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The number of papers and articles on goals would suggest that goal-oriented requirements engineering is a well understood and mature area within the requirements engineering discipline. In particular, there is a wealth of published material on formal goal modelling approaches. However, the uptake of the goal approaches advocated by academics and re...
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... However, despite the growing popularity of NLP4RE as a research domain, some gaps remain, as discussed here [28]: 1) Lack of industrial case studies: A divide prevails between NLP4RE research and its industrial penetration [12,[29][30][31][32]. This divide can be attributed to the fragmented approach to sharing knowledge pertaining to NLP4RE tools, techniques [33], and datasets. ...
We address the challenges inherent in converting natural language (NL) requirements into machine-readable formats by investigating the application of named-entity recognition (NER) within the aerospace domain. Recognizing the necessity for domain-specific language models, we developed an open-source annotated aerospace corpus and fine-tuned different versions of the BERT language model on the corpus to create aeroBERT-NER: a new model for identifying named entities (NEs) in the aerospace domain. A comparison between aeroBERT-NER and [Formula: see text]-NER demonstrated the superior performance of aeroBERT-NER in identifying NEs within a set of aerospace requirements. The identified NEs contribute to the development of a glossary, promoting consistent terminology usage in aerospace requirements and addressing challenges associated with the standardization of NL requirements.
... As an example of gap, the author points out the predominance of GORE in research but their shortfall in practice [8,5]. Thus, Mavin et al. point out the lack of connection between research and industrial practice via a study based on a GORE literature survey and a questionnaire addressed to practitioners [7]. Some recent works have tried to bridge the gap between academic and industry domains by considering more relevant graphical layouts [15] or by investigating how agility and non-functional requirements can be handled together [17]. ...
In aeronautics, the development of a new aircraft is usually organised in sequence. That means the aircraft is designed first, then its industrial system. Therefore, the industrial system may endure stringent constraints due to aircraft design choices. This can result in suboptimal performance with respect to manufacturing. But approaches such as Collaborative Engineering or Concurrent Engineering invite different engineering teams to work simultaneously and together in order to open up new prospects for a product design. In the context of a project that aims at developing methods and tools for co-designing an aircraft and its industrial system, we use Goal-Oriented Requirements Engineering (GORE) to model and to understand their respective expectations but also their dependencies. In this paper, we describe our application of goal modelling based on three iterative attempts. We start from an exploratory stage to have a global picture of the dependencies between the design of an aircraft nose section and its industrial system. We finish with a focus on a smaller problem in which we understand the key elements of the assembly line performance based on a nose design. For each attempt, we describe our results and feedback, and show how we overcame issues raised at the previous stage. We also highlight the links with known issues about GORE practical application.KeywordsCollaborative EngineeringConcurrent EngineeringGoal-Oriented Requirements EngineeringGoal ModellingAeronautics
... Many studies have concluded that there is a gap between RE tasks automation research and its implementation undertaken in industrial and real-life projects [147,148,149]. This gap is more obvious in the case of rule-based approaches since they usually need the requirements to be represented based on specific templates [150]; hence, their success strongly depends on the consistency of the requirements with the predefined templates [114,150]. ...
... These situations are common in real-life projects when it is hard to control requirements authoring environments, especially in large development projects, or when one has little control over the requirements authoring environments. [114,151,147,148,149,150,12]. One of the potential future research directions is working on more adaptive approaches which can be more flexible when handling requirements, such as identifying the syntactic structures automatically and building more adaptive approaches based on the dynamically identified structure. ...
Natural Language Processing (NLP) is widely used to support the automation of different Requirements Engineering (RE) tasks. Most of the proposed approaches start with various NLP steps that analyze requirements statements, extract their linguistic information, and convert them to easy-to-process representations, such as lists of features or embedding-based vector representations. These NLP-based representations are usually used at a later stage as inputs for machine learning techniques or rule-based methods. Thus, requirements representations play a major role in determining the accuracy of different approaches. In this paper, we conducted a survey in the form of a systematic literature mapping (classification) to find out (1) what are the representations used in RE tasks literature, (2) what is the main focus of these works, (3) what are the main research directions in this domain, and (4) what are the gaps and potential future directions. After compiling an initial pool of 2,227 papers, and applying a set of inclusion/exclusion criteria, we obtained a final pool containing 104 relevant papers. Our survey shows that the research direction has changed from the use of lexical and syntactic features to the use of advanced embedding techniques, especially in the last two years. Using advanced embedding representations has proved its effectiveness in most RE tasks (such as requirement analysis, extracting requirements from reviews and forums, and semantic-level quality tasks). However, representations that are based on lexical and syntactic features are still more appropriate for other RE tasks (such as modeling and syntax-level quality tasks) since they provide the required information for the rules and regular expressions used when handling these tasks. In addition, we identify four gaps in the existing literature, why they matter, and how future research can begin to address them.
... Many studies have concluded that there is a gap between RE tasks automation research and its implementation undertaken in industrial and real-life projects [147,148,149]. This gap is more obvious in the case of rule-based approaches since they usually need the requirements to be represented based on specific templates [150]; hence, their success strongly depends on the consistency of the requirements with the predefined templates [114,150]. ...
... These situations are common in real-life projects when it is hard to control requirements authoring environments, especially in large development projects, or when one has little control over the requirements authoring environments. [114,151,147,148,149,150,12]. One of the potential future research directions is working on more adaptive approaches which can be more flexible when handling requirements, such as identifying the syntactic structures automatically and building more adaptive approaches based on the dynamically identified structure. ...
Natural Language Processing (NLP) is widely used to support the automation of different Requirements Engineering (RE) tasks. Most of the proposed approaches start with various NLP steps that analyze requirements statements, extract their linguistic information, and convert them to easy-to-process representations, such as lists of features or embedding-based vector representations. These NLP-based representations are usually used at a later stage as inputs for machine learning techniques or rule-based methods. Thus, requirements representations play a major role in determining the accuracy of different approaches. In this paper, we conducted a survey in the form of a systematic literature mapping (classification) to find out (1) what are the representations used in RE tasks literature, (2) what is the main focus of these works, (3) what are the main research directions in this domain, and (4) what are the gaps and potential future directions. After compiling an initial pool of 2,227 papers, and applying a set of inclusion/exclusion criteria, we obtained a final pool containing 104 relevant papers. Our survey shows that the research direction has changed from the use of lexical and syntactic features to the use of advanced embedding techniques, especially in the last two years. Using advanced embedding representations has proved its effectiveness in most RE tasks (such as requirement analysis, extracting requirements from reviews and forums, and semantic-level quality tasks). However, representations that are based on lexical and syntactic features are still more appropriate for other RE tasks (such as modeling and syntax-level quality tasks) since they provide the required information for the rules and regular expressions used when handling these tasks. In addition, we identify four gaps in the existing literature, why they matter, and how future research can begin to address them.
... Interacting requirements are a common source for errors [24] and manual analysis is time-consuming and costly [25]. In addition, there is a need for clearly defined relationships to foster more formal methods, e.g., in the relation between requirements and goals [26] and with respect to a broad use of the term traceability [3]. To address this, the following research questions are investigated: ...
... Whilst the specific purpose and semantics of the relations is important for their beneficial usage, the respective representation in industrial application is shallow and remains often implicit. This has already been acknowledged at the turn of the millennium by Gotel and Finkelstein [64] and Dick [1], but has not changed since, as assessed, e.g., by Goodrum et al. [3] for respective tool support and Mavin et al. [26] for the use of goal-oriented approaches. ...
... This opens a wide range of possible interpretations. While formal approaches as KAOS [11,65] provide a clear definition of refinement within their context, in practice there is often no common interpretation [26]. According to Salay et al. [70], the following three types of refinement can be isolated: [52]. ...
Relations between requirements are part of nearly every requirements engineering approach. Yet, relations of views, such as requirements documents, are scarcely considered. This is remarkable as requirements documents and their structure are a key factor in requirements reuse, which is still challenging. Explicit formalized relations between documents can help to ensure consistency, improve completeness, and facilitate review activities in general. For example, this is relevant in space engineering, where many challenges related to complex document dependencies occur: 1. Several contractors contribute to a project. 2. Requirements from standards have to be applied in several projects. 3. Requirements from previous phases have to be reused. We exploit the concept of “layered traceability”, explicitly considering documents as views on sets of individual requirements and specific traceability relations on and between all of these representation layers. Different types of relations and their dependencies are investigated with a special focus on requirement reuse through standards and formalized in an Object-Role Modelling (ORM) conceptual model. Automated analyses of requirement graphs based on this model are able to reveal document inconsistencies. We show examples of such queries in Neo4J/Cypher for the EagleEye case study. This work aims to be a step toward a better support to handle highly complex requirement document dependencies in large projects with a special focus on requirements reuse and to enable automated quality checks on dependent documents to facilitate requirements reviews.
... This is particularly for the reason that our industry partners were more interested in gaining an understanding of the system to be developed than a formal goal fulfillment analysis. As industry is typically reluctant to introduce goal modeling approaches in practice [26,27], we develop the extension based on observed industry needs. ...
... Another remaining threat is if industry will ever use the extension on their own. Particularly, there is a threat that goal models at all will not be used by industry as recent studies have shown industry's reluctance to the use of goal modeling [26,27]. While we cannot rule out this possibility, we want to highlight that we have shown for the automotive industry that goal models are welcomed when the introduction is accompanied with training and tutoring sessions [52]. ...
Collaborative cyber-physical systems are capable of forming networks at runtime to achieve goals that are unachievable for individual systems. They do so by connecting to each other and exchanging information that helps them coordinate their behaviors to achieve shared goals. Their highly complex dependencies, however, are difficult to document using traditional goal modeling approaches. To help developers of collaborative cyber-physical systems leverage the advantages of goal modeling approaches, we developed a GRL-compliant extension to the popular iStar goal modeling language that takes the particularities of collaborative cyber-physical systems and their developers’ needs into account. In particular, our extension provides support for explicitly distinguishing between the goals of the individual collaborative cyber-physical systems and the network and for documenting various dependencies not only among the individual collaborative cyber-physical systems but also between the individual systems and the network. We provide abstract syntax, concrete syntax, and well-formedness rules for the extension. To illustrate the benefits of our extension for goal modeling of collaborative cyber-physical systems, we report on two case studies conducted in different industry domains.
... Regardless of the extensive research in academia, there is no evidence that the goal-based requirements engineering approaches have been undertaken in an industrial context, indicating a significant gap between research and practice [23]. In particular, the majority of existing goal modeling approaches have not been evaluated through practitioner feedback. ...
... In particular, the majority of existing goal modeling approaches have not been evaluated through practitioner feedback. As reported by Mavin et al., there are several difficulties in applying goal modeling in practice, such as conceptual confusion, lack of industry-oriented guidance, and scalability issues [23]. Lima et al. have surveyed 126 papers that consider scalability issues of i* framework [22]. ...
Bridging the gap between academia and industry is an important issue to promote the practicality of i* framework. Researchers have been dealing with this issue from various perspectives, such as simplifying the meta-models or modeling processes of i* framework. In this paper, we exclusively focus on the scalability issue in laying out large-scale i* models and propose a two-level layout approach to automatically lay out i* models in an efficient and comprehensible manner, contributing to the adoption of i* framework in the industry. The proposed approach is designed by considering the semantics of i* constructs and layout conventions of i* models in order to produce meaningful layouts and can appropriately handle both the SD (Strategic Dependency) view and the SR (Strategic Rationale) view of i* models. We have implemented our approach in an open-access prototype tool, which is able to be integrated with existing iStarML-compatible modeling tools. We have conducted a controlled experiment, a case study, and performance testing to empirically and comprehensively evaluate the utility of our approach, the results of which show that our proposal can efficiently produce meaningful layouts that are as comprehensible as manually laid out models in most cases.
... Generally speaking, graphical representations carry information more effectively to non-technical people than textual ones [5]. However, the ever-increasing complexity of modern systems has brought a significant amount of requirements, resulting in the scalability problem when dealing with their graphical representations [6]. Also, the graphical modeling method requires the knowledge of the model and its notations before modeling. ...
... To obtain highquality requirements and reduce development efforts to ensure the success of projects, many researchers have proposed a large number of RE methods from different perspectives, such as goal-based, model-based, scenario-based, and value-based RE methods. However, many methods have not been applied on a large scale in the industry [3]. One possible explanation is that the proposed methods did not consider the real needs of the industry effectively. ...
... One possible explanation is that the proposed methods did not consider the real needs of the industry effectively. The starting point of the methods proposed by many researchers is the problems pointed out in the existing literature, but these problems are not consistent with the real needs of the industry [3]. To bridge the gap between academia and industry, researchers and developers of RE tools need to have a deeper understanding of issues and challenges in RE. ...
... Although the existing literature provides some insights into the current application of RE in the industry [3][4][5][6], as an emerging service mode, RE of crossover services faces enormous challenges, but there is no literature on systematic research on this issue. To investigate and understand the essential issues and challenges, we conducted an industry study guided by the following research question: ...
Abstract Crossover services involve deep convergence of services in different domains. Requirements analysis of crossover services often requires the collaboration of engineers in different domains and various organizations. The industry has a demand for sophisticated requirements engineering (RE) methods to address challenges brought by crossover and convergence. However, many methods proposed by researchers have not been widely used in the industry, and the reason is that these methods provide technological solutions to the problems and challenges that may not be considered accurate or even real by practitioners in the crossover services industry. A great effort is needed to explore what needs, expectations, and constraints that RE approaches must satisfy and promote the adoption of novel RE approaches in the crossover services industry. The authors have conducted an industrial study to gain an in‐depth understanding of practitioners' needs concerning RE research and method development. The study involved qualitative interviews as well as questionnaires to collect data. The objective of this study is to investigate issues, challenges, and practices of crossover services RE from practitioners' perspectives and to reveal potential guidelines for researchers and tools developers. Findings from five aspects of RE methods are reported and some research directions for future crossover services RE research are provided.
... This indication comprises the administration of different measurements, for example, platform requirements, performance, smartness, scalability, customization, and client agreement. A substantial trial is to deal with these properties at the primary step of requirements designing and to determine the insight of PSS related clashes on requirements [28,38]. The activities of RM are executed at the 'Managed' level of CMMI, i.e., level 2. Numerous software companies at this step try to follow these practices; yet, they don't fast-track to process innovation. ...
The developmental paradigm in the software engineering industry has transformed from a programming-oriented approach to model-oriented development. At present, model-based development is becoming an emerging method for enterprises for constructing software systems and services most proficiently. In Capability Maturity Model Integration (CMMI) Level 2, i.e., Managed, we need to sustain the bi-directional trace of the transformed models for the administration of user requirements and demands. This goal is achieved by the organization after applying the particular practices suggested by CMMI level 2 process area of Requirements Management (RM). It is very challenging for software developers and testers to maintain trace, particularly during the evaluation and upgrading phases of development. In our previous research work, we proposed a traceability framework for model-based development of applications for software enterprises. This work is the extension of our previously presented research work in which we have anticipated the meta-model transformations according to the Software Development Life Cycle (SDLC). These meta-models are capable of maintaining the trace information through relations. The proposed technique is also verified using a generalized illustration of an application. This transformation practice will give a foundation to software designers to maintain traceability links in model-driven development
