代码搜索方法

复用已有高质量源代码可提高软件开发效率及软件质量.当前,基于用户提供的输入/输出对的匹配判断是代码语义搜索的主要方法之一,但该方法难以刻画完整代码行为,且仅能处理单输入类型.提出一种针对多种形式类型匹配的代码语义搜索方法.首先将代码集内各个代码片段中数据对象个数及类型的加工过程转换为Petri网模型;其次根据用户查询中...     

基于开源技术的城市地理信息平台构建方法研究

摘 要：针对城市地理信息平台构建过程中存在的数据获取困难、研发成本较高等问题,引入开源技术,对基于开源数据、开源开发平台与开源工具的城市地理信息平台构建技术进行研究。所提出的城市地理信息平台由数据模块与可视化模块 2 部分组成。为构建数据模块,由开源地理信息项目(OSM)获取了建筑与区划数据,并设计了建筑合并算法以提升数据质量。建筑数据随之基于行政区划分级存储,通过由 ASP. NET 构建的数据接口提供给具体应用。可视化模块则基于开源地理信息系统(GIS)项目 Cesium 实现,并设计了完善的用户界面。以北京市为例,完成了原型系统的开发与测试,证实了该技术体系的可行性,通过开源技术降低平台研发成本,推进城市地理信息平台的研究与应用。     

Reliability analysis and optimal version-updating for open source software

Context

Although reliability is a major concern of most open source projects, research on this problem has attracted attention only recently. In addition, the optimal version-dating for open source software considering its special properties is not yet discussed.

Objective

In this paper, the reliability analysis and optimal version-updating for open source software are studied.

Method

A modified non-homogeneous Poisson process model is developed for open source software reliability modeling and analysis. Based on this model, optimal version-updating for open source software is investigated as well. In the decision process, the rapid release strategy and the level of reliability are the two most important factors. However, they are essentially contradicting with each other. In order to consider these two conflicting factors simultaneously, a new decision model based on multi-attribute utility theory is proposed.

Results

Our models are tested on the real world data sets from two famous open source projects: Apache and GNOME. It is found that traditional software reliability models provide overestimations of the reliability of open source software. In addition, the proposed decision model can help management to make a rational decision on the optimal version-updating for open source software.

Conclusion

Empirical results reveal that the proposed model for open source software reliability can describe the failure process more accurately. Furthermore, it can be seen that the proposed decision model can assist management to appropriately determine the optimal version-update time for open source software.     

Empirical analysis of search based algorithms to identify change prone classes of open source software

There are numerous reasons leading to change in software such as changing requirements, changing technology, increasing customer demands, fixing of defects etc. Thus, identifying and analyzing the change-prone classes of the software during software evolution is gaining wide importance in the field of software engineering. This would help software developers to judiciously allocate the resources used for testing and maintenance. Software metrics can be used for constructing various classification models which can be used for timely identification of change prone classes. Search based algorithms which form a subset of machine learning algorithms can be utilized for constructing prediction models to identify change prone classes of software. Search based algorithms use a fitness function to find the best optimal solution among all the possible solutions. In this work, we analyze the effectiveness of hybridized search based algorithms for change prediction. In other words, the aim of this work is to find whether search based algorithms are capable for accurate model construction to predict change prone classes. We have also constructed models using machine learning techniques and compared the performance of these models with the models constructed using Search Based Algorithms. The validation is carried out on two open source Apache projects, Rave and Commons Math. The results prove the effectiveness of hybridized search based algorithms in predicting change prone classes of software. Thus, they can be utilized by the software developers to produce an efficient and better developed software.     

AUSTIN: An open source tool for search based software testing of C programs

ContextDespite the large number of publications on Search-Based Software Testing (SBST), there remain few publicly available tools. This paper introduces AUSTIN, a publicly available open source SBST tool for the C language.¹ The paper is an extension of previous work [1]. It includes a new hill climb algorithm implemented in AUSTIN and an investigation into the effectiveness and efficiency of different pointer handling techniques implemented by AUSTIN’s test data generation algorithms.ObjectiveTo evaluate the different search algorithms implemented within AUSTIN on open source systems with respect to effectiveness and efficiency in achieving branch coverage. Further, to compare AUSTIN against a non-publicly available, state-of-the-art Evolutionary Testing Framework (ETF).MethodFirst, we use example functions from open source benchmarks as well as common data structure implementations to check if the decision procedure for pointer inputs, introduced in this paper, differs in terms of effectiveness and efficiency compared to a simpler alternative that generates random memory graphs. A second empirical study formulates two alternate hypotheses regarding the effectiveness and efficiency of AUSTIN compared to the ETF. These hypotheses are tested using a paired Wilcoxon test.Results and ConclusionThe first study highlights some practical problems with the decision procedure for pointer inputs described in this paper. In particular, if the code under test contains insufficient guard statements to enforce constraints over pointers, then using a constraint solver for pointer inputs may be suboptimal compared to a method that generates random memory graphs. The programs used in the second study do not require any constraint solving for pointer inputs and consist of eight non-trivial, real-world C functions drawn from three embedded automotive software modules. For these functions, AUSTIN is competitive compared to the ETF, achieving an equal or higher branch coverage for six of the functions. In addition, for functions where AUSTIN’s branch coverage is equal or higher, AUSTIN is more efficient than the ETF.     

化学信息学与开源软件

化学信息学研究需要性能强大而又能随时修订的、开放性的软件工具。通过回顾自由软件到开源软件的发展历史,展示开源式程序开发的丰富成就,包括操作系统如Linux、社区如SourceForge和我国的共创软件联盟等,澄清与copyright针锋相对的copyleft式版权概念,介绍并比较多种软件许可证,对开源软件的发展机制进行简要分析,认为开源软件是满足化学信息学要求的最佳选择。     

Code quality analysis in open source software development

Abstract Proponents of open source style software development claim that better software is produced using this model compared with the traditional closed model. However, there is little empirical evidence in support of these claims. In this paper, we present the results of a pilot case study aiming: (a) to understand the implications of structural quality; and (b) to figure out the benefits of structural quality analysis of the code delivered by open source style development. To this end, we have measured quality characteristics of 100 applications written for Linux, using a software measurement tool, and compared the results with the industrial standard that is proposed by the tool. Another target of this case study was to investigate the issue of modularity in open source as this characteristic is being considered crucial by the proponents of open source for this type of software development. We have empirically assessed the relationship between the size of the application components and the delivered quality measured through user satisfaction. We have determined that, up to a certain extent, the average component size of an application is negatively related to the user satisfaction for this application.     

Runtime analysis of search heuristics on software engineering problems

Many software engineering tasks can potentially be automated using search heuristics. However, much work is needed in designing and evaluating search heuristics before this approach can be routinely applied to a software engineering problem. Experimental methodology should be complemented with theoretical analysis to achieve this goal. Recently, there have been significant theoretical advances in the runtime analysis of evolutionary algorithms (EAs) and other search heuristics in other problem domains. We suggest that these methods could be transferred and adapted to gain insight into the behaviour of search heuristics on software engineering problems while automating software engineering.     

开放源代码软件的应用研究

目前,开放源代码的软件开发模式已经越来越多的被采用,其基本思想是通过公开软件的源代码使得不同的开发人员可以互相交流、发现错误从而提升软件质量.在某些环境下运行的软件由于对可靠性的高度要求,采用开放源代码的模式进行软件开发将能最大化的做到这一点,本文试从商业模型、法律规范、实现技术这三个角度论述了开放源代码软件的应用.     

On the security of open source software

Abstract With the rising popularity of so‐called ‘open source’ software there has been increasing interest in both its various benefits and disadvantages. In particular, despite its prominent use in providing many aspects of the Internet's basic infrastructure, many still question the suitability of such software for the commerce‐oriented Internet of the future. This paper evaluates the suitability of open source software with respect to one of the key attributes that tomorrow's Internet will require, namely security. It seeks to present a variety of arguments that have been made, both for and against open source security and analyses in relation to empirical evidence of system security from a previous study. The results represent preliminary quantitative evidence concerning the security issues surrounding the use and development of open source software, in particular relative to traditional proprietary software.     

Organizational adoption of open source software

Organizations and individuals can use open source software (OSS) for free, they can study its internal workings, and they can even fix it or modify it to make it suit their particular needs. These attributes make OSS an enticing technological choice for a company. Unfortunately, because most enterprises view technology as a proprietary differentiating element of their operation, little is known about the extent of OSS adoption in industry and the key drivers behind adoption decisions. In this article we examine factors and behaviors associated with the adoption of OSS and provide empirical findings through data gathered from the US Fortune-1000 companies. The data come from each company's web browsing and serving activities, gathered by sifting through more than 278 million web server log records and analyzing the results of thousands of network probes. We show that the adoption of OSS in large US companies is significant and is increasing over time through a low-churn transition, advancing from applications to platforms. Its adoption is a pragmatic decision influenced by network effects. It is likelier in larger organizations and those with many less productive employees, and is associated with IT and knowledge-intensive work and operating efficiencies.