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Requirements Engineering: Bridging Theory, Research and Practice

Submission Deadline: 31 May 2024 (closed) View: 616

Guest Editors

Dr. Affan Yasin, Northwestern Polytechnical University, China
Dr. Javed Ali Khan, University of Hertfordshire, UK
Dr. Ziqi Wei, Chinese Academy of Sciences, China
Prof. Shijun Liu, Shandong University, China

Summary

Software engineering involves creating digital systems, and a crucial part of this process is requirements engineering. Requirements engineering focuses on understanding user needs and defining how a system should function. This ensures that the software we develop is not only valuable and functional but also user-friendly and enjoyable.

 

In today's rapidly evolving software landscape, we're constantly seeking fresh ideas. Agile and DevOps teams are introducing innovative strategies into requirements engineering to adapt swiftly and bring products to market faster. The emergence of artificial intelligence, particularly machine learning, presents both opportunities and challenges. Future systems must also address ethical and societal concerns like sustainability, human values, and gender-related issues, as they influence how these systems impact society and the environment.

 

Requirements engineering (RE) is a human-centered process seamlessly integrated into systems and software engineering. It aids our understanding of complex systems throughout their lifecycle through tasks such as gathering, analyzing, defining, documenting, validating, and managing requirements. Neglecting these initial RE tasks can lead to problems, as extensively discussed in academic literature.

 

In the realm of requirements engineering, we must consider how people perceive their environment, interact with systems, and are influenced by societal dynamics. To achieve this, insights from cognitive and social sciences are drawn upon to establish both theoretical foundations and practical methods for defining requirements. These insights come from diverse fields, including computer science, software engineering, psychology, anthropology, sociology, and linguistics.

 

Given these ongoing developments, it is imperative for the requirements engineering community to adopt a proactive approach. We must adapt current practices and rigorously assess the foundations and effectiveness of these novel approaches in RE. This proactive adaptation is essential to remain at the forefront of our ever-evolving field.


Keywords

• Software requirements methods and tools
• Software requirements application in industry
• Software requirements education
• Software requirements and Artificial Intelligence (AI)
• Functional and non-functional requirements
• Model driven requirements engineering
• Formal methods for the early software development stages
• User-centered software development
• Requirements engineering for sustainability
• Ethical and societal concerns in software requirements
• Requirements in Agile development
• Requirements in DevOps (processes)
• Security and Privacy challenges in context of requirements engineering
• Interdisciplinary studies
• New and Emerging Ideas

Published Papers


  • Open Access

    ARTICLE

    Towards Improving the Quality of Requirement and Testing Process in Agile Software Development: An Empirical Study

    Irum Ilays, Yaser Hafeez, Nabil Almashfi, Sadia Ali, Mamoona Humayun, Muhammad Aqib, Ghadah Alwakid
    CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 3761-3784, 2024, DOI:10.32604/cmc.2024.053830
    (This article belongs to the Special Issue: Requirements Engineering: Bridging Theory, Research and Practice)
    Abstract Software testing is a critical phase due to misconceptions about ambiguities in the requirements during specification, which affect the testing process. Therefore, it is difficult to identify all faults in software. As requirement changes continuously, it increases the irrelevancy and redundancy during testing. Due to these challenges; fault detection capability decreases and there arises a need to improve the testing process, which is based on changes in requirements specification. In this research, we have developed a model to resolve testing challenges through requirement prioritization and prediction in an agile-based environment. The research objective is to… More >

  • Open Access

    ARTICLE

    Fine-Tuning Cyber Security Defenses: Evaluating Supervised Machine Learning Classifiers for Windows Malware Detection

    Islam Zada, Mohammed Naif Alatawi, Syed Muhammad Saqlain, Abdullah Alshahrani, Adel Alshamran, Kanwal Imran, Hessa Alfraihi
    CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 2917-2939, 2024, DOI:10.32604/cmc.2024.052835
    (This article belongs to the Special Issue: Requirements Engineering: Bridging Theory, Research and Practice)
    Abstract Malware attacks on Windows machines pose significant cybersecurity threats, necessitating effective detection and prevention mechanisms. Supervised machine learning classifiers have emerged as promising tools for malware detection. However, there remains a need for comprehensive studies that compare the performance of different classifiers specifically for Windows malware detection. Addressing this gap can provide valuable insights for enhancing cybersecurity strategies. While numerous studies have explored malware detection using machine learning techniques, there is a lack of systematic comparison of supervised classifiers for Windows malware detection. Understanding the relative effectiveness of these classifiers can inform the selection of… More >

  • Open Access

    ARTICLE

    Classification and Comprehension of Software Requirements Using Ensemble Learning

    Jalil Abbas, Arshad Ahmad, Syed Muqsit Shaheed, Rubia Fatima, Sajid Shah, Mohammad Elaffendi, Gauhar Ali
    CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 2839-2855, 2024, DOI:10.32604/cmc.2024.052218
    (This article belongs to the Special Issue: Requirements Engineering: Bridging Theory, Research and Practice)
    Abstract The software development process mostly depends on accurately identifying both essential and optional features. Initially, user needs are typically expressed in free-form language, requiring significant time and human resources to translate these into clear functional and non-functional requirements. To address this challenge, various machine learning (ML) methods have been explored to automate the understanding of these requirements, aiming to reduce time and human effort. However, existing techniques often struggle with complex instructions and large-scale projects. In our study, we introduce an innovative approach known as the Functional and Non-functional Requirements Classifier (FNRC). By combining the… More >

  • Open Access

    ARTICLE

    Developing Lexicons for Enhanced Sentiment Analysis in Software Engineering: An Innovative Multilingual Approach for Social Media Reviews

    Zohaib Ahmad Khan, Yuanqing Xia, Ahmed Khan, Muhammad Sadiq, Mahmood Alam, Fuad A. Awwad, Emad A. A. Ismail
    CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 2771-2793, 2024, DOI:10.32604/cmc.2024.046897
    (This article belongs to the Special Issue: Requirements Engineering: Bridging Theory, Research and Practice)
    Abstract Sentiment analysis is becoming increasingly important in today’s digital age, with social media being a significant source of user-generated content. The development of sentiment lexicons that can support languages other than English is a challenging task, especially for analyzing sentiment analysis in social media reviews. Most existing sentiment analysis systems focus on English, leaving a significant research gap in other languages due to limited resources and tools. This research aims to address this gap by building a sentiment lexicon for local languages, which is then used with a machine learning algorithm for efficient sentiment analysis.… More >

  • Open Access

    ARTICLE

    Identification of Software Bugs by Analyzing Natural Language-Based Requirements Using Optimized Deep Learning Features

    Qazi Mazhar ul Haq, Fahim Arif, Khursheed Aurangzeb, Noor ul Ain, Javed Ali Khan, Saddaf Rubab, Muhammad Shahid Anwar
    CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 4379-4397, 2024, DOI:10.32604/cmc.2024.047172
    (This article belongs to the Special Issue: Requirements Engineering: Bridging Theory, Research and Practice)
    Abstract Software project outcomes heavily depend on natural language requirements, often causing diverse interpretations and issues like ambiguities and incomplete or faulty requirements. Researchers are exploring machine learning to predict software bugs, but a more precise and general approach is needed. Accurate bug prediction is crucial for software evolution and user training, prompting an investigation into deep and ensemble learning methods. However, these studies are not generalized and efficient when extended to other datasets. Therefore, this paper proposed a hybrid approach combining multiple techniques to explore their effectiveness on bug identification problems. The methods involved feature… More >

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