Requirements for product derivation support: Results from a systematic literature review and an expert survey

ContextAn increasing number of publications in product line engineering address product derivation, i.e., the process of building products from reusable assets. Despite its importance, there is still no consensus regarding the requirements for product derivation support.ObjectiveOur aim is to identify and validate requirements for tool-supported product derivation.MethodWe identify the requirements through a systematic literature review and validate them with an expert survey.ResultsWe discuss the resulting requirements and provide implementation examples from existing product derivation approaches.ConclusionsWe conclude that key requirements are emerging in the research literature and are also considered relevant by experts in the field.     

A systematic review of domain analysis solutions for product lines

Domain analysis is crucial and central to software product line engineering (SPLE) as it is one of the main instruments to decide what to include in a product and how it should fit in to the overall software product line. For this reason many domain analysis solutions have been proposed both by researchers and industry practitioners. Domain analysis comprises various modeling and scoping activities. This paper presents a systematic review of all the domain analysis solutions presented until 2007. The goal of the review is to analyze the level of industrial application and/or empirical validation of the proposed solutions with the purpose of mapping maturity in terms of industrial application, as well as to what extent proposed solutions might have been evaluated in terms of usability and usefulness. The finding of this review indicates that, although many new domain analysis solutions for software product lines have been proposed over the years, the absence of qualitative and quantitative results from empirical application and/or validation makes it hard to evaluate the potential of proposed solutions with respect to their usability and/or usefulness for industry adoption. The detailed results of the systematic review can be used by individual researchers to see large gaps in research that give opportunities for future work, and from a general research perspective lessons can be learned from the absence of validation as well as from good examples presented. From an industry practitioner view, the results can be used to gauge as to what extent solutions have been applied and/or validated and in what manner, both valuable as input prior to industry adoption of a domain analysis solution.     

A systematic review of quality attributes and measures for software product lines

It is widely accepted that software measures provide an appropriate mechanism for understanding, monitoring, controlling, and predicting the quality of software development projects. In software product lines (SPL), quality is even more important than in a single software product since, owing to systematic reuse, a fault or an inadequate design decision could be propagated to several products in the family. Over the last few years, a great number of quality attributes and measures for assessing the quality of SPL have been reported in literature. However, no studies summarizing the current knowledge about them exist. This paper presents a systematic literature review with the objective of identifying and interpreting all the available studies from 1996 to 2010 that present quality attributes and/or measures for SPL. These attributes and measures have been classified using a set of criteria that includes the life cycle phase in which the measures are applied; the corresponding quality characteristics; their support for specific SPL characteristics (e.g., variability, compositionality); the procedure used to validate the measures, etc. We found 165 measures related to 97 different quality attributes. The results of the review indicated that 92% of the measures evaluate attributes that are related to maintainability. In addition, 67% of the measures are used during the design phase of Domain Engineering, and 56% are applied to evaluate the product line architecture. However, only 25% of them have been empirically validated. In conclusion, the results provide a global vision of the state of the research within this area in order to help researchers in detecting weaknesses, directing research efforts, and identifying new research lines. In particular, there is a need for new measures with which to evaluate both the quality of the artifacts produced during the entire SPL life cycle and other quality characteristics. There is also a need for more validation (both theoretical and empirical) of existing measures. In addition, our results may be useful as a reference guide for practitioners to assist them in the selection or the adaptation of existing measures for evaluating their software product lines.     

Requirements engineering for software product lines: A systematic literature review

ContextSoftware product line engineering (SPLE) is a growing area showing promising results in research and practice. In order to foster its further development and acceptance in industry, it is necessary to assess the quality of the research so that proper evidence for adoption and validity are ensured. This holds in particular for requirements engineering (RE) within SPLE, where a growing number of approaches have been proposed.ObjectiveThis paper focuses on RE within SPLE and has the following goals: assess research quality, synthesize evidence to suggest important implications for practice, and identify research trends, open problems, and areas for improvement.MethodA systematic literature review was conducted with three research questions and assessed 49 studies, dated from 1990 to 2009.ResultsThe evidence for adoption of the methods is not mature, given the primary focus on toy examples. The proposed approaches still have serious limitations in terms of rigor, credibility, and validity of their findings. Additionally, most approaches still lack tool support addressing the heterogeneity and mostly textual nature of requirements formats as well as address only the proactive SPLE adoption strategy.ConclusionsFurther empirical studies should be performed with sufficient rigor to enhance the body of evidence in RE within SPLE. In this context, there is a clear need for conducting studies comparing alternative methods. In order to address scalability and popularization of the approaches, future research should be invested in tool support and in addressing combined SPLE adoption strategies.     

A systematic review of evaluation of variability management approaches in software product lines

Context

Variability management (VM) is one of the most important activities of software product-line engineering (SPLE), which intends to develop software-intensive systems using platforms and mass customization. VM encompasses the activities of eliciting and representing variability in software artefacts, establishing and managing dependencies among different variabilities, and supporting the exploitation of the variabilities for building and evolving a family of software systems. Software product line (SPL) community has allocated huge amount of effort to develop various approaches to dealing with variability related challenges during the last two decade. Several dozens of VM approaches have been reported. However, there has been no systematic effort to study how the reported VM approaches have been evaluated.

Objective

The objectives of this research are to review the status of evaluation of reported VM approaches and to synthesize the available evidence about the effects of the reported approaches.

Method

We carried out a systematic literature review of the VM approaches in SPLE reported from 1990s until December 2007.

Results

We selected 97 papers according to our inclusion and exclusion criteria. The selected papers appeared in 56 publication venues. We found that only a small number of the reviewed approaches had been evaluated using rigorous scientific methods. A detailed investigation of the reviewed studies employing empirical research methods revealed significant quality deficiencies in various aspects of the used quality assessment criteria. The synthesis of the available evidence showed that all studies, except one, reported only positive effects.

Conclusion

The findings from this systematic review show that a large majority of the reported VM approaches have not been sufficiently evaluated using scientifically rigorous methods. The available evidence is sparse and the quality of the presented evidence is quite low. The findings highlight the areas in need of improvement, i.e., rigorous evaluation of VM approaches. However, the reported evidence is quite consistent across different studies. That means the proposed approaches may be very beneficial when they are applied properly in appropriate situations. Hence, it can be concluded that further investigations need to pay more attention to the contexts under which different approaches can be more beneficial.     

A systematic mapping study of software product lines testing

Context

In software development, Testing is an important mechanism both to identify defects and assure that completed products work as specified. This is a common practice in single-system development, and continues to hold in Software Product Lines (SPL). Even though extensive research has been done in the SPL Testing field, it is necessary to assess the current state of research and practice, in order to provide practitioners with evidence that enable fostering its further development.

Objective

This paper focuses on Testing in SPL and has the following goals: investigate state-of-the-art testing practices, synthesize available evidence, and identify gaps between required techniques and existing approaches, available in the literature.

Method

A systematic mapping study was conducted with a set of nine research questions, in which 120 studies, dated from 1993 to 2009, were evaluated.

Results

Although several aspects regarding testing have been covered by single-system development approaches, many cannot be directly applied in the SPL context due to specific issues. In addition, particular aspects regarding SPL are not covered by the existing SPL approaches, and when the aspects are covered, the literature just gives brief overviews. This scenario indicates that additional investigation, empirical and practical, should be performed.

Conclusion

The results can help to understand the needs in SPL Testing, by identifying points that still require additional investigation, since important aspects regarding particular points of software product lines have not been addressed yet.     

The use of software product lines for business process management: A systematic literature review

ContextBusiness Process Management (BPM) is a potential domain in which Software Product Line (PL) can be successfully applied. Including the support of Service-oriented Architecture (SOA), BPM and PL may help companies achieve strategic alignment between business and IT.ObjectivePresenting the results of a study undertaken to seek and assess PL approaches for BPM through a Systematic Literature Review (SLR). Moreover, identifying the existence of dynamic PL approaches for BPM.MethodA SLR was conducted with four research questions formulated to evaluate PL approaches for BPM.Results63 papers were selected as primary studies according to the criteria established. From these primary studies, only 15 papers address the specific dynamic aspects in the context evaluated. Moreover, it was found that PLs only partially address the BPM lifecycle since the last business process phase is not a current concern on the found approaches.ConclusionsThe found PL approaches for BPM only cover partially the BPM lifecycle, not taking into account the last phase which restarts the lifecycle. Moreover, no wide dynamic PL proposal was found for BPM, but only the treatment of specific dynamic aspects. The results indicate that PL approaches for BPM are still at an early stage and gaining maturity.     

A survey on expert finding techniques

Finding experts in specified areas is an important task and has attracted much attention in the information retrieval community. Research on this topic has made significant progress in the past few decades and various techniques have been proposed. In this survey, we review the state-of-the-art methods in expert finding and summarize these methods into different categories based on their underlying algorithms and models. We also introduce the most widely used data collection for evaluating expert finding systems, and discuss future research directions.     

A multi source product reputation model

Product reputation model is very important for customers and manufacturers in order to make decisions. Several product reputation models are proposed in literature which use customer reviews in order to compute reputation values. However, the aggregation methods used are not able to estimate a good reputation value when some ratings are false. Some of these aggregation methods are not robust to false and biased ratings because a single false rating is enough to change the result. Others are robust to false ratings but not able to reflect the recent opinions about product quickly. In addition, most of the product reputation models are based on single source, therefore suffer from availability and vulnerability issues. In this paper, we propose a multi-source product reputation model where robust and strategy proof aggregation methods are used. A source credibility measure method is proposed, which uses four factors to determine malicious sources. Furthermore, a suitable decay principle for product reputation is also introduced in order to reflect the newest opinions quickly. The results show that proposed model is robust, strategy proof and able to provide a good estimation even if some ratings are false.     

A systematic test case selection methodology for product lines: results and insights from an industrial case study

In the context of product lines, test case selection aims at obtaining a set of relevant test cases for a product from the entire set of test cases available for a product line. While working on a research-based innovation project on automated testing of product lines of Video Conferencing Systems (VCSs) developed by Cisco, we felt the need to devise a cost-effective way of selecting relevant test cases for a product. To fulfill such need, we propose a systematic and automated test selection methodology using: 1) Feature Model for Testing (FM_T) to capture commonalities and variabilities of a product line; 2) Component Family Model for Testing (CFM_T) to model the structure of test case repository; 3) A tool to automatically build restrictions from CFM_T to FM_T and traces from CFM_T to the actual test cases. Using our methodology, a test engineer is only required to select relevant features through FM_T at a higher level of abstraction for a product and the corresponding test cases will be obtained automatically. We evaluate our methodology by applying it to a VCS product line called Saturn with seven commercial products and the results show that our methodology can significantly reduce cost measured as test selection time and at the same time achieves higher effectiveness (feature coverage, feature pairwise coverage and fault detection) as compared with the current manual process. Moreover, we conduct a questionnaire-based study to solicit the views of test engineers who are involved in developing FM_T and CFM_T. The results show that test engineers are positive about adapting our methodology in their current practice. Finally, we present a set of lessons learnt while applying product line engineering at Cisco for test case selection.     

A classification and systematic review of product line feature model defects

Product line (PL)-based development is a thriving research area to develop software-intensive systems. Feature models (FMs) facilitate derivation of valid products from a PL by managing commonalities and variabilities among software products. However, the researchers in academia as well as in the industries experience difficulties in quality assessment of FMs. The increasing complexity and size of FMs may lead to defects, which outweigh the benefits of PL. This paper provides a systematic literature review and key research issues related to the FM defects in PL. We derive a typology of FM defects according to their level of importance. The information on defects’ identification and explanations are provided with formalization. Further, corrective explanations are presented which incorporates various techniques used to fix defects with their implementation. This information would help software engineering community by enabling developers or modelers to find the types of defects and their causes and to choose an appropriate technique to fix defects in order to produce defect-free products from FMs, thereby enhancing the overall quality of PL-based development.

     

A systematic mapping study of search-based software engineering for software product lines

ContextSearch-Based Software Engineering (SBSE) is an emerging discipline that focuses on the application of search-based optimization techniques to software engineering problems. Software Product Lines (SPLs) are families of related software systems whose members are distinguished by the set of features each one provides. SPL development practices have proven benefits such as improved software reuse, better customization, and faster time to market. A typical SPL usually involves a large number of systems and features, a fact that makes them attractive for the application of SBSE techniques which are able to tackle problems that involve large search spaces.ObjectiveThe main objective of our work is to identify the quantity and the type of research on the application of SBSE techniques to SPL problems. More concretely, the SBSE techniques that have been used and at what stage of the SPL life cycle, the type of case studies employed and their empirical analysis, and the fora where the research has been published.MethodA systematic mapping study was conducted with five research questions and assessed 77 publications from 2001, when the term SBSE was coined, until 2014.ResultsThe most common application of SBSE techniques found was testing followed by product configuration, with genetic algorithms and multi-objective evolutionary algorithms being the two most commonly used techniques. Our study identified the need to improve the robustness of the empirical evaluation of existing research, a lack of extensive and robust tool support, and multiple avenues worthy of further investigation.ConclusionsOur study attested the great synergy existing between both fields, corroborated the increasing and ongoing interest in research on the subject, and revealed challenging open research questions.     

Big data analytics capabilities: a systematic literature review and research agenda

With big data growing rapidly in importance over the past few years, academics and practitioners have been considering the means through which they can incorporate the shifts these technologies bring into their competitive strategies. To date, emphasis has been on the technical aspects of big data, with limited attention paid to the organizational changes they entail and how they should be leveraged strategically. As with any novel technology, it is important to understand the mechanisms and processes through which big data can add business value to companies, and to have a clear picture of the different elements and their interdependencies. To this end, the present paper aims to provide a systematic literature review that can help to explain the mechanisms through which big data analytics (BDA) lead to competitive performance gains. The research framework is grounded on past empirical work on IT business value research, and builds on the resource-based view and dynamic capabilities view of the firm. By identifying the main areas of focus for BDA and explaining the mechanisms through which they should be leveraged, this paper attempts to add to literature on how big data should be examined as a source of competitive advantage. To this end, we identify gaps in the extant literature and propose six future research themes.     

A systematic review of research on open source software in commercial software product development

Context

The popularity of the open source software development in the last decade, has brought about an increased interest from the industry on how to use open source components, participate in the open source community, build business models around this type of software development, and learn more about open source development methodologies. There is a need to understand the results of research in this area.

Objective

Since there is a need to understand conducted research, the aim of this study is to summarize the findings of research that has ben carried out on usage of open source components and development methodologies by the industry, as well as companies’ participation in the open source community.

Method

Systematic review through searches in library databases and manual identification of articles from the open source conference. The search was first carried out in May 2009 and then once again in May 2010.

Results

In 2009, 237 articles were first found, from which 19 were selected based on content and quality, and in 2010, 76 new articles were found from which four were selected. Twenty three articles were identified in total.

Conclusions

The articles could be divided into four categories: open source as part of component based software engineering, business models with open source in commercial organization, company participation in open source development communities, and usage of open source processes within a company.     

Reengineering legacy applications into software product lines: a systematic mapping

Software Product Lines (SPLs) are families of systems that share common assets allowing a disciplined reuse. Rarely SPLs start from scratch, instead they usually start from a set of existing systems that undergo a reengineering process. Many approaches to conduct the reengineering process have been proposed and documented in research literature. This scenario is a clear testament to the interest in this research area. We conducted a systematic mapping study to provide an overview of the current research on reengineering of existing systems to SPLs, identify the community activity in regarding of venues and frequency of publications in this field, and point out trends and open issues that could serve as references for future research. This study identified 119 relevant publications. These primary sources were classified in six different dimensions related to reengineering phases, strategies applied, types of systems used in the evaluation, input artefacts, output artefacts, and tool support. The analysis of the results points out the existence of a consolidate community on this topic and a wide range of strategies to deal with different phases and tasks of the reengineering process, besides the availability of some tools. We identify some open issues and areas for future research such as the implementation of automation and tool support, the use of different sources of information, need for improvements in the feature management, the definition of ways to combine different strategies and methods, lack of sophisticated refactoring, need for new metrics and measures and more robust empirical evaluation. Reengineering of existing systems into SPLs is an active research topic with real benefits in practice. This mapping study motivates new research in this field as well as the adoption of systematic reuse in software companies.     

支持IPv6的多视点视频点播系统*

介绍了多视点视频点播系统的框架结构,提出了多视点视频系统的关键技术、网络传输控制以及具体实现方法。     

Factors affecting response rates of the web survey: A systematic review

The lower response rate in web surveys has been a major concern for survey researchers. The literature has sought to identify a wide variety of factors that affect response rates in web surveys. In this article, we developed a conceptual model of the web survey process and use the model to systematically review a wide variety of factors influencing the response rate in the stage of survey development, survey delivery, survey completion, and survey return. Practical suggestion and future research directions on how to increase the response rate are discussed.     

A systematic data-mining-based methodology for product family design and product configuration

Product family design and product configuration based on data mining technology is identified as an intelligent and automated means to improve the efficiency of product development. However, few of previous literatures have proposed systematic product family design method based on data mining technology. To make up for this deficiency, this research put forward a systematic data-mining-based method for product family design and product configuration. First, the customer requirement information and product engineering information in the historical order are formatted into structural data. Second, principal component analysis is performed on historical orders to extract the customers' differentiated needs. Third, association rule algorithm is introduced to mine the rules between differentiated needs and module instances in the historical orders, thus obtained the configuration knowledge between customer needs and product engineer. Forth, the mined rules are used to construct association rule-based classifier (CBA) that is employed to sort out the best product configuration schemes as popular product variants. Fifth, sequence alignment technique is employed to identify modules for popular product variants, so that the module instances are divided into optional, common and special module, respectively, thereby the product platform is generated based on common modules. Finally, according to new customer needs, the CBA classifier is used to recommend the best configuration schemes, and then popular product variants are configured based on the product platform. The feasibility of the proposed method is demonstrated by the product family design example of desktop computer hosts.     

A survey on run-time supporting platforms for cyber physical systems

Cyber physical systems (CPSs) incorporate computation, communication, and physical processes. The deep coupling and continuous interaction between such processes lead to a significant increase in complexity in the design and implementation of CPSs. Consequently, whereas developing CPSs from scratch is inefficient, developing them with the aid of CPS run-time sup-porting platforms can be efficient. In recent years, much research has been actively conducted on CPS run-time supporting plat-forms. However, few surveys have been conducted on these platforms. In this paper, we analyze and evaluate existing CPS run-time supporting platforms by first classifying them into three categories from the viewpoint of software architecture: com-ponent-based platforms, service-based platforms, and agent-based platforms. Then, for each type, we detail its design philosophy, key technical problems, and corresponding solutions with specific use cases. Subsequently, we compare existing platforms from two aspects: construction approaches for CPS tasks and support for non-functional properties. Finally, we outline several im-portant future research issues.