Awakening: Modern Challenges and Opportunities of Software Engineering Research

2026-03-22

AI Summary

Current software engineering research is constrained by the large scale and closed-source nature of core industrial systems, as well as the opacity of real-world deployment environments, which hinder the reproducibility and in-depth investigation of practical challenges. This work systematically examines the evolution of research paradigms through a literature review and trend analysis, uncovering structural bottlenecks and advocating for transformative—rather than incremental—change. Its central contribution lies in proposing a novel research organizational model grounded in industrial PhD programs, sustained academia–industry collaboration, and large-scale research teams, complemented by aligned evaluation mechanisms. Together, these elements offer a strategic framework and actionable pathways to fundamentally reshape the software engineering research ecosystem.

Technology Category

• Application Domains: Software Engineering
• Cognitive Modeling & Cognitive Systems: (Computational) Cognitive Architectures
• Search and Optimization: Evolutionary Computation

Application Category

• User Modeling, Personalization and Recommendation: Practical large-scale studies of user experience
• Web Mining and Content Analysis: Models for Web evolution
• Systems and Infrastructure for Web, Mobile and WoT: Web performance, measurement, and characterization

Abstract

Software engineering research benefited for decades from openly available tools, accessible systems, and problems that could be studied at modest scale. Today, many of the most relevant software systems are large, proprietary, and embedded in industrial contexts that are difficult to access or replicate in academia. We review how the field reached this point, identify structural challenges facing contemporary research, and argue that incremental methodological refinement is insufficient. We discuss practical directions forward, including industrial PhDs, long-term industry-academia collaborations, larger research teams, moonshot projects, and changes to funding and evaluation practices.

Problem

• software engineering research
• proprietary systems
• industrial context
• research accessibility
• large-scale systems

Innovation

• software engineering research
• industry-academia collaboration
• research methodology
• structural challenges
• moonshot projects