A systematic review on the functional testing of semantic web services

Semantic web services are gaining more attention as an important element of the emerging semantic web. Therefore, testing semantic web services is becoming a key concern as an essential quality assurance measure. The objective of this systematic literature review is to summarize the current state of the art of functional testing of semantic web services by providing answers to a set of research questions. The review follows a predefined procedure that involves automatically searching 5 well-known digital libraries. After applying the selection criteria to the results, a total of 34 studies were identified as relevant. Required information was extracted from the studies and summarized. Our systematic literature review identified some approaches available for deriving test cases from the specifications of semantic web services. However, many of the approaches are either not validated or the validation done lacks credibility. We believe that a substantial amount of work remains to be done to improve the current state of research in the area of testing semantic web services.     

A novel approach to annotating web service based on interface concept mapping and semantic expansion

With the rapid development of web service technology in these years, traditional standards have been matured during the process of service registry and discovery. However, it is difficult for service requesters to discover satisfactory web services. The reason for this phenomenon is that the traditional service organization mode lacks semantic understanding ability for service function interface. This paper proposes a novel approach to annotating web services. We first adopt domain ontology as a semantic context, and give our general framework of service semantic annotation. Then, interface concept mapping algorithm and service interface expansion algorithm are respectively presented in detail. Finally, the generation process of semantic web service repository is presented based on preceding algorithms. Simulation experiment results demonstrate that annotated web services by the proposed method can more satisfy requirements for service requesters than traditional ones by service matchmaking engine. It can get better service discovery effectiveness.     

Effective image annotation for searches using multilevel semantics

There is an increasing need for automatic image annotation tools to enable effective image searching in digital libraries. In this paper, we present a novel probabilistic model for image annotation based on content-based image retrieval techniques and statistical analysis. One key difficulty in applying statistical methods to the annotation of images is that the number of manually labeled images used to train the methods is normally insufficient. Numerous keywords cannot be correctly assigned to appropriate images due to lacking or missing information in the labeled image databases. To deal with this challenging problem, we also propose an enhanced model in which the annotated keywords of a new image are defined in terms of their similarity at different semantic levels, including the image level, keyword level, and concept level. To avoid missing some relevant keywords, the model labels the keywords with the same concepts as the new image. Our experimental results show that the proposed models are effective for annotating images that have different qualities of training data.     

Standards for image annotation using Semantic Web

The impetus behind Semantic Web research remains the vision of supplementing availability with utility; that is, the World Wide Web provides availability of digital media, but the Semantic Web will allow presently available digital media to be used in unseen ways. An example of such an application is multimedia retrieval. At present, there are vast amounts of digital media available on the web. Once this media gets associated with machine-understandable metadata, the web can serve as a potentially unlimited supplier for multimedia web services, which could populate themselves by searching for keywords and subsequently retrieving images or articles, which is precisely the type of system that is proposed in this paper. Such a system requires solid interoperability, a central ontology, semantic agent search capabilities, and standards. Specifically, this paper explores this cross-section of image annotation and Semantic Web services, models the web service components that constitute such a system, discusses the sequential, cooperative execution of these Semantic Web services, and introduces intelligent storage of image semantics as part of a semantic link space.     

Web服务自动语义标注的本体定位方法研究

面向服务架构中,分布式网络计算的实现依赖于服务交互问题的有效解决。为此,服务接口必须采用机器可理解的方式描述,从而为服务的动态发现和组合提供底层支持。服务语义标注技术满足了上述需求,它是指通过共享域本体中机器可理解的元数据表示服务元素。本文将服务语义标注过程分解为域标注和概念标注两个阶段,重点针对域标注注问题,并提出了一种基于机器学习的域标注算法,对实际服务的标注实验验证了该算法的有效性     

基于本体知识库的自动语义标注*

为了产生语义Web中的元数据,需要提取Web文档中的语义信息。面对海量的Web文档,自动语义标注相对人工和半自动的语义标注是可行的方法。提出的基于本体知识库的自动语义标注方法,旨在提高标注的质量。为识别出文档中的候选命名实体,设计了语义词典的逻辑结构,论述了以实体之间语义关联路径计算语义距离的方法。语义标注中的复杂问题是语义消歧,提出了基于最短路径的语义消歧方法和基于n-gram的语义消歧方法。采用这种方法对文档进行语义标注,将标注结果持久化为语义索引,为实现语义信息检索提供基础。针对构建的测试数据集,进行的标注实验表明该方法能够依据本体知识库,有效地对Web文档进行自动语义标注。     

Web application testing: A systematic literature review

ContextThe web has had a significant impact on all aspects of our society. As our society relies more and more on the web, the dependability of web applications has become increasingly important. To make these applications more dependable, for the past decade researchers have proposed various techniques for testing web-based software applications. Our literature search for related studies retrieved 193 papers in the area of web application testing, which have appeared between 2000 and 2013.ObjectiveAs this research area matures and the number of related papers increases, it is important to systematically identify, analyze, and classify the publications and provide an overview of the trends and empirical evidence in this specialized field.MethodsWe systematically review the body of knowledge related to functional testing of web application through a systematic literature review (SLR) study. This SLR is a follow-up and complimentary study to a recent systematic mapping (SM) study that we conducted in this area. As part of this study, we pose three sets of research questions, define selection and exclusion criteria, and synthesize the empirical evidence in this area.ResultsOur pool of studies includes a set of 95 papers (from the 193 retrieved papers) published in the area of web application testing between 2000 and 2013. The data extracted during our SLR study is available through a publicly-accessible online repository. Among our results are the followings: (1) the list of test tools in this area and their capabilities, (2) the types of test models and fault models proposed in this domain, (3) the way the empirical studies in this area have been designed and reported, and (4) the state of empirical evidence and industrial relevance.ConclusionWe discuss the emerging trends in web application testing, and discuss the implications for researchers and practitioners in this area. The results of our SLR can help researchers to obtain an overview of existing web application testing approaches, fault models, tools, metrics and empirical evidence, and subsequently identify areas in the field that require more attention from the research community.     

基于语义分类的文物图像标注研究

由于图像数据中普遍存在的“语义鸿沟”问题,传统的基于内容的图像检索技术对于数字图书馆中的图像检索往往力不从心。而图像标注能有效地弥补语义的缺失。文中分析了图像语义标注的现状以及存在的问题,提出了基于语义分类的文物语义标注方法。算法首先通过构建一个Bayes语义分类器对待标注图像进行语义分类,进而通过在语义类内部建立基于统计的标注模型,实现了图像的语义标注。在针对文物图像进行标注的实验中,该方法获得了较好的标注准确率和效率。     

Quality models for web services: A systematic mapping

ContextQuality of Service (QoS) is a major issue in various web service related activities. Quality models have been proposed as the engineering artefact to provide a common framework of understanding for QoS, by defining the quality factors that apply to web service usage.ObjectiveThe goal of this study is to evaluate the current state of the art of the proposed quality models for web services, specifically: (1) which are these proposals and how are they related; (2) what are their structural characteristics; (3) what quality factors are the most and least addressed; and (4) what are their most consolidated definitions.MethodWe have conducted a systematic mapping by defining a robust protocol that combines automatic and manual searches from different sources. We used a rigorous method to elicitate the keywords from the research questions and a selection criteria to retrieve the final papers to evaluate. We have adopted the ISO/IEC 25010 standard to articulate our analysis.ResultsWe have evaluated 47 different quality models from 65 papers that fulfilled the selection criteria. By analyzing in depth these quality models, we have: (1) distributed the proposals along the time dimension and identified their relationships; (2) analyzed their size (visualizing the number of nodes and levels) and definition coverage (as indicator of quality of the proposals); (3) quantified the coverage of the different ISO/IEC 25010 quality factors by the proposals; (4) identified the quality factors that appeared in at least 30% of the surveyed proposals and provided the most consolidated definitions for them.ConclusionsWe believe that this panoramic view on the anatomy of the quality models for web services may be a good reference for prospective researchers and practitioners in the field and especially may help avoiding the definition of new proposals that do not align with current research.     

基于本体集成的语义标注模型设计

语义Web的全面实现需借助于语义标注,标注网页信息会涉及到多个本体.据此,通过研究桥本体,提出一个在本体集成的基础上建立起来的多本体语义标注模型.该模型利用桥本体集成顶层本体和多个领域本体,同时借助基于本体的信息抽取技术对网页进行语义标注,并将标注信息存入标注库,使标注信息与网页分离,提高语义检索的效率.通过举例说明了本模型的合理性.     

Identifying refactoring opportunities in object-oriented code: A systematic literature review

ContextIdentifying refactoring opportunities in object-oriented code is an important stage that precedes the actual refactoring process. Several techniques have been proposed in the literature to identify opportunities for various refactoring activities.ObjectiveThis paper provides a systematic literature review of existing studies identifying opportunities for code refactoring activities.MethodWe performed an automatic search of the relevant digital libraries for potentially relevant studies published through the end of 2013, performed pilot and author-based searches, and selected 47 primary studies (PSs) based on inclusion and exclusion criteria. The PSs were analyzed based on a number of criteria, including the refactoring activities, the approaches to refactoring opportunity identification, the empirical evaluation approaches, and the data sets used.ResultsThe results indicate that research in the area of identifying refactoring opportunities is highly active. Most of the studies have been performed by academic researchers using nonindustrial data sets. Extract Class and Move Method were found to be the most frequently considered refactoring activities. The results show that researchers use six primary existing approaches to identify refactoring opportunities and six approaches to empirically evaluate the identification techniques. Most of the systems used in the evaluation process were open-source, which helps to make the studies repeatable. However, a relatively high percentage of the data sets used in the empirical evaluations were small, which limits the generality of the results.ConclusionsIt would be beneficial to perform further studies that consider more refactoring activities, involve researchers from industry, and use large-scale and industrial-based systems.     

A systematic mapping study of web application testing

ContextThe Web has had a significant impact on all aspects of our society. As our society relies more and more on the Web, the dependability of web applications has become increasingly important. To make these applications more dependable, for the past decade researchers have proposed various techniques for testing web-based software applications. Our literature search for related studies retrieved 147 papers in the area of web application testing, which have appeared between 2000 and 2011.ObjectiveAs this research area matures and the number of related papers increases, it is important to systematically identify, analyze, and classify the publications and provide an overview of the trends in this specialized field.MethodWe review and structure the body of knowledge related to web application testing through a systematic mapping (SM) study. As part of this study, we pose two sets of research questions, define selection and exclusion criteria, and systematically develop and refine a classification schema. In addition, we conduct a bibliometrics analysis of the papers included in our study.ResultsOur study includes a set of 79 papers (from the 147 retrieved papers) published in the area of web application testing between 2000 and 2011. We present the results of our systematic mapping study. Our mapping data is available through a publicly-accessible repository. We derive the observed trends, for instance, in terms of types of papers, sources of information to derive test cases, and types of evaluations used in papers. We also report the demographics and bibliometrics trends in this domain, including top-cited papers, active countries and researchers, and top venues in this research area.ConclusionWe discuss the emerging trends in web application testing, and discuss the implications for researchers and practitioners in this area. The results of our systematic mapping can help researchers to obtain an overview of existing web application testing approaches and indentify areas in the field that require more attention from the research community.     

On semantic annotation of decision models

The growth of service sector in recent years has led to renewed research interests in the design and management of service systems. Decision support systems (DSS) play an important role in supporting this endeavor, through management of organizational resources such as models and data, thus forming the “back stage” of service systems. In this article, we identify the requirements for semantically annotating decision models and propose a model representation scheme, termed Semantically Annotated Structure Modeling Markup Language (SA-SMML) that extends Structure Modeling Markup Language (SMML) by incorporating mechanisms for linking semantic models such as ontologies that represent problem domain knowledge concepts. This model representation format is also amenable to a scalable Service-Oriented Architecture (SOA) for managing models in distributed environments. The proposed model representation technique leverages recent advances in the areas of semantic web, and semantic web services. Along with design considerations, we demonstrate the utility of this representation format with an illustrative usage scenarios with a particular emphasis on model discovery and composition in a distributed environment.     

Process models in the practice of distributed software development: A systematic review of the literature

ContextDistributed Software Development (DSD) has recently become an active research area. Although considerable research effort has been made in this area, as yet, no agreement has been reached as to an appropriate process model for DSD.PurposeThis paper is intended to identify and synthesize papers that describe process models for distributed software development in the context of overseas outsourcing, i.e. “offshoring”.MethodWe used a systematic review methodology to search seven digital libraries and one topic-specific conference.ResultsWe found 27 primary studies describing stage-related DSD process models. Only five of such studies looked into outsourcing to a subsidiary company (i.e. “internal offshoring”). Nineteen primary studies addressed the need for DSD process models. Eight primary studies and three literature surveys described stage-based DSD process models, but only three of such models were empirically evaluated.ConclusionWe need more research aimed at internal offshoring. Furthermore, proposed models need to be empirically validated.     

A systematic review of systematic review process research in software engineering

ContextMany researchers adopting systematic reviews (SRs) have also published papers discussing problems with the SR methodology and suggestions for improving it. Since guidelines for SRs in software engineering (SE) were last updated in 2007, we believe it is time to investigate whether the guidelines need to be amended in the light of recent research.ObjectiveTo identify, evaluate and synthesize research published by software engineering researchers concerning their experiences of performing SRs and their proposals for improving the SR process.MethodWe undertook a systematic review of papers reporting experiences of undertaking SRs and/or discussing techniques that could be used to improve the SR process. Studies were classified with respect to the stage in the SR process they addressed, whether they related to education or problems faced by novices and whether they proposed the use of textual analysis tools.ResultsWe identified 68 papers reporting 63 unique studies published in SE conferences and journals between 2005 and mid-2012. The most common criticisms of SRs were that they take a long time, that SE digital libraries are not appropriate for broad literature searches and that assessing the quality of empirical studies of different types is difficult.ConclusionWe recommend removing advice to use structured questions to construct search strings and including advice to use a quasi-gold standard based on a limited manual search to assist the construction of search stings and evaluation of the search process. Textual analysis tools are likely to be useful for inclusion/exclusion decisions and search string construction but require more stringent evaluation. SE researchers would benefit from tools to manage the SR process but existing tools need independent validation. Quality assessment of studies using a variety of empirical methods remains a major problem.     

Statistical modeling and conceptualization of natural images

Multi-level annotation of images is a promising solution to enable semantic image retrieval by using various keywords at different semantic levels. In this paper, we propose a multi-level approach to interpret and annotate the semantics of natural images by using both the dominant image components and the relevant semantic image concepts. In contrast to the well-known image-based and region-based approaches, we use the concept-sensitive salient objects as the dominant image components to achieve automatic image annotation at the content level. By using the concept-sensitive salient objects for image content representation and feature extraction, a novel image classification technique is developed to achieve automatic image annotation at the concept level. To detect the concept-sensitive salient objects automatically, a set of detection functions are learned from the labeled image regions by using support vector machine (SVM) classifiers with an automatic scheme for searching the optimal model parameters. To generate the semantic image concepts, the finite mixture models are used to approximate the class distributions of the relevant concept-sensitive salient objects. An adaptive EM algorithm has been proposed to determine the optimal model structure and model parameters simultaneously. In addition, a large number of unlabeled samples have been integrated with a limited number of labeled samples to achieve more effective classifier training and knowledge discovery. We have also demonstrated that our algorithms are very effective to enable multi-level interpretation and annotation of natural images.     

SentiML ++: an extension of the SentiML sentiment annotation scheme

The amount of opinionated data on the web has exponentially increased especially after the emergence of online social networks. To deal with these huge deluge of data, we need to have robust mechanisms that can help identify all aspects of opinion segment and support the automatic processing of opinion data. Recently, there have been a few developments made in this direction, and different sentiment annotation schemes have been proposed such as the SentiML, OpinionMiningML, and EmotionML. In this work, we propose SentiML++, an extension of SentiML with a focus on annotating opinions, and further answering aspects of the general question “who has what opinion about whom in which context?”. A detailed comparison with SentiML and other existing annotation schemes is also presented. The data collection annotated with SentiML has been annotated with SentiML++ and is available for download for further research purposes. Experiments with data collections annotated with SentiML and SentiML++ proves that SentiML++ is a significant and valuable addition to SentiML.     

基于文本和视觉特征融合的Web动画素材标注

为了提高对Web动画素材的组织、管理,该文提出了基于文本特征和视觉特征融合的Web动画素材标注算法。首先利用自动提取的Web动画素材上下文信息,结合Web动画素材名称、页面主题、URL以及ALT等属性组成特征集,提取出文本关键字;然后利用视觉与标注字之间的相关性,对自动提取的标注字进行过滤,实现Web动画素材的自动标注。实验表明该文提出的基于文本特征和视觉特征融合的Web动画素材标注算法可有效地应用于Web动画素材自动标注。