adoption playbook design

This study addresses the persistent challenges faced by User Experience Research (UXR) teams—namely, stakeholder bias, reactive engagement, and fragmented insights—that hinder their ability to exert strategic influence. To overcome these limitations, the authors innovatively integrate structured strategic thinking into UXR function development, proposing an organizational maturity model grounded in a UXR Point-of-View (POV) framework. Complementing this model is a practical playbook that combines “offensive” and “defensive” strategies to guide implementation. This integrated approach systematically enables UXR teams to transition from tactical execution to strategic impact, significantly enhancing their capacity to forge strategic partnerships, generate actionable insights, and contribute meaningfully to long-term corporate strategy formulation.

Existing research lacks systematic methods to assess how requirements engineering (RE) impacts downstream development activities, hindering RE process optimization. Method: This paper proposes the first fitness-for-purpose RE impact assessment model, integrating a systematic literature review with multi-source empirical data to identify and structure 24 downstream development activities affected by requirements and 16 quantifiable attributes. Contribution/Results: The model bridges two critical gaps in requirements quality assessment—namely, the “activity dimension” and “measurability of impact”—by enabling empirical analysis of how specific requirements artifacts and processes concretely influence development practices. It provides a theoretically grounded framework and evidence-based decision support for precise, targeted optimization of the RE phase.

Rigid activity implementation binding in digital business processes hinders adaptation to heterogeneous organizational requirements. Method: This paper proposes a three-level dynamic binding mechanism—operating at compile time, launch time, and runtime—that enables concurrent execution of multiple implementations for the same activity and supports context-aware, dynamic customization of input/output data contracts. Integrating Software Product Line (SPL) engineering with Process-Aware Information Systems (PAIS), we develop a variability modeling and runtime feature configuration framework. Contribution/Results: Our approach achieves, for the first time, end-to-end flexible activity binding across the full process lifecycle. It overcomes the limitations of conventional single-version, static binding by enabling on-demand composition of diverse activity implementations and data interfaces within a unified process model. This significantly enhances the adaptability and configurability of process systems in multi-organizational settings.

This work addresses the limitations of traditional security auditing, which relies on manually crafted playbooks that are difficult to automate and lack cross-agent transferability. The authors propose EvoHunt, a novel framework that enables the first fully automated evolution and cross-model transfer of security audit playbooks. EvoHunt employs three types of agents—auditing, evaluation, and revision—that collaboratively optimize playbooks in a closed loop over open-source repositories without human intervention. Integrating large language models, an agent execution framework, and an evolvable playbook structure, the approach significantly enhances the vulnerability discovery and validation capabilities of weaker models. Experiments demonstrate that evolved playbooks improve end-to-end exploit success rates by 6× for Codex/GPT-5.4-xhigh and, when transferred to Qwen3.6-27B, increase target match rates from 2.4% to 6.5%, surpassing existing commercial solutions.

Prior research lacks empirical insights into the actual adoption, quality effectiveness, and influencing factors of use case (UC) descriptions in industrial practice. Method: Drawing on large-scale industrial data from multinational enterprises (2020–2024), this study employs a mixed-methods approach—combining large-scale textual statistics, expert-based quality assessment, and regression/correlation analyses—to systematically examine UC practices. Contribution/Results: It provides the first large-scale empirical evidence revealing systematic deviations between real-world UC usage and textbook norms. Findings indicate that only a few features—such as solution orientation—significantly enhance development efficiency; UC template adoption exhibits a nonlinear relationship with quality; and UC quality exerts limited, highly context-dependent influence on downstream development—challenging conventional assumptions about UC quality efficacy. These results offer novel empirical evidence and theoretical directions for requirements engineering research and practice.

This study addresses the lack of a unified theoretical foundation in traditional requirements engineering (RE) quality assessment, which often fails to integrate artifact- and process-oriented perspectives and overlooks information transmission efficiency. To bridge this gap, the paper proposes a holistic theoretical framework that models RE as a flow of information particles among stakeholders, developers, testers, and artifacts, with information flow as its core construct. Building on this model, the authors develop a simulation system to capture dynamic interactions and information exchanges across roles. The simulation reveals how high-quality requirements specifications can be inadvertently bypassed in agile environments and yields actionable insights for improving RE processes. This work establishes a theoretical basis for optimizing information flow, enhancing RE effectiveness, and understanding the underlying causes of success or failure in requirements engineering practices.

This study addresses the challenge of translating user research (UXR) data into strategically impactful insights within complex developer tooling contexts—such as AI agents, command-line interfaces, and error messaging—where traditional approaches often fall short. To bridge this gap, the work proposes a mixed-methods research framework that triangulates qualitative and quantitative data to produce high-confidence findings. Central to this approach are three structured “playbook cards”—Paradigm Shift, Explainability as Trust, and Friction Cost—that transform technical observations into compelling, irrefutable business narratives. By operationalizing a reusable pipeline from raw insight generation to strategic viewpoint formulation, this framework significantly enhances the influence and persuasive power of UXR in technology product decision-making.

This work addresses the challenge of effectively integrating process mining results into early-stage requirements engineering by proposing an automated modeling approach tailored to Use Case Maps (UCMs) within the ITU-T URN standard. By extending the PM4Py library, the authors develop the first process mining pipeline that treats UCMs as first-class outputs, supporting configurable actor mapping and nested hierarchical decomposition. The method enables high-fidelity bidirectional interoperability with the jUCMNav tool. Empirical evaluation on both public and synthetic event logs demonstrates its capability to accurately represent behavioral models across multiple abstraction levels, thereby advancing process mining as a practical enabler for model-driven requirements engineering.

研究探讨了在旧系统现代化过程中，仅依赖以利益相关者为中心的需求工程方法的局限性，并提出需要结合不确定性意识、迭代和基于证据的方法来解决新旧系统功能映射问题。

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.