agile methodologies

Current DevOps practices in the IT industry suffer from insufficient integration of agile methodologies, leading to suboptimal coordination across development and operations. Method: This study employs semi-structured interviews and thematic analysis with 11 frontline practitioners to empirically investigate integration challenges and opportunities. From the data, 51 initial codes were derived and consolidated into 19 core themes. Contribution/Results: The research uncovers dynamic synergies between agile principles and DevOps practices—particularly in continuous integration, continuous deployment, and cross-functional collaboration—and proposes the first comprehensive, lifecycle-spanning framework for deep agile–DevOps integration. The framework explicitly articulates their complementary logic and actionable implementation pathways, demonstrably enhancing the predictability and consistency of software delivery speed and quality. It thus provides both a theoretical foundation and a practical, operationally grounded guide for agile–DevOps convergence.

This study addresses the challenge of integrating strategic planning into agile development without compromising its empirical control and responsiveness. To this end, the authors propose the Milestone-Driven Agile Execution (MDAX) framework, which aligns project execution with organizational objectives by using strategic milestones to guide backlog prioritization. MDAX decouples high-level strategic planning from low-level implementation through a methodology-agnostic and mechanism-decoupled design, enabling organizations to flexibly adopt development practices best suited to their context. The framework enhances strategic alignment of project delivery while preserving the core agility needed for rapid adaptation. As such, MDAX offers an innovative and scalable solution for hybrid project management that effectively bridges strategic intent and agile execution.

This study addresses the pedagogical challenge of teaching the threshold concept of “empirical process control” in Scrum by designing a lightweight, free, customizable, and scalable sprint simulation activity. Integrating the threshold concepts framework with active learning, the approach guides students through a single instructional session in which they practice visualizing work status, selecting tasks, and allocating resources, thereby directly experiencing decision-making grounded in empirical feedback. The method combines direct instruction with interactive simulation and employs abductive analysis to evaluate its effectiveness. Implementation across master’s-level courses at two universities and a teaching assistant training program at another institution demonstrates that the simulation significantly enhances students’ understanding of empirical process control, confirming its viability and efficacy as a cross-institutional tool for teaching agile development.

To address inefficient sprint planning and perfunctory retrospective meetings in Agile/Scrum, this paper proposes RetroAI++—the first lightweight temporal reasoning framework integrating meeting transcripts, task logs, and code-level behavioral traces. Methodologically, it innovatively combines fine-tuned lightweight LLMs, event graph modeling, multi-granularity sentiment-topic joint analysis, and real-time incremental knowledge distillation to enable end-to-end interpretable process intelligence enhancement. Evaluated across eight real-world Scrum teams, RetroAI++ improves sprint plan validity by 37%, achieves 89.2% accuracy in generating actionable retrospective items, and reduces average meeting duration by 42%. This work establishes a deployable, interpretable, and evolvable AI-augmentation paradigm for Agile practice.

This study addresses the persistent challenges impeding the effective integration of Agile and DevOps practices, which are often constrained by cultural, organizational, procedural, and technological barriers that undermine software delivery performance. Through semi-structured interviews with six senior practitioners from Brazil and Germany, the research employs qualitative thematic analysis to systematically identify—within a cross-national context—four core integration challenges and proposes a corresponding solution framework. The findings underscore the pivotal roles of cultural alignment, team autonomy, process coordination, and infrastructure automation, highlighting that organizational and cultural factors are critical enablers of successful technical integration. By elucidating these interdependencies, the study offers actionable, cross-cultural guidance for software organizations seeking to enhance their Agile–DevOps convergence and overall delivery effectiveness.

This study investigates the effective adaptation of Scrum methodology to support student-led, long-term software projects under academic constraints and hybrid work conditions. Through a year-long case study tracking an eight-member team developing a virtual reality educational campus game, the research introduces lightweight coordination mechanisms, one-week sprints, and flexible ceremonies aligned with academic calendars, exam pressures, and remote collaboration needs. A toolchain integrating Discord, Notion, and GitHub, complemented by contribution metrics and a custom Communication Effectiveness Index (0.76/1.00), enables multidimensional team performance assessment. Findings demonstrate that lightweight coordination sustains consistent remote progress, while adaptable Scrum practices effectively balance academic workloads. The study further highlights the critical influence of non-process factors—such as motivation, role clarity, and work-style compatibility—on team success, offering a reusable framework and empirical guidance for agile practices in educational settings.

This work proposes Visual Milestone Planning (VMP), a novel approach that addresses the lack of intuitive, collaborative milestone planning mechanisms in hybrid development environments where agile teams struggle to integrate with traditional planning paradigms. VMP innovatively combines a milestone planning matrix with a physically inspired visual scheduling mechanism: product backlog items are mapped to milestones and arranged as Tetris-like work packages on a resource–time canvas, enabling dynamic determination of milestone deadlines. By bridging agile practices with conventional project planning, the method significantly enhances team collaboration, planning transparency, and shared understanding of delivery cadence.

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 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.