Cultural influence on requirements engineering activities: a systematic literature review and analysis

Requirements Engineering - Requirements engineering (RE) involves the critical activities required to capture customers’ requirements/needs accurately. RE is a communication-intensive...     

Software requirements testing approaches: a systematic literature review

Requirements Engineering - Testing a software system is an important step approach to ensuring quality, safety, and reliability in safety-critical systems (SCS). Several authors have published new...     

On the generation of requirements specifications from software engineering models: A systematic literature review

System and software requirements documents play a crucial role in software engineering in that they must both communicate requirements to clients in an understandable manner and define requirements in precise detail for system developers. The benefits of both lists of textual requirements (usually written in natural language) and software engineering models (usually specified in graphical form) can be brought together by combining the two approaches in the specification of system and software requirements documents. If, moreover, textual requirements are generated from models in an automatic or closely monitored form, the effort of specifying those requirements is reduced and the completeness of the specification and the management of the requirements traceability are improved. This paper presents a systematic review of the literature related to the generation of textual requirements specifications from software engineering models.     

A systematic review of security requirements engineering

One of the most important aspects in the achievement of secure software systems in the software development process is what is known as Security Requirements Engineering. However, very few reviews focus on this theme in a systematic, thorough and unbiased manner, that is, none of them perform a systematic review of security requirements engineering, and there is not, therefore, a sufficiently good context in which to operate. In this paper we carry out a systematic review of the existing literature concerning security requirements engineering in order to summarize the evidence regarding this issue and to provide a framework/background in which to appropriately position new research activities.     

Bayesian networks for enhancement of requirements engineering: a literature review

Requirements analysis is the software engineering stage that is closest to the users’ world. It also involves tasks that are knowledge intensive. Thus, the use of Bayesian networks (BNs) to model this knowledge would be a valuable aid. These probabilistic models could manage the imprecision and ambiguities usually present in requirements engineering (RE). In this work, we conduct a literature review focusing on where and how BNs are applied on subareas of RE in order to identify which gaps remain uncovered and which methods might engineers employ to incorporate this intelligent technique into their own requirements processes. The scarcity of identified studies (there are only 20) suggests that not all RE areas have been properly investigated in the literature. The evidence available for adopting BNs into RE is sufficiently mature yet the methods applied are not easily translatable to other topics. Nonetheless, there are enough studies supporting the applicability of synergistic cooperation between RE and BNs. This work provides a background for understanding the current state of research encompassing RE and BNs. Functional, non-functional and -ilities requirements artifacts are enhanced by the use of BNs. These models were obtained by interacting with experts or by learning from databases. The most common criticism from the point of view of BN experts is that the models lack validation, whereas requirements engineers point to the lack of a clear application method for BNs and the lack of tools for incorporating them as built-in help functions.     

Exploring service-oriented system engineering challenges: a systematic literature review

Service-oriented system engineering (SOSE) has drawn increasing attention since service-oriented computing was introduced in the beginning of this decade. A large number of SOSE challenges that call for special software engineering efforts have been proposed in the research community. Our goal is to gain insight into the current status of SOSE research issues as published to date. To this end, we conducted a systematic literature review exploring SOSE challenges that have been claimed between January 2000 and July 2008. This paper presents the results of the systematic review as well as the empirical research method we followed. In this review, of the 729 publications that have been examined, 51 were selected as primary studies, from which more than 400 SOSE challenges were elicited. By applying qualitative data analysis methods to the extracted data from the review, we proved our hypotheses about the classification scheme. We are able to conclude that the SOSE challenges can be classified along two dimensions: (a) based on themes (or topics) that they cover and (b) based on characteristics (or types) that they reveal. By analyzing the distribution of the SOSE challenges on the topics and types in the years 2000–2008, we are able to point out the trend in SOSE research activities. The findings of this review further provide empirical evidence for establishing future SOSE research agendas.     

Applications of artificial intelligence in engineering and manufacturing: a systematic review

Journal of Intelligent Manufacturing - Engineering and manufacturing processes and systems designs involve many challenges, such as dynamism, chaotic behaviours, and complexity. Of late, the...     

Technology transfer decision support in requirements engineering research: a systematic review of REj

One of the main goals of an applied research field such as requirements engineering is the transfer of research results to industrial use. To promote industrial adoption of technologies developed in academia, researchers need to provide tangible evidence of the advantages of using them. This can be done through industry validation, enabling researchers to test and validate technologies in a real setting with real users and applications. The evidence obtained, together with detailed information on how the validation was conducted, offers rich decision support material for industrial practitioners seeking to adopt new technologies. This paper presents a comprehensive systematic literature review of all papers published in the Requirements Engineering journal containing any type of technology evaluation. The aim is to gauge the support for technology transfer, i.e., to what degree industrial practitioners can use the reporting of technology evaluations in the journal as decision support for adopting the technologies in industrial practice. Findings show that very few evaluations offer full technology transfer support, i.e., have a realistic scale, application or subjects. The major improvement potential concerning support for technology transfer is found to be the subjects used in the evaluations. Attaining company support, including support for using practitioners as subjects, is vital for technology transfer and for researchers seeking to validate technologies.

A systematic literature review of software requirements prioritization research

ContextDuring requirements engineering, prioritization is performed to grade or rank requirements in their order of importance and subsequent implementation releases. It is a major step taken in making crucial decisions so as to increase the economic value of a system.ObjectiveThe purpose of this study is to identify and analyze existing prioritization techniques in the context of the formulated research questions.MethodSearch terms with relevant keywords were used to identify primary studies that relate requirements prioritization classified under journal articles, conference papers, workshops, symposiums, book chapters and IEEE bulletins.Results73 Primary studies were selected from the search processes. Out of these studies; 13 were journal articles, 35 were conference papers and 8 were workshop papers. Furthermore, contributions from symposiums as well as IEEE bulletins were 2 each while the total number of book chapters amounted to 13.ConclusionPrioritization has been significantly discussed in the requirements engineering domain. However, it was generally discovered that, existing prioritization techniques suffer from a number of limitations which includes: lack of scalability, methods of dealing with rank updates during requirements evolution, coordination among stakeholders and requirements dependency issues. Also, the applicability of existing techniques in complex and real setting has not been reported yet.     

Systematic literature reviews in software engineering – A systematic literature review

BackgroundIn 2004 the concept of evidence-based software engineering (EBSE) was introduced at the ICSE04 conference.AimsThis study assesses the impact of systematic literature reviews (SLRs) which are the recommended EBSE method for aggregating evidence.MethodWe used the standard systematic literature review method employing a manual search of 10 journals and 4 conference proceedings.ResultsOf 20 relevant studies, eight addressed research trends rather than technique evaluation. Seven SLRs addressed cost estimation. The quality of SLRs was fair with only three scoring less than 2 out of 4.ConclusionsCurrently, the topic areas covered by SLRs are limited. European researchers, particularly those at the Simula Laboratory appear to be the leading exponents of systematic literature reviews. The series of cost estimation SLRs demonstrate the potential value of EBSE for synthesising evidence and making it available to practitioners.     

A systematic literature review of stakeholder identification methods in requirements elicitation

This paper presents a systematic review of relevant published studies related to topics in Requirements Engineering, specifically, concerning stakeholder identification methods in requirements elicitation, dated from 1984 to 2011. Addressing four specific research questions, this systematic literature review shows the following evidence gathered from these studies: current status of stakeholder identification in software requirement elicitation, the best practices recommended for its performance, consequences of incorrect identification in requirements quality, and, aspects which need to be improved. Our findings suggest that the analyzed approaches still have serious limitations in terms of covering all aspects of stakeholder identification as an important part of requirements elicitation. However, through correctly identifying and understanding the stakeholders, it is possible to develop high quality software.     

Applications of machine learning to BIM: A systematic literature review

As Building Information Modeling (BIM) workflows are becoming very relevant for the different stages of the project’s lifecycle, more data is produced and managed across it. The information and data accumulated in BIM-based projects present an opportunity for analysis and extraction of project knowledge from the inception to the operation phase. In other industries, Machine Learning (ML) has been demonstrated to be an effective approach to automate processes and extract useful insights from different types and sources of data. The rapid development of ML applications, the growing generation of BIM-related data in projects, and the different needs for use of this data present serious challenges to adopt and effectively apply ML techniques to BIM-based projects in the Architecture, Engineering, Construction and Operations (AECO) industry. While research on the use of BIM data through ML has increased in the past decade, it is still in a nascent stage. In order to asses where the industry stands today, this paper carries out a systematic literature review (SLR) identifying and summarizing common emerging areas of application and utilization of ML within the context of BIM-generated data. Moreover, the paper identifies research gaps and trends. Based on the observed limitations, prominent future research directions are suggested, focusing on information architecture and data, applications scalability, and human information interactions.     

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.     

Comparing ontologies and databases: a critical review of lifecycle engineering models in manufacturing

Knowledge and Information Systems - The literature on the modeling and management of data generated through the lifecycle of a manufacturing system is split into two main paradigms: product...     

Reusable knowledge in security requirements engineering: a systematic mapping study

Security is a concern that must be taken into consideration starting from the early stages of system development. Over the last two decades, researchers and engineers have developed a considerable number of methods for security requirements engineering. Some of them rely on the (re)use of security knowledge. Despite some existing surveys about security requirements engineering, there is not yet any reference for researchers and practitioners that presents in a systematic way the existing proposals, techniques, and tools related to security knowledge reuse in security requirements engineering. The aim of this paper is to fill this gap by looking into drawing a picture of the literature on knowledge and reuse in security requirements engineering. The questions we address are related to methods, techniques, modeling frameworks, and tools for and by reuse in security requirements engineering. We address these questions through a systematic mapping study. The mapping study was a literature review conducted with the goal of identifying, analyzing, and categorizing state-of-the-art research on our topic. This mapping study analyzes more than thirty approaches, covering 20 years of research in security requirements engineering. The contributions can be summarized as follows: (1) A framework was defined for analyzing and comparing the different proposals as well as categorizing future contributions related to knowledge reuse and security requirements engineering; (2) the different forms of knowledge representation and reuse were identified; and (3) previous surveys were updated. We conclude that most methods should introduce more reusable knowledge to manage security requirements.     

A systematic literature review on the usage of eye-tracking in software engineering

ContextEye-tracking is a mean to collect evidence regarding some participants’ cognitive processes. Eye-trackers monitor participants’ visual attention by collecting eye-movement data. These data are useful to get insights into participants’ cognitive processes during reasoning tasks.ObjectiveThe Evidence-based Software Engineering (EBSE) paradigm has been proposed in 2004 and, since then, has been used to provide detailed insights regarding different topics in software engineering research and practice. Systematic Literature Reviews (SLR) are also useful in the context of EBSE by bringing together all existing evidence of research and results about a particular topic. This SLR evaluates the current state of the art of using eye-trackers in software engineering and provides evidence on the uses and contributions of eye-trackers to empirical studies in software engineering.MethodWe perform a SLR covering eye-tracking studies in software engineering published from 1990 up to the end of 2014. To search all recognised resources, instead of applying manual search, we perform an extensive automated search using Engineering Village. We identify 36 relevant publications, including nine journal papers, two workshop papers, and 25 conference papers.ResultsThe software engineering community started using eye-trackers in the 1990s and they have become increasingly recognised as useful tools to conduct empirical studies from 2006. We observe that researchers use eye-trackers to study model comprehension, code comprehension, debugging, collaborative interaction, and traceability. Moreover, we find that studies use different metrics based on eye-movement data to obtain quantitative measures. We also report the limitations of current eye-tracking technology, which threaten the validity of previous studies, along with suggestions to mitigate these limitations.ConclusionHowever, not withstanding these limitations and threats, we conclude that the advent of new eye-trackers makes the use of these tools easier and less obtrusive and that the software engineering community could benefit more from this technology.     

Claims about the use of software engineering practices in science: A systematic literature review

Context: Scientists have become increasingly reliant on software in order to perform research that is too time-intensive, expensive, or dangerous to perform physically. Because the results produced by the software drive important decisions, the software must be correct and developed efficiently. Various software engineering practices have been shown to increase correctness and efficiency in the development of traditional software. It is unclear whether these observations will hold in a scientific context.Objective: This paper evaluates claims from software engineers and scientific software developers about 12 different software engineering practices and their use in developing scientific software.Method: We performed a systematic literature review examining claims about how scientists develop software. Of the 189 papers originally identified, 43 are included in the literature review. These 43 papers contain 33 different claims about 12 software engineering practices.Results: The majority of the claims indicated that software engineering practices are useful for scientific software development. Every claim was supported by evidence (i.e. personal experience, interview/survey, or case study) with slightly over half supported by multiple forms of evidence. For those claims supported by only one type of evidence, interviews/surveys were the most common. The claims that received the most support were: “The effectiveness of the testing practices currently used by scientific software developers is limited” and “Version control software is necessary for research groups with more than one developer.” Additionally, many scientific software developers have unconsciously adopted an agile-like development methodology.Conclusion: Use of software engineering practices could increase the correctness of scientific software and the efficiency of its development. While there is still potential for increased use of these practices, scientific software developers have begun to embrace software engineering practices to improve their software. Additionally, software engineering practices still need to be tailored to better fit the needs of scientific software development.     

Integrating ontologies,model driven,and CNL in a multi-viewed approach for requirements engineering

Research in requirements engineering (RE) has been growing in the last few years. RE researchers are generally concerned with a set of open issues such as: (i) the need for a well-defined process to identify and specify the requirements scope, (ii) suitable mechanisms to support communication among different stakeholders and development teams involved in the RE process, (iii) mechanisms to deal with the inherent volatility of requirements, and (iv) the need for a traceability scheme to help managing requirements in the downstream phases of the development process. In this work, we address some of these open issues by proposing the use of an iterative and incremental model-driven RE process combined with the employment of different notations such as controlled natural language and ontology in each activity of RE process. Based on the argument that there is no single notation suitable to represent requirements from the different perspectives of all the stakeholders and development teams, we propose a RE process encompassing different views, representing each perspective. This paper describes the proposed process, its tool support, and presents a controlled experiment that illustrates the proposal and evaluates its benefits.     

Competence-based recommender systems: a systematic literature review

ABSTRACT

Competence-based learning is increasingly widespread in many institutions since it provides flexibility, facilitates the self-learning and brings the academic and professional worlds closer together. Thus, the competence-based recommender systems emerged taking the advantages of competences to offer suggestions (performance of a learning experience, assistance of an expert or recommendation of a learning resource) to the user (learner or instructor). The objective of this work is to conduct a new Systematic Literature Review (SLR) concerning competence-based recommender systems to analyse in relation to their nature and assessment of competences an others key factors that provide more flexible and exhaustive recommendations. To do so, a SLR research methodology was followed in which 25 competence-based recommender systems related to learning or instruction environments were classified according to multiple criteria. We evaluate the role of competences in these proposals and enumerate the emerging challenges. Also a critical analysis of current proposals is carried out to determine their strengths and weakness. Finally, future research paths to be explored are grouped around two main axes closely interlinked; first about the typical challenges related to recommender systems and second, concerning ambitious emerging challenges.