Information is all you need: Requirements Engineering Quality Reframed

Qualitative Analysis of Industry Personnel’s Perspective on Future Ready Software Engineering Undergraduate Employability

In order to determine whether a requirements statement has been well-defined, it is necessary to read the statement from the developer’s perspective. Requirements engineering (RE) encompasses all activities involved in discovering, documenting, and maintaining a set of requirements for a system. The importance of RE can be understood in light of the problems software developers face in attempting to anticipate stakeholders’ requirements.  The failure to correctly predict stakeholders’ requirements would result in a lot of extra work. Without accurate, consistent, and complete requirements specifications, it is very difficult to develop, change, and maintain software.  The objective of this research is to obtain feedback from industry experts to understand the challenges related to the employability of future-ready software engineering undergraduate students. This research employs a qualitative study to gather the views of the experts. The NVivo tool is used to analyze the data. The results of the sources are written in free node code. The practitioners agreed that the problem regarding undergraduate students is due to students being taught only theories but given a project assignment to complete in their final semester. The current industry practice is to form a team; follow a specific process for developing software, beginning with meeting the correct requirements, and staying abreast of requirement changes based on received feedback. To align practices across higher education and industry, practitioners proposed better collaboration between institutions of higher education and industry by regularly assigning hands-on projects to equip students with the required knowledge and skills. This ensure that graduating students have the knowledge and skills to make a smooth, competent transition from student to employee. 

From Metrics to Improvement: A Lifecycle-Aware LLM Feedback Framework for Research Software Quality

Research software is increasingly central to scientific workflows, yet it is often developed by researchers with limited software engineering expertise. This can lead to quality issues that hinder maintainability, reproducibility, reuse, and sustainability. Existing static analysis tools can identify such issues, but their outputs often require expert interpretation and provide limited support for translating quality assessments into actionable improvements. To address this gap, we propose a lifecycle-aware framework that integrates quantitative software quality assessment with Large Language Model (LLM)-based code refinement. The framework comprises two stages. First, a lifecycle-aware Quality Model is developed from established software quality standards and practitioner requirements. The model defines five quality dimensions and 25 candidate metrics, of which 14 are operationalized using existing analysis tools and custom measurements. Second, the resulting quality diagnostics are used as structured feedback within an iterative LLM-based refinement process, enabling generated improvements to be repeatedly reassessed against the Quality Model. We evaluate the framework on notebook-centric research software using multiple LLMs and compare iterative structured feedback with single-step feedback and unstructured prompting. The results show improvements in specific quality attributes, particularly code duplication and structural quality, while also revealing trade-offs among maintainability, code size, documentation, and complexity. These findings demonstrate the potential of metric-driven LLM feedback for research software quality improvement while highlighting its inherently multi-objective nature \footnote{The source code and experimental data are publicly available at https://github.com/QCDIS/Software_Quality_Control_LLM . }

A Theoretical Framework for Requirements Management in Complex Engineering Projects

Requirements management is fundamental to complex projects, especially in areas such as engineering, infrastructure, and defense. This article develops an integrative theoretical framework for requirements management in complex projects, grounded in a PRISMA-guided systematic literature review with a qualitative synthesis of the key dimensions of the field. In this review, 136 studies selected from an initial set of 519 records identified across multiple databases were reviewed. Five pillars were found to underpin the proposal: (i) the definition and traceability of requirements, (ii) the mitigation of uncertainties and risks, (iii) team maturity, (iv) digitalization and organizational transformation, and (v) the application of model-based systems engineering (MBSE). A literature review revealed that high-quality requirements reduce errors, improve predictability, and optimize resources, whereas digital approaches and collaborative practices strengthen the adaptive capacity of projects. Thus, in the proposed framework, these dimensions are organized into a hierarchical structure, with an emphasis on the integration of technical, organizational, and digital processes. One limitation is the lack of empirical validation, necessitating future studies on the practical application of the model in real projects, interviews with experts, and the development of operational metrics. This conceptual model is aimed at contributing to the literature and supporting more resilient, automated, and sustainability-oriented practices in complex environments.

The Journal of Systems & Software

Integrating Human-factors into Enterprise Architecture Leveraging Ontologies and Metamodels

This paper builds on the author’s previous work regarding domain-specific ontologies (DSO) and its importance in the human-factors integration (HFI) space. Explicit term definitions captured by a DSO allow the HFI vocabulary to be mapped into a model-based enterprise architecture (MBEA). Integrating this terminology into the overall MBEA provides insight into the role that individuals play by considering personnel as a critical system component. Often considered external actors, human resources are typically not accounted for in the original solution design. However, MBEA promises to reverse this trend by implementing the Unified Architecture Framework (UAF). The UAF is composed of various domains and their aspects and is meant to graphically illustrate enterprise concepts such as strategy, operations, resources, personnel, and services in a digital environment. Capturing HFI information in a model improves the traceability of person(s) and organizational concerns, responsibilities, and competencies to highlight gaps that must be addressed. The incorporation of the HFI DSO into an MBEA enhances communication between disciplines and provides transparency for stakeholders. This research demonstrates the feasibility of constructing a DSO based on an HFI body of knowledge; leveraging the Web Ontology Language (OWL), the subject-predicate-object (SPO) approach, and the Protégé ontology editor. It also shows that by importing the OWL file into a concept model, understanding HFI terms facilitates MBEA while maintaining personnel as a critical part of a successful organization. This research identifies areas for improvement of the UAF domain-specific modeling language (DSML) to ensure that it adequately addresses HFI concerns by mapping like-terms.

Frameworks for Transitioning from Technology-Siloed to Cross-Functional Engineering Teams in Modern Software Organizations

Software organizations often keep frontend, backend, mobile, infrastructure, and quality-assurance engineers in separate units long after product delivery has begun to depend on joint ownership across these domains. The separation protects specialist knowledge, yet it creates delays when one feature moves through several queues before release. This review examines phased transition patterns from technology-siloed structures toward cross-functional engineering teams. It draws on recent software engineering literature on agile teamwork, DevOps structures, continuous delivery, platform teams, scaled autonomy, communities of practice, and human factors in agile projects. The method combines comparative source analysis, conceptual synthesis, typological classification, and analytical generalization. The review identifies structural limits of silo-based delivery, compares transition mechanisms, and develops a practical interpretation of staged ownership transfer. The proposed approach links cross-functional restructuring with federated governance, enabling teams, quality practices embedded in development, and monitoring indicators covering flow, reliability, collaboration, capability, and sustainability.