product development

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 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 addresses the persistent paradox of engineering managers in agile software development: despite agile’s emphasis on decentralization and team autonomy, the engineering manager role remains salient. Adopting a mixed-methods approach—integrating systematic literature review with multi-case empirical investigation—the research identifies three interlocking drivers of this persistence: historical path dependence, theoretical tensions (e.g., balancing autonomy with cross-team coordination), and organizational constraints (e.g., technical debt governance, inter-team alignment, and talent development). Based on these findings, the paper proposes the “adaptive leadership” conceptual model, positioning engineering managers not as control-oriented supervisors but as enablers and architects who focus on technical strategy alignment, capability co-development, and systemic resilience. The model offers a theoretically grounded framework for rethinking leadership in agile organizations, informing management tool design and guiding future empirical inquiry. (149 words)

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 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 challenges faced by SAE Level 4 autonomous driving systems in handling internal and external disturbances and faults, which are often exacerbated by a lack of stakeholder consensus on performance metrics and interface requirements, leading to non-traceable architectural decisions and inefficient communication. To overcome these issues, this work proposes a process-oriented engineering methodology that employs structured steps to harmonize multi-stakeholder requirements, explicitly define the performance metrics and interface specifications necessary for self-awareness and self-adaptation capabilities, and systematically integrate traceability and knowledge transfer mechanisms into the architecture design process. Validated within the autotech.agil project, the approach significantly enhances requirement consistency, decision transparency, and collaboration efficiency, while yielding key practical insights and directions for future improvement.

This study addresses the inefficiencies in requirements management within large-scale agile development, stemming from the absence of a unified requirements engineering process and high-level guiding principles. Through a five-year longitudinal industrial case study encompassing over 25 sprints, more than 320 weekly meetings, seven cross-organizational workshops, and focused group interviews, the research employs thematic analysis to distill six transferable and scalable core principles—such as architectural context, stakeholder-driven validation, and lightweight documentation evolution. Validated across multiple multinational enterprises, these principles significantly enhance requirements management effectiveness in large-scale agile settings. This work presents the first systematic strategic requirements engineering framework tailored specifically for such complex environments.

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 the challenge of transforming stakeholder requirements into product requirements in software-driven automotive systems. Leveraging a dataset of 8,082 stakeholder requirements and 5,870 product requirements provided by Infineon, the research employs a hybrid methodology integrating structural statistics, decision modeling, traceability mining, textual analysis, and hardware-software linkage to systematically analyze the requirement refinement process. It reveals, for the first time, that requirement complexity primarily stems from ambiguous architectural scope and missing contextual information rather than linguistic redundancy. The work establishes a classification framework for mapping stakeholder to product requirements, identifies systematic differences across abstraction levels, and proposes key improvements in requirement validation, deviation management, and contextual tooling to support efficient and reusable automotive development.

This study addresses the persistent challenge organizations face in aligning DevOps automation initiatives with strategic objectives such as waste reduction, delivery predictability, cross-team collaboration, and customer-perceived quality. To bridge this gap, the authors propose a unified VSM–GQM–DevOps framework that integrates Value Stream Mapping (VSM), the Goal-Question-Metric (GQM) approach, and DevOps practices. The framework enables identification of delivery bottlenecks, construction of decision-oriented measurement models, and implementation of maturity-aligned, reversible automation interventions, thereby establishing an auditable and traceable pathway for automation investment. Validated through a multi-site longitudinal study employing DORA metrics, interrupted time series analysis, and mixed-methods evaluation, the framework demonstrates significant improvements in delivery performance and project management outcomes, fostering continuous, strategy-aligned improvement.