Quality issues in User Stories (US) frequently arise during implementation, with common problems including ambiguity, integration challenges, and inconsistencies in templates or formal structure. These challenges emphasize the critical need to evaluate the quality of the US, prompting extensive research focused on developing methods and innovations to improve the requirement elicitation process. This study aims to analyze the frameworks, application methods, and tools employed in previous research to assess US quality. Utilizing the Kitchenham framework, 26 relevant studies were systematically reviewed. Next, the analysis identified six prominent quality evaluation frameworks: INVEST, Quality User Story (QUS), ISO 25010, IEEE 830, USQM, and linguistic-based approaches. The application of these frameworks often involves experts, practitioners, and artificial intelligence (AI). Meanwhile, among the tools reviewed, AQUSA emerged as the most frequently used due to its alignment with QUS standards. These findings highlight the adaptability of existing frameworks and tools while underscoring the potential for further integrating generative AI to enhance the accuracy and efficiency of US quality evaluations. Subsequently, future research should explore innovative AI-based methods to advance this critical area of requirement engineering.

One of the businesses in the service sector that is needed by the community who use motorbikes is a repair shop. The existence of workshops scattered in areas in the city of Mataram often causes people to be confused about finding a workshop that suits their needs. Based on the existing problems, a solution was designed, namely Disera (Digital Service App). DISERA is a service-based digital business to connect automotive experts or repair workers with people who need motorcycle service services. In the DISERA application development process, a structured requirements identification technique is needed. Based on the presentation of the problem and the urgency of elicitation, this research will focus on how to identify the need for the DISERA application as an Android-based motorcycle online service ordering application in the city of Mataram. The elicitation techniques that will be used in this study are survey and prototyping techniques with the aim of obtaining actual user needs and providing prototype designs so that the application development process becomes more focused and produces a good appearance. This research was conducted using a mix of methods, namely qualitative and quantitative methods. Quantitative methods are used as a scheme in collecting data in the form of numbers from survey results to selecting data from observations. While the qualitative method is constructed as a correlative scheme in analyzing problems in the results of case studies and reviewing the basic theory of concept development. In the application design process, data collection is first carried out from primary data obtained through digital surveys, so that user data is obtained to determine the application development process. Prototyping techniques in the software requirements elicitation process can help the process of making application designs that suit user needs. The result is that through survey and prototyping techniques can create application designs that meet user needs

As automated decision-making permeates almost all aspects of everyday life, capabilities to generate meaningful explanations for various stakeholders (i.e., decision-makers, addressees of decisions including individuals, auditors, and regulators) should be carefully deployed. This article presents a typology of explanations intended to support the first pillar of an explainability-by-design strategy. Its production has been achieved by pursuing a responsible innovation approach and introducing a new persona within the research and innovation process, i.e., a legal engineer, whose role is to work at the interface of two teams, the compliance and the engineering teams, and to oversee the process of requirement elicitation, which is often opinionated and narrowing. Once explanation requirements have been derived from applicable regulatory requirements, compliance rules, or business policies, they have been mapped to the dimensions of the typology to produce fine-grained explanation requirements, forming computable building blocks that can then be translated into system requirements during the technical design phase. The typology has been co-created with industry partners operating in two sectors: finance and education. Two pilot studies have thus been conducted to test both the feasibility of the generation and computation of explanations on the basis of the typology and the usefulness of the outputs in the light of the state-of-the-art. The typology comprises nine hierarchical dimensions. It can be leveraged to operate a stand-alone classifier of explanations that acts as detective controls within a broader partially automated compliance strategy. A machine-readable format of the typology is provided in the form of a light ontology.

Abstract Requirement elicitation, a critical, yet time-consuming and challenging step in product development, often fails to capture the full spectrum of user needs. This may lead to products that fall short of user expectations. This article introduces a novel framework that leverages large language models (LLMs) to automate and enhance the requirement elicitation process. LLMs are used to generate a vast array of simulated users (LLM agents), enabling the exploration of a much broader range of user needs and unforeseen use cases. These agents engage in product experience scenarios, explaining their actions, observations, and challenges. Subsequent agent interviews and analysis uncover valuable user needs, including latent ones. We validate our framework with three experiments. First, we explore different methodologies for the challenge of diverse agent generation, discussing their advantages and shortcomings. We measure the diversity of identified user needs and demonstrate that context-aware agent generation leads to greater diversity. Second, we show how our framework effectively mimics empathic lead user interviews, identifying a greater number of latent needs than conventional human interviews. Third, we show that LLMs can be used to analyze interviews, capture needs, and classify them as latent or not. Our work highlights the potential of using LLMs to accelerate early-stage product development with minimal costs and increase innovation.

Requirements elicitation is a fundamental process in software engineering, essential for aligning software products with user needs and project objectives. As software projects become more complex, effective elicitation methods are vital for capturing accurate and comprehensive requirements. Despite the variety of available elicitation methods, practitioners face persistent challenges such as capturing tacit knowledge, managing diverse stakeholder needs, and addressing ambiguities in requirements. Moreover, although elicitation is recognized as a core process for gathering and analyzing system objectives, there is a lack of a unified and systematic framework to guide practitioners—especially newcomers—through the activity. To address these challenges, we provide a comprehensive analysis of existing elicitation methods, aiming to contribute to better alignment between software products and project objectives, ultimately improving software engineering practices. We do so by performing a systematic literature review identifying crosscutting steps, common techniques, tools, and approaches that define the core activities of the elicitation process. We synthesize our findings into a metamodel that structures software elicitation processes. This review uncovers various elicitation methods—such as collaborative workshops, interviews, and prototyping—each demonstrating unique strengths in different project contexts. It also highlights significant limitations, including stakeholder misalignment and incomplete requirements capture, which continue to reduce the effectiveness of elicitation processes. Finally, our study seeks to contribute to understanding requirements elicitation methods by providing a comprehensive view of their current strengths and limitations through a metamodel enabling the structuring and optimization of elicitation processes.

The digital transformation and proliferation of social network sites (SNSs) have created new opportunities to consider digital sources to support the development of software systems. Social network sites (SNSs), such as Twitter and Facebook, can be major sources used during the process of requirement elicitation to identify and extract users’ requirements. The primary objective of SNS-based requirement elicitation is to overcome the limitations of the traditional requirement elicitation methods. However, these valued resources for requirement elicitation are yet to be fully exploited. Software products might not fulfill users’ needs owing to the numerous challenges in processing the data effectively. This study aims to explore the actual use, benefits, and challenges of SNS-based requirement elicitation. Twenty-five practitioners in the software companies in Saudi Arabia were interviewed, and thematic analysis was conducted on the interview data. With the application of the TOE model, five critical benefits and nine challenges were identified and classified into technological, organizational, and environmental contexts. The findings of this study offer valuable implications for researchers and practitioners by providing fine-grained details about the adoption of SNS-based requirement elicitation that could eventually facilitate its implementation effectively.

BackgroundIn Jordan, the confluence of traffic congestion and overcrowding in public hospitals poses a significant challenge for patients to collect their medications timely. This challenge was further intensified during the COVID-19 pandemic. Recognizing this issue, the Ministry of Health (MOH) and Electronic Health Solutions (EHS) intend to establish a Medication Delivery System (MDS), designed to provide patients with home delivery of medications and ensure proper treatment. This paper outlines a comprehensive framework to guide requirements engineers in devising an effective MDS framework, with a focus on expediting the development and testing processes and mitigating the risks associated with constructing such a system.MethodThe proposed methodology entails a robust, structured approach to requirements development for an MDS that integrates an electronic health record system, billing system, pharmacy application, the patient-oriented My Hakeem app, and a delivery tracking system. The requirements elicitation and analysis processes were undertaken by a multidisciplinary committee from MOH and EHS teams, ensuring a diverse understanding of stakeholder needs and expectations. The requirement specifications were meticulously documented via a data dictionary, unified modeling language (UML), and context diagrams. The quality and accuracy of the requirements were verified through an extensive validation process, involving thorough review by various EHS teams and the MOH committee.ResultsThe MDS was implemented across numerous MOH facilities within a timeline that was a third of the original projection, leveraging the same level of resources and expertise. Post the requirements development phase, there were no changes requested by any stakeholders, indicating a high level of requirement accuracy and satisfaction.ConclusionThe study illustrates that our proposed methodology significantly results in a comprehensive, well-documented, and validated set of requirements, which streamlines the development and testing phases of the project and effectively eliminates requirement errors at an early stage of the requirements development process.

There is a growing interest in the use of Design Thinking (DT) to enrich requirements elicitation processes. We carried out a quasi-experiment to compare the Effectiveness of Brainstorming sessions in terms of the number of ideas of requirements generated, and the Identified Stakeholders, complementing the Brainstorming sessions with two of the most widely used DT techniques: Empathy Maps and Personas. Therefore, we consider three treatments: Personas + Brainstorming, Empathy Maps + Brainstorming, and Brainstorming alone (control group). The quasi-experiment was carried out with 74 students enrolled in the Bachelor of Computer Engineering course at the Universitat Politècnica de València in 2021. The results reveal a statistically significant effect on Identified Stakeholders when using Empathy Maps. Descriptive analysis also shows an increase in Identified Stakeholders when using Personas, and in the Effectiveness of Brainstorming sessions when used together with Empathy Maps or Personas. There is also a variation in the type of ideas, with the number of functional ideas being higher, and that of non-functional ideas being lower when Empathy Maps are used. These results seem to indicate that Brainstorming sessions are improved when complemented with Empathy Maps or Personas techniques. Nonetheless, we still lack enough evidence to recommend either Personas or Empathy Maps, necessitating further validation.

Refining a design thinking-based requirements elicitation process: Insights from a focus group

Requirements elicitation is a crucial phase in the software development lifecycle, ensuring that stakeholders' needs are understood and translated into system specifications. Traditional methods often face challenges such as ambiguity, inconsistency, and evolving requirements, leading to project delays and cost overruns. This review proposes a conceptual model that integrates advancements and innovations in requirements elicitation to address these challenges comprehensively. The proposed model leverages various techniques, including but not limited to, natural language processing (NLP), machine learning (ML), and human-computer interaction (HCI), to enhance the accuracy and efficiency of requirements elicitation. NLP techniques enable automated analysis of textual requirements documents, extracting key information and identifying implicit requirements. ML algorithms facilitate the prediction of potential changes in requirements based on historical data and project context, enabling proactive management of evolving requirements. Moreover, the integration of HCI principles in the requirements elicitation process enhances stakeholder engagement and collaboration. Interactive interfaces and visualization tools enable stakeholders to provide feedback in real-time, fostering a more iterative and participatory approach to requirement gathering. Additionally, techniques such as prototyping and simulation facilitate early validation of requirements, reducing the risk of misinterpretation and ensuring alignment with stakeholders' expectations. Furthermore, the proposed model emphasizes the importance of context-awareness in requirements elicitation. By considering the organizational, cultural, and environmental context of a project, the model adapts its elicitation strategies and techniques to suit specific needs and constraints. Context-awareness also enables the identification of implicit requirements that may not be explicitly stated but are crucial for the success of the system. The model also addresses the challenge of managing conflicting requirements by introducing a systematic approach to requirements prioritization and negotiation. By employing multi-criteria decision-making techniques, stakeholders can collaboratively prioritize requirements based on their importance, feasibility, and impact on project objectives. Conflict resolution mechanisms facilitate consensus-building and trade-off analysis, ensuring that the final set of requirements reflects the collective interests of all stakeholders. Additionally, the proposed model emphasizes the iterative nature of requirements elicitation, advocating for continuous refinement and validation of requirements throughout the development lifecycle. Feedback loops enable stakeholders to review and revise requirements based on evolving needs and changing circumstances, thereby enhancing the adaptability and resilience of the system. The conceptual model presented in this review represents a holistic approach to requirements elicitation, leveraging advancements and innovations in technology, human interaction, and context-awareness. By integrating these elements, the model aims to enhance the accuracy, efficiency, and stakeholder satisfaction in the requirements elicitation process, ultimately contributing to the successful delivery of high-quality software systems.

A survey of 108 agile practitioners revealed that user stories are the most widely used method for capturing requirements. However, user stories can be interpreted differently by different stakeholders, leading to potential misunderstandings within the development team. Additionally, the interconnectedness of user stories poses challenges during the requirement elicitation process. A Systematic Literature Review (SLR) of 27 articles about user story elicitation process were selected and these are examined to determine user story quality. This research will provide a comprehensive summary of user story elicitation approaches and their application in addressing user story quality issues. The study will also offer insights into selecting appropriate approaches for resolving challenges in user story requirement elicitation. Finally, most user story elicitation approach primarily focus on addressing the issue of ambiguity.

This systematic literature review paper aims to identify and analyze the issues of managing users during requirement elicitation within agile software development (ASD) in the existing studies. The study employs a comprehensive search strategy to identify relevant articles published in peer-reviewed journals and conference proceedings. The findings reveal that the current literature focuses on various issues related to user involvement, communication, and collaboration during requirement elicitation. The paper identified 8 different issues related to managing users during requirement elicitation within ASD: user availability, lack of user involvement, long users’ feedback loops, lack of user expertise, ineffective product owner, lack of user communication skills, lack of process regarding user involvement, and lack of motivation. By identifying these issues, practitioners can overcome the issues of user involvement during requirement elicitation within ASD, and resolve conflicts to ensure a successful requirement elicitation process. The paper concludes by identifying the gaps in the existing literature and suggesting future research directions to address these gaps. The research provides valuable insights into the issues of managing users during requirement elicitation within ASD.

Requirements elicitation is a stakeholder-centered approach; therefore, natural language remains an effective way of documenting and validating requirements. As the scope of the software domain grows, software analysts process a higher number of requirements documents, generating delays and errors while characterizing the software domain. Natural language processing is key in such a process, allowing software analysts for speeding up the requirements elicitation process and mitigating the impact of the ambiguity and misinterpretations coming from natural-language-based requirements documents. However, natural-language-processing-based proposals for requirements elicitation are mainly focused on specific domains and still fail for understanding several requirements writing styles. In this paper, we present QUARE, a question-answering model for requirements elicitation. The QUARE model comprises a meta-ontology for requirements elicitation, easing the generation of requirements-elicitation-related questions and the initial structuration of any software domain. In addition, the QUARE model includes a named entity recognition and relation extraction system focused on requirements elicitation, allowing software analysts for processing several requirements writing styles. Although software analysts address a software domain at a time, they use the same kind of questions for identifying and characterizing requirements abstractions such as actors, concepts, and actions from a software domain. Such a process may be framed into the QUARE model workflow. We validate our proposal by using an experimental process including real-world requirements documents coming from several software domains and requirements writing styles. The QUARE model is a novel proposal aimed at supporting software analysts in the requirements elicitation process.

Abstract Current automotive Industry is facing numerous challenges. Business model is transitioning from ownership to shared mobility. Mobility of the future is becoming smarter, safer, more secured and connected. Distributed interconnected automotive systems will deliver added‐value mobility services. In the meantime, industrial standards require description of systems engineering practices as well as the practices justification. Automotive SPICE (ASPICE), a standard of software development best practices for automotive industry, for example, was one of the first to support the development of system and software now include hardware and cybersecurity. Traditional systems engineering development approaches are not any more appropriate. The current automotive system complexity requires new approaches like Model‐Based Systems Engineering (MBSE), using modeling and simulation. To address compliance to industry standards, traditional quality approaches consisting of or defining a quality system with a set of processes (e.g. Requirement elicitation process, documentation process…) are no more sufficient. Addressing these challenges require a digital transformation with two pillars. The first pillar is an MBSE methodology such as Cyber MagicGrid (Dassault Systèmes MBSE method) to define a set of best practices to develop a system. The second pillar is a quality management system that relies on the MBSE methodology rather than on a set of enterprise processes to address compliance with standards. Benefits of this approach is in acceleration of the digital enterprise transformation which is achieved by capitalizing the know‐how and considering the industry standards constraints.

Requirements elicitation is a highly relevant part of the software development process. Due to the several techniques that exist to perform it, it is necessary to understand the complexity of this activity for it to be well performed, thus ensuring the quality of the final product. In addition, it is also worth emphasizing that the existence of well-defined processes is essential for the stakeholders' needs to be correctly identified in the initial stages of the software development process. This paper presents an experience report of the requirements elicitation and business process modeling teams. The teams used the best practices and reference frameworks to understand, model, and perform business process enhancements to the Brazilian Unified Health System General Audit Office (AUDSUS) audit system by using the business process model and notation (BPMN). Thus, all software requirements were specified based on the modeled business processes, providing a faster software development process and a more efficient information flow between stakeholders and the teams involved.

BackgroundIn patient care, data are historically generated and stored in heterogeneous databases that are domain specific and often noninteroperable or isolated. As the amount of health data increases, the number of isolated data silos is also expected to grow, limiting the accessibility of the collected data. Medical informatics is developing ways to move from siloed data to a more harmonized arrangement in information architectures. This paradigm shift will allow future research to integrate medical data at various levels and from various sources. Currently, comprehensive requirements engineering is working on data integration projects in both patient care– and research-oriented contexts, and it is significantly contributing to the success of such projects. In addition to various stakeholder-based methods, document-based requirement elicitation is a valid method for improving the scope and quality of requirements.ObjectiveOur main objective was to provide a general catalog of functional requirements for integrating medical data into knowledge management environments. We aimed to identify where integration projects intersect to derive consistent and representative functional requirements from the literature. On the basis of these findings, we identified which functional requirements for data integration exist in the literature and thus provide a general catalog of requirements.MethodsThis work began by conducting a literature-based requirement elicitation based on a broad requirement engineering approach. Thus, in the first step, we performed a web-based systematic literature review to identify published articles that dealt with the requirements for medical data integration. We identified and analyzed the available literature by applying the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. In the second step, we screened the results for functional requirements using the requirements engineering method of document analysis and derived the requirements into a uniform requirement syntax. Finally, we classified the elicited requirements into a category scheme that represents the data life cycle.ResultsOur 2-step requirements elicitation approach yielded 821 articles, of which 61 (7.4%) were included in the requirement elicitation process. There, we identified 220 requirements, which were covered by 314 references. We assigned the requirements to different data life cycle categories as follows: 25% (55/220) to data acquisition, 35.9% (79/220) to data processing, 12.7% (28/220) to data storage, 9.1% (20/220) to data analysis, 6.4% (14/220) to metadata management, 2.3% (5/220) to data lineage, 3.2% (7/220) to data traceability, and 5.5% (12/220) to data security.ConclusionsThe aim of this study was to present a cross-section of functional data integration–related requirements defined in the literature by other researchers. The aim was achieved with 220 distinct requirements from 61 publications. We concluded that scientific publications are, in principle, a reliable source of information for functional requirements with respect to medical data integration. Finally, we provide a broad catalog to support other scientists in the requirement elicitation phase.

Classification of Stakeholders of an Information System using Fuzzy based Adjusted Cosine Similarity Measure during Requirements Elicitation Process

In goal oriented requirements elicitation process (GOREP), the requirements of the stakeholders are refined and decomposed using AND/OR graph. Goal is a high level objective of a company which is refined and decomposed into sub-goals. After refinement and decomposition, a system may have several goals and it is not possible to implement all goals because of the time, budget, and other constraints of an organisation. It is a primarily research issue that how to select those goals that would be designed, implemented and tested during different phases of the software development process. On the basis of our review, we found that there is no support for the selection of goals in GOREP when preference relations are incomplete and the preferences of the decision-makers are represented by linguistic variables. Therefore, to address this research issue, we present a method for goal selection when linguistic preference relations are incomplete. Proposed method was applied to select the goals of the institute examination system.

Requirements elicitation is a key sub-process of requirements engineering in which various types of software requirements such as functional and non-functional requirements, testing requirements etc., are identified according to the needs of the stakeholders. After the completion of the requirements elicitation process, there may be a large set of requirements and practically it is not possible to implement all requirements due to budget, time and other constraints of an organization. Under this situation, software developers select the highest ranked software requirements from the list of the elicited software requirements for different releases of software so that a successful software product can be developed. The selection of software requirements for different releases is a difficult task because it requires the participation of various stakeholders. In the field of science and engineering, datasets play an important role during experimental work. Based on our review, we found that in the literature of software engineering less attention is given on the generation of the datasets particularly in the domain of software requirements prioritization and selection (SRPS). Therefore, to address this issue, in this paper we present a four-step method for generating the dataset for SRPS research, i.e. (a) identification of stakeholders, (b) elicitation of software requirements using the goal-oriented concept, (c) formation of decision maker committee and (d) evaluation of the functional requirements and non-functional requirements by decision makers under fuzzy environment. The proposed method has been applied to generate the dataset for the requirements of an institute examination system.

Requirements engineering (RE) is an essential initial stage in software engineering. The RE process begins with the elicitation stage. This stage collects all user requirements that must be fulfilled by the system which will be developed. A goal-oriented approach is an effective approach used to automate the RE process. The development of goal-oriented input document standards is one of the important issues that has not been widely studied. Therefore, this study developed a goal-oriented input document standard for the requirements elicitation process. A tool is developed based on the form of the input document that has been generated. The development of standard forms of input documents begins with literature study and data collection, analysis, design of standard forms of documents, tool design, tool development, and testing. At the analysis stage, a logical framework and element structure is formulated in a goal-oriented approach. Furthermore, the standard form of input documents is developed. The standard form of the document becomes a guideline for developing tools to process data requirements from elicitation results. Tool testing is carried out using black-box testing. The test results show that the tool can work according to the planned function. The trial of the use of the tools was carried out using five requirements datasets. The results of testing and using the tool through the requirements dataset show that GoEliTools can be used to record data on the requirements of several users for the development of an information system.