From Papers to Progress: Rethinking Knowledge Accumulation in Software Engineering

2026-04-17

AI Summary

This study addresses the pervasive problem of knowledge fragmentation in software engineering research, which hinders scientific progress due to insufficient mechanisms for accumulation, integration, and reuse. Through a large-scale survey of 280 experienced researchers, complemented by qualitative content analysis and systematic diagnosis, the work proposes four technology-agnostic principles: structured and interpretable articulation of claims and evidence, traceable documentation of methodological decisions, evolvable long-term research foundations, and incentive-aligned knowledge governance mechanisms. The findings reveal a fundamental tension between high research productivity and effective knowledge integration, offering both theoretical grounding and practical guidance for reimagining research outputs, reforming publication norms, and building community infrastructure that supports cumulative knowledge construction.

Technology Category

• Knowledge Representation and Reasoning: Knowledge Engineering
• Data Mining & Knowledge Management: Representing, Reasoning, and Using Provenance, Trust
• Reasoning under Uncertainty: Other Foundations of Reasoning under Uncertainty

Application Category

• Semantics and Knowledge: Scalable techniques for the creation, curation, publication, maintenance, and consumption of large, Web-based, structured, reusable, knowledge graphs and ontologies
• Security and Privacy: Data transparency and provenance
• Web Mining and Content Analysis: Bridging structured and unstructured data

Abstract

Software engineering research has experienced rapid growth in both output and participation over the past decades. Yet concerns persist about the field's ability to accumulate, integrate, and reuse knowledge in ways that support long-term progress. To better understand how the community itself perceives these challenges, we analyze responses from the ICSE 2026 Future of Software Engineering pre-survey, which captures perspectives from 280 globally distributed and highly experienced researchers. Our analysis reveals a tension between increasing research productivity and the limited mechanisms available for synthesizing results, tracking evolving claims, and supporting cumulative understanding over time. Building on these observations, we diagnose four interrelated structural breakdowns: papers function as isolated knowledge units with claims embedded in prose; context and provenance are lost as knowledge moves through the publication pipeline; claims evolve without systematic tracking; and incentive structures favor novelty over consolidation. We argue that addressing these barriers requires rethinking the fundamental properties of research artifacts. We articulate four technology-agnostic principles for future research artifacts: structured and interpretable representations of claims and evidence; inspectable and provenance-aware documentation of methodological decisions; long-lived and reusable substrates that evolve beyond publication; and governance mechanisms that align individual incentives with collective knowledge-building goals. We discuss implications for research practice, publication norms, and community infrastructure, positioning FOSE as a venue for experimenting with alternative artifact designs that support cumulative scientific progress.

Problem

• knowledge accumulation
• software engineering
• research artifacts
• claim tracking
• scientific progress

Innovation

• knowledge accumulation
• research artifacts
• structured claims
• provenance-aware documentation
• incentive alignment