Software Requirements Engineering Research Articles

A Systematic Literature Review on Using Natural Language Processing in Software Requirements Engineering

This systematic literature review examines the integration of natural language processing (NLP) in software requirements engineering (SRE) from 1991 to 2023. Focusing on the enhancement of software requirement processes through technological innovation, this study spans an extensive array of scholarly articles, conference papers, and key journal and conference reports, including data from Scopus, IEEE Xplore, ACM Digital Library, and Clarivate. Our methodology employs both quantitative bibliometric tools, like keyword trend analysis and thematic mapping, and qualitative content analysis to provide a robust synthesis of current trends and future directions. Reported findings underscore the essential roles of advanced computational techniques like machine learning, deep learning, and large language models in refining and automating SRE tasks. This review highlights the progressive adoption of these technologies in response to the increasing complexity of software systems, emphasizing their significant potential to enhance the accuracy and efficiency of requirement engineering practices while also pointing to the challenges of integrating artificial intelligence (AI) and NLP into existing SRE workflows. The systematic exploration of both historical contributions and emerging trends offers new insights into the dynamic interplay between technological advances and their practical applications in SRE.

Using ChatGPT in Software Requirements Engineering: A Comprehensive Review

Large language models (LLMs) have had a significant impact on several domains, including software engineering. However, a comprehensive understanding of LLMs’ use, impact, and potential limitations in software engineering is still emerging and remains in its early stages. This paper analyzes the role of large language models (LLMs), such as ChatGPT-3.5, in software requirements engineering, a critical area in software engineering experiencing rapid advances due to artificial intelligence (AI). By analyzing several studies, we systematically evaluate the integration of ChatGPT into software requirements engineering, focusing on its benefits, challenges, and ethical considerations. This evaluation is based on a comparative analysis that highlights ChatGPT’s efficiency in eliciting requirements, accuracy in capturing user needs, potential to improve communication among stakeholders, and impact on the responsibilities of requirements engineers. The selected studies were analyzed for their insights into the effectiveness of ChatGPT, the importance of human feedback, prompt engineering techniques, technological limitations, and future research directions in using LLMs in software requirements engineering. This comprehensive analysis aims to provide a differentiated perspective on how ChatGPT can reshape software requirements engineering practices and provides strategic recommendations for leveraging ChatGPT to effectively improve the software requirements engineering process.

Software Requirements Engineering and User Experience Design Modeling of Big Data Analysis using Convolution-Bidirectional Temporal Convolutional Network

The study of user perception and interaction with applications is referred to as user experience, or UX. The intricacy and versatility of software products, from requirements engineering to product functionality are well recognized. UX evaluations are often depends on prototypes, but it's important to consider the semantics embedded in software requirements to ensure project success. In this manuscript, Software Requirements Engineering and User Experience Design Modeling of Big Data Analysis using Convolution-Bidirectional Temporal Convolutional Network (SRE-UEDM-BDA-CBTCN) is proposed. The input data are collected from Requirements dataset. The collected data are given to the Convolution-Bidirectional Temporal Convolutional Network (CBTCN) to Design Modeling of Big Data Analysis user experience based on the dataset. In general, CBTCN does not express any adaption of optimization techniques for determining the ideal parameters to accurate Design user experience. Hence, African Vultures Optimization Algorithm (AVOA) is proposed in this work to improve the weight parameter of CBTCN. The proposed model is implemented and the efficiency is evaluated utilizing some performance metrics like accuracy, precision, specificity, sensitivity and F1-Score. The proposed SRE-UEDM-BDA-CBTCN method provides 28.46%, 21.34 and 33.81% higher accuracy, 22.88%, 26.52% and 34.63% higher Precision and 28.46%, 21.34 and 33.81% higher specificity compared with the existing techniques like Holistic big data integrated artificial intelligent modeling to improve privacy and safety in data management of smart cities (AIM-BDI-SDM), Exploring the factors that affect user experience in mobile-health applications: A text-mining and machine-learning approach (MHA-UED-MLA) and Towards Measuring User Experience based on Software Requirements (TM-UEB-SR).

Eliciting and modeling emotional requirements: a systematic mapping review.

Considering users' emotions plays an extremely crucial role in the adoption and acceptance of recent technology by the end user. User emotions can also help to identify unknown requirements, saving resources that would otherwise be wasted if discovered later. However, eliciting and modeling users' emotional requirements in software engineering is still an open research area. This systematic mapping review analyzes emotional requirements (ER) practices in software engineering from two perspectives: elicitation and modeling. For elicitation techniques, we investigate the techniques, evaluation methods, limitations, and application domains. For modeling techniques, we examine the modeling languages, analyses, limitations, and domains. We systematically reviewed studies on emotional requirements engineering published between 1993-2023 and identified 46 relevant primary studies. A total of 34 studies investigated ER elicitation techniques, five examined modeling techniques, and seven covered both. Illustrative case studies were the main evaluation method for proposed elicitation techniques. Identified limitations include time consumption and extensive human involvement. The dominant application domains were healthcare and well-being, and game development. This review summarizes the current landscape of emotional requirements research, highlighting key elicitation and modeling techniques, evaluations, limitations, and domains. Further research can build on these findings to advance emotional requirements practices in software engineering. Future research may address (1) managing conflicting emotional requirements across users, (2) evaluating the value and impact of considering emotional requirements during the development and (3) Modeling and analyzing emotional requirements in relation to other requirements.

Sustainability-centric integration software requirements validation

Software Development Life Cycle (SDLC) is enriched with different phases. Requirement Analysis is predominant in designing and developing the software application with proper functionality and to produce expected outcome. The client expects the great deal of functionality and ease of use application and outstanding performance from the application developed. If the application is appropriately demonstrating the outcome what the client expected the requirements have to be gathered once again and re do the application until the client satisfaction. Understanding the client specific requirements from the users’ point of view and smooth running of the operations with proper integration between the modules of the application. The requirements from the client would be vague and taken in the user’s perception. The requirements taken from the client’s user requirements should be integrated with realistic expectations and plan according to the project schedule for each stage of SDLC. The requirement gathering technique should replicate the software requirement engineering with proper integration oriented methods. So that the project development will be completed without facing the challenges and issues arise in the different stages of SDLC. This research is proposing the integration oriented scrutiny on the software requirement engineering mechanism in the requirement analysis phase of SDLC.

Application of Generative AI for Business Analyst Role

This paper presents a comprehensive study on the application of Generative AI, specifically focusing on its role in enhancing the business analyst role within the realm of software development. It delves into the nuances of requirements engineering, a crucial phase in the software development lifecycle, and the transformation of user requirements into user stories. The paper explores the use of natural languages for crafting user requirements and emphasizes the revolutionary impact of Generative AI, particularly Open AI's Chat GPT, in automating and refining the process of generating user stories, acceptance criteria, and the definition of done. It speaks about the prompt-compression method with “LLM Lingua,” and conversation chaining using “Lang chain” aimed at optimizing the efficiency of large language models in handling extensive requirements, thereby signifying a significant stride in the field of software development and requirements engineering.

Improving monitoring and evaluation of undergraduate curriculum: A case of Software Requirements Engineering course

Improving monitoring and evaluation of undergraduate curriculum: A case of Software Requirements Engineering course

The role of informal communication in building shared understanding of non-functional requirements in remote continuous software engineering

The role of informal communication in building shared understanding of non-functional requirements in remote continuous software engineering

Joint Impact of Agents and Services in Enhancing Software Requirements Engineering

Requirements engineering (RE) is a significant aspect of system development stages in generating reliable software (SW). Despite RE’s decisive impact on project success, SW systems still fail since there is a perplexity in sorting out requirements correctly. Researchers have tried several paradigms to deal with the specified challenges, such as agent-oriented RE (AORE), model-based RE, and service-oriented RE (SORE). By investigating the limitations of the independent use of these paradigms, this research sets an objective that proposes a framework which integrates the two paradigms (agent and service) on top of social media to enhance the SW RE processes. Thus, the research addresses challenges in gathering adequate requirements, detecting alignment between business requirements and SW products, prioritizing requirements, and recommending innovative ideas. The research has mainly adopted an empirical research methodology for SW engineering. Accordingly, two distinct expert groups have been formed based on their previous experience in AORE and SORE, respectively. The experts have been selected from enterprises and academic institutions, and they participated in our case study. After performing the necessary assessment based on specified criteria, those experts in the first group have reported that CASCRE (Collaboration of Agents and Services for Crowd-based Requirements Engineering) with a score of 93.7% is found to be better than that of AORE with a score of 88.7%. Moreover, experts in the second group have declared that CASCRE, with a score of 92.3%, is better than SORE, with a score of 83.7%. In both cases, improvements have been observed, which reveals that the synergy of the CASCRE features has a better impact on the RE process than utilizing individual approaches. Moreover, in order to demonstrate the applicability of CASCRE, feedback has been gathered from a focused crowd of local pharmaceuticals using a mini-prototype. Accordingly, 250 requirements related comments have been gathered from the discussion forum, and 1400 keywords were generated. Then, after performing a sentiment analysis using NLP algorithms, the result was demonstrated to experts. Therefore, 93% of gurus strongly agreed on the applicability of CASCRE in real projects.

A Systematic Review on Natural Language Processing and Machine Learning Approaches to Improve Requirements Specification in Software Requirements Engineering

A Systematic Review on Natural Language Processing and Machine Learning Approaches to Improve Requirements Specification in Software Requirements Engineering

Software Requirement Engineering: Traceability Techniques and Tools

Requirement Traceability is one of the activities in managing requirements. It is important for software projects and is affecting the quality of software products. Requirement Traceability is a method to analyze the effect of changes among various software development lifecycle parts. Agile methodologies have been presented as an alternative to traditional software engineering methodologies. The transformation between traditional and agile methodologies is a hard task so the need for traceability grows. This paper introduces traceability research at the requirement engineering on the traceability literature published during the last years. It also investigates and discusses the requirements for traceability issues. It finally presents several requirement traceability techniques and tools to support traceability.

Interview with Alessio Antonini

Dr Alessio Antonini is a research fellow at the Knowledge Media Institute of the Open University (UK). He leads the "Knowledge Architectures" group that focuses on conceptual modeling for research and inter-organization infrastructures applied to, e.g., digital humanities and applied Artificial Intelligence to community and city digital innovations. His research focuses on the phenomenology and aesthetics of interactive and intelligent media, positive computing for digital healthcare and the design of ***Al-enabled health and well-being interventions. His methods focus on the scoping and design of technologies, connecting philosophy of mind, communication pragmatics, cognition and social ontology theories with information and data models, and software engineering requirements for such infrastructures. He is actively advocating and supporting the adoption of digital-informed methodologies and agenda in the Humanities, and Humanities interpretative methods in computer science.

Agile Software Requirements Engineering Challenges-Solutions—A Conceptual Framework from Systematic Literature Review

Agile software requirements engineering processes enable quick responses to reflect changes in the client’s software requirements. However, there are challenges associated with agile requirements engineering processes, which hinder fast, sustainable software development. Research addressing the challenges with available solutions is patchy, diverse and inclusive. In this study, we use a systematic literature review coupled with thematic classification and gap mapping analysis to examine extant solutions against challenges; the typologies/classifications of challenges faced with agile software development in general and specifically in requirements engineering and how the solutions address the challenges. Our study covers the period from 2009 to 2023. Scopus—the largest database for credible academic publications was searched. Using the exclusion criteria to filter the articles, a total of 78 valid papers were selected and reviewed. Following our investigation, we develop a framework that takes a three-dimensional view of agile requirements engineering solutions and suggest an orchestrated approach balancing the focus between the business context, project management and agile techniques. This study contributes to the theoretical frontier of agile software requirement engineering approaches and guidelines for practice.

A Systematic Mapping Study on Process Improvement in Software Requirements Engineering

Software analysis is the process carried out to obtain requirements that reflects the needs of a client's stakeholders and that allows the construction of a software product that meets their expectations. However, it is also known as a process where many defects are injected. In this context, although process improvement has contributed to the software industry, in the case of software requirements it needs to be studied to determine the improvements obtained and established models. In the literature reviewed, a similar mapping study with 4 research question was identified and used as a reference. The objective of this work is to structure the available literature on process improvement in the software requirements engineering (SRE) domain to identify the improvement phases, paradigms, principles, and established models. For this purpose, a systematic mapping study (SMS) was carried out in the most recognized digital databases. The mapping carried out recovered a total of 1,495 studies, and after the process, 86 primary studies were obtained. In this SMS had established and answered 13 research questions. The different models that are applied throughout the software requirements engineering process were identified, and accepted studies were classified and findings on SRE process improvement were collected. The most used models are CMMI, Requirements Engineering Good Practice Guide (REGPG), and ISO/IEC 15504. Also, 62% of accepted studies are of the proposal and evaluation type; that is, they propose a framework and study the implementation of a proposal in one or more case studies respectively. On the other hand, it was found that most of the studies focused on the process improvement analysis phase. Likewise, in contrast with a previous study, proposal and validation type of studies increased in 9 papers each one from 2014 to date. This shows the interest of the scientific community in this domain.

Research on the application of data mining technology in software engineering

The role of data mining in software engineering is obvious, but there is a lack of mining depth. In the past, engineering layout and function distribution problems in software development, and the framework construction was unreasonable. Therefore, this paper proposes a software system based on data mining technology. First, the software engineering project is divided, and the software engineering project design is carried out according to the interactive requirements to realize the preprocessing of software engineering. Then, according to the design criteria, the design collection of software engineering is formed, and the information system is analyzed in depth. MATLAB simulation shows that the design interactivity and accuracy of data mining are superior to traditional design methods under the condition that software engineering requirements are consistent.

Designing an Evaluation Framework for IoT Environmental Monitoring Systems

Environmental monitoring systems have been evolving dynamically to embrace modern Internet of Things (IoT) technology in the last decade. Despite this progress there are, however, continuing limitations and issues with some IoT designs. Thus, past research has identified areas of concern in areas such as communications, interoperability, reliability, and scalability. As enabling technologies evolve in an accelerated manner, there will no doubt be a plethora of environmental monitoring solutions under development. Such solutions need to be well evaluated so that potential users are knowledgeable in relation to the best solution for their specific applications. Along these lines, this paper puts forward a framework to evaluate proposed IT designs relevant to smart environmental monitoring systems. This framework is based on model standardized software engineering requirements found in ISO 25010, which it uses as an aid to develop business-driven ‘smart’ environmental monitoring systems.

MiniPI: Minimizing Power Imbalance among Stakeholders for Quality Software Product

The role of requirements elicitation is crucial in the software requirement engineering process as the requirement engineer has to extract the accurate requirements from different stakeholders. However, the problem emerges when the requirement team could not prioritize the extracted requirements because the requirement’s nature may vary as different categories of stakeholders have their own perspectives. This ultimately produces a power imbalance among stakeholders. Therefore, minimizing the power imbalance of software requirements among different categories of stakeholders is fundamentally important for a quality software product. Although many contributions have been made to this subject in the past, there is still a research gap available for minimizing the power imbalance among stakeholders. In this paper, we present a novel approach for minimizing the effects of power imbalance by age-sampling among different categories of stakeholders into three groups and then by age-mapping the requirements. After gathering questionnaires from stakeholders, the concerned parties determine the attributes of the Kano model through the filled Kano’s questionnaires and afterward, the satisfaction index is calculated by taking the values of the relevant age group into account, which eventually minimizes the power imbalance among stakeholders. In order to verify our methodology, we have performed quantitative analysis by calculating index values and applied verified Kano’s satisfaction formula to calculate the overall satisfaction index which improves the quality level of a software product.

Assessing Soft Skills for Software Requirements Engineering Processes

Software requirement engineering (SRE) is the process of establishing, documenting, and maintaining software requirements. The goal of this research is to investigate the importance of soft skills in SRE. The data collection was performed through an online questionnaire. Descriptive statistics, principal components analysis (PCA), and stepwise regression techniques were used to analyze the data. A comprehensive review determined the 31 soft skills associated with SRE. There were 122 software development experts in Gaza who participated in the survey. The PCA analysis extracted six factors, named problem-solving, learning willingness, commitment, pressure resilience, critical thinking, and interpersonal skills. The analysis discovered that the level of SRE practice in Gaza is 73.71%. Furthermore, it was determined that 89.2% of respondents have critical thinking skills, and 85% have problem-solving and commitment skills. The result shows that all soft skills factors have strong links to SRE. However, only four soft skills (problem-solving, willingness to learn, pressure tolerance, and critical thinking) were found to have an impact on SRE. Considering these findings, we recommend focusing on the development of soft skills, especially problem-solving and willingness to learn skills, for the team analyzing software system requirements.

Process Improvement in Software Requirements Engineering: A Systematic Mapping Study

Process Improvement in Software Requirements Engineering: A Systematic Mapping Study

Applied personal profile ontology for personnel appraisals

Purpose The purpose of this paper is to apply the earlier enhanced personal profile ontology (e-PPO) developed by the authors as a case study for the appraisal of the lecturers in the department of computer science, University of Uyo, Uyo for the purposes of promotions. The developed e-PPO was a sample smart résumé for the selection of the best among three personnel using linguistic variables and formal rules representing the combination of the criteria and subcriteria was illustrated which was used to allocate competent personnel for software requirement engineering tasks. The need for the use of the smart resume for appraisal purposes was pointed out in the conference paper, calling for the applicant’s data to be inputted into the enhanced personal profile ontology (e-PPO) for personnel appraisa. Design/methodology/approach Appraisal is a regular review of employees’ performances and their overall contribution to the organization they are working for. The availability of a web application for personnel appraisal requires PPO which includes both static and dynamic features. Personal profile is often modified for several purposes calling for augmentation and annotation when needs arise. Resume is one resulting extract from personal profile and often contain slightly different information based on needs. The urgent preparation of resume may introduce bias and incorrect information for the sole aim of projecting the personnel as being qualified for the available job. Religious and gender biases may sometimes be observed during appointments of new personnel, which may not be the case during appraisals for promotions or reassignment of tasks because such biases become insignificant given the fact that job targets and the skills needed are already set and the appraisals passes through several phases that are not determined by a single individual. This work therefore applied the earlier developed e-PPO for appraisal of the academic staff of the department of computer science, university of Uyo, Uyo, Nigeria. A mixed approach of existing ontologies like Methontology and Neon have been followed in the creation of the e-PPO, which is a constraint-based semantic data model tested using Protégé inbuilt reasoner with its updated plugins. Upon application of e-PPO on personnel appraisals, promotion and selection of employee for specific assignments in any organization is possible using the smart resume. Findings The use of the smart resume reduces the numerous task that would have been taken up by the human resource team, thereby reducing the processing time for the appraisals. The appraisal task is done void of biases of any kind such as gender and religion. Originality/value This work is an extension of the original work done by the authors.