Developer Experience (Dev-X) has emerged as a critical driver of software quality, developer productivity, and project success. However, the empirical literature remains fragmented, with limited understanding of how specific Dev-X interventions affect downstream software and business outcomes. This study aims to synthesize and map the current empirical evidence on Dev-X interventions, identifying how they influence software outcomes (e.g., code readability, collaboration) and propagate to organizational key performance indicators (KPIs) such as product quality and process efficiency. We conducted a systematic mapping study of 160 empirical articles published between 2006 and 2024. We identified 146 unique interventions that impacts software outcomes such as role match may impact on developers’ workload, likewise managing burnout in developer feedback may impact organizational culture. Using grounded coding, we also classified such mappings to 8 KPIs and 5 Dev-X dimensions based on the strength of empirical relationships (correlational, causal, classification-based) reported in the literature. Our analysis reveal that quality-related KPIs are more frequently impacted than productivity metrics, challenging traditional emphasis. Emotional state and values-oriented interventions dominate current practices, while cognitive load and motivation-focused strategies remain underexplored. Only a minority of studies (39 out of 160) explicitly trace full chains of intervention–outcome–KPI, highlighting persistent fragmentation; in other cases, we reconstructed these chains using cross-sectional synthesis of study data. Notably, recent years show an emergence of AI-assisted and value-centered intervention designs. This study consolidates the fragmented Dev-X landscape by offering an evidence-based, open-access Ready-Reckoner tool for navigating interventions and their effects. While not prescriptive, it enables structured, context-aware exploration of empirical findings and lays the foundation for future causal, longitudinal, and multi-channel Dev-X research. • We systematically map 160 empirical studies to trace how Developer Experience (Dev-X) interventions influence software outcomes and business-critical KPIs. • The study identifies 146 unique interventions and categorizes them by their targeted Dev-X facets, intermediate outcomes, and relationship strength (causal, correlational, qualitative). • Our results highlight a gap in empirical traceability between Dev-X practices and long-term organizational success, emphasizing the need for integrated evaluation frameworks. • The study identifies underexplored connections across Dev-X dimensions and advocates for research into their combined influence on developer performance and project outcomes. • We deliver an open-access, practitioner-oriented Dev-X Ready-Reckoner Tool that supports evidence-based selection of interventions aligned with organizational goals.

Summary Software architecture assists developers in addressing non‐functional requirements and in maintaining, debugging, and upgrading their software systems. Consequently, consistency between the designed architecture and the implemented software system itself is important; without this consistency the non‐functional requirements targeted may not be addressed and architectural documentation may mis‐direct maintenance efforts that target the associated code‐base. But often, when software is initially implemented or subsequently evolved, the designed architecture and software architecture become inconsistent, with the implemented structure degraded due to issues like developer time‐pressures, or ambiguous communication of the designed architecture. In such cases, Software Architecture Recovery (SAR) or consistency approaches can be applied to reconstruct the architecture of the software system and possibly to compare it to/re‐align it with the designed architecture. Many SAR approaches have been proposed in the research. However, choosing an appropriate architecture recovery approach for software systems is still an open issue. Consequently, this research aims to conduct a tertiary‐mapping study based on available secondary studies of architecture recovery approaches, to uncover important characteristics, towards the selection of appropriate SAR approaches. This research has aggregated 13 secondary studies and 10 primary studies beyond 2020 from 5 databases and, in doing so, identified 111 architecture recovery approaches. Based on these approaches, a taxonomy, containing nine main SAR‐selection categories is proposed and a framework (in the form of a supporting tool to help developers select an appropriate SAR approach) has been developed. Finally, this research identifies six potential open research gaps related to the underlying research that could be helpful for guiding research in the future.