practice development

This study addresses the persistent gap between learning and application in corporate software engineering training. Drawing on open-ended feedback from 174 practitioners, the authors employ reflexive thematic analysis to systematically identify five key dimensions that enhance training effectiveness: practical applicability and alignment with learner needs, instructional quality and organizational logistics, temporal and structural conditions, motivational incentives and institutional recognition, and interactive guidance coupled with social interaction. The findings reveal that significantly improving the efficacy of workplace education requires a systemic intervention integrating practice relevance, structural support, and a conducive institutional culture. Only through such a holistic approach can organizations bridge the theory–practice divide and foster meaningful learning outcomes in professional software engineering contexts.

Systematic learning from software failures remains critically underdeveloped in High-Reliability Organizations (HROs), resulting in recurrent failures. Method: This study employs a qualitative single-case design, conducting in-depth interviews with 10 software engineers at a national space research center, supplemented by cross-organizational validation interviews across five HROs. Thematic analysis reveals pervasive absence of structured processes for collecting, documenting, sharing, and applying failure knowledge. Contribution/Results: Three key barriers are identified: knowledge loss due to personnel turnover, fragmented documentation, and weak process enforcement. The study proposes an innovative “Process–Knowledge–Organization” tri-dimensional improvement framework, advocating (1) embedding learning mechanisms directly into development workflows, (2) establishing a searchable, semantically enriched failure knowledge repository, and (3) strengthening cross-functional collaboration and executive sponsorship. The framework delivers actionable, transferable practices to enhance reliability in safety-critical software systems.

This study addresses the challenges of implementing technical quality control in agile R&D projects under conditions of high technological uncertainty and experimental pressure. Through a mixed-methods approach combining survey data, quantitative statistical analysis, and qualitative content analysis, it examines the adoption, perceived effectiveness, and key obstacles related to technical quality practices—such as automated testing, code reviews, and continuous integration—among Scrum teams in technology organizations based in Manaus, Brazil. As the first exploratory investigation focused on this regional innovation ecosystem, the research establishes a baseline for understanding technical quality management in agile R&D contexts. It reveals critical issues including inconsistent practice implementation, insufficient monitoring of technical quality metrics, and a lack of effective mechanisms to evaluate technical debt from a business-value perspective.

This study addresses the dynamic, modular, and diverse demands of vocational education by proposing a systematic approach to effectively integrate requirements engineering (RE) into practitioner-oriented software engineering curricula. Grounded in three real-world course development initiatives, the approach centers on curriculum content mapping and synergistically combines modular design principles with the established RE Body of Knowledge to construct an adaptable integration framework. This framework enables flexible yet structured incorporation of RE content, significantly enhancing curricular adaptability and instructional effectiveness. Empirical validation through the implemented courses demonstrates the feasibility and practical value of the proposed method in vocational education contexts, offering a scalable model for aligning software engineering education with industry needs.

This study addresses the persistent theory–practice gaps in agile software development—specifically theoretical, temporal, and translational disconnects—by convening the Second Workshop on Agile Practice and Research, which brought together academic and industry stakeholders. Through qualitative methods including structured small-group collaboration, reflective discussions, and synthesis of outputs, the work investigates the root causes of these gaps. Building on these insights, it proposes four propositions to enhance intersection mechanisms and distills them into three research imperatives centered on open science, theoretical rigor, and value orientation. The study concludes with four practical recommendations: improving scholarly communication, aligning with industry needs, incentivizing sustained collaboration, and integrating educational practices—collectively advancing agile research toward greater transparency, methodological rigor, and practical relevance.

This study addresses the challenges in software architecture education—such as high abstraction, demanding prerequisite knowledge, lack of authentic project contexts, and limited resources—that hinder students’ practical competencies. To overcome these issues, the authors propose and empirically validate a reusable catalog of software architecture training patterns, collaboratively developed by universities in Colombia and Argentina. The approach integrates instructional patterns, a collaborative learning framework, and curriculum alignment strategies to orchestrate cross-institutional, industry-simulated development projects. Evaluation grounded in the Technology Acceptance Model (TAM) demonstrates that this method significantly enhances students’ architectural decision-making and design capabilities. The findings confirm its practicality and scalability under resource-constrained conditions, offering a novel paradigm for high-quality, inter-institutional software architecture education.

This study addresses a critical gap in software leadership research by moving beyond formal roles or theoretical models to examine how practitioners genuinely enact leadership in practice. Through a systematic content analysis of 116 self-reported articles from the Dev.to community, the authors construct the first empirical framework of software leadership grounded in social media discourse. The analysis yields 103 recommended and discouraged leadership practices, organized into five thematic categories and represented through a visual conceptual map. Findings reveal that effective software leadership centers on interpersonal and managerial competencies rather than technical expertise, thereby challenging conventional role- or technology-centric perspectives and offering a nuanced, practice-based understanding of leadership in software development contexts.

This study addresses the practical challenges of technical debt management (TDM), which often hinders long-term software evolution due to the absence of actionable processes. Through a 30-month action research project conducted in two companies—encompassing five workshops, retrospective meetings, and qualitative analysis of 96 hours of meeting transcripts—the feasibility of existing TDM approaches was systematically evaluated. The work identifies common practices and divergent strategies across multiple teams, proposes a structured technical debt item model incorporating key attributes such as interest and contagion, and distills an actionable implementation guide. All participating teams integrated dedicated debt items into their backlogs and demonstrated strong alignment in prevention and documentation practices. Key outcomes include a foundational set of best practices, strategies for addressing typical challenges, tooling recommendations, and a practitioner-oriented white paper.

This study addresses the challenges of regression testing in remote and hybrid work environments, where communication, coordination, and quality assurance are increasingly complex. Through qualitative interviews with 20 software practitioners, complemented by process analysis, tool integration assessment, and coding of collaborative practices, the research systematically investigates the sociotechnical evolution of regression testing in distributed settings. Findings indicate that while core testing phases remain largely stable, teams increasingly rely on documentation, automation, and integrated toolchains to sustain effectiveness. Standardized reporting formats, shared repositories, and traceability mechanisms significantly mitigate collaboration barriers inherent in remote work. The study offers novel insights and practical guidance for ensuring software quality in geographically dispersed development contexts.

This study addresses a critical limitation of existing DORA metrics, which rely solely on first-order statistics and thus fail to capture the distributional characteristics of software release cadence or distinguish teams with markedly different release regularity. To overcome this, the work introduces second-order statistics into the DORA framework for the first time, proposing a novel Delivery Consistency (DC) metric based on the coefficient of variation of inter-release intervals. It further constructs an eight-prototype Delivery Health Matrix to enable multidimensional diagnosis and targeted intervention for software delivery rhythms across platforms. Validation using real-world data spanning 120 weeks from four platforms—including Jira, GitHub, and Firebase—demonstrates that the approach effectively identifies teams sharing identical DORA ratings yet exhibiting divergent release patterns, uncovering underlying organizational or process constraints common to such teams.