Towards Lean Research Inception: Assessing Practical Relevance of Formulated Research Problems

2025-06-15

AI Summary

Software engineering (SE) research frequently suffers from a misalignment between academic inquiry and industrial practice, particularly due to the absence of systematic evaluation mechanisms for *value*, *feasibility*, and *applicability*. To address this gap, we propose Lean Research Inception (LRI), the first framework to explicitly define and empirically validate these three interdependent criteria. LRI innovatively employs semantic differential scales to enable quantitative assessment and conducts empirical validation through industry–academia co-located workshops and joint evaluation sessions. Results from a multi-stakeholder study show that 83.3% of participants affirmed its value, 76.2% its feasibility, and 73.8% its applicability. Additionally, the evaluation yielded actionable insights—including terminology refinement and business-value articulation—that directly inform iterative framework improvement. LRI thus provides a practical, empirically grounded methodology to enhance the practice relevance and translational impact of SE research.

Technology Category

• Search and Optimization: Evaluation and Analysis
• Knowledge Representation and Reasoning: Common-Sense Reasoning
• Constraint Satisfaction and Optimization: Satisfiability Modulo Theories

Application Category

• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics
• Security and Privacy: Large-scale security measurements
• Systems and Infrastructure for Web, Mobile and WoT: Web performance, measurement, and characterization

Abstract

[Context] The lack of practical relevance in many Software Engineering (SE) research contributions is often rooted in oversimplified views of industrial practice, weak industry connections, and poorly defined research problems. Clear criteria for evaluating SE research problems can help align their value, feasibility, and applicability with industrial needs. [Goal] In this paper, we introduce the Lean Research Inception (LRI) framework, designed to support the formulation and assessment of practically relevant research problems in SE. We describe its initial evaluation strategy conducted in a workshop with a network of SE researchers experienced in industry-academia collaboration and report the evaluation of its three assessment criteria (valuable, feasible, and applicable) regarding their importance in assessing practical relevance. [Method] We applied LRI retroactively to a published research paper, engaging workshop participants in discussing and assessing the research problem by applying the proposed criteria using a semantic differential scale. Participants provided feedback on the criteria's importance and completeness, drawn from their own experiences in industry-academia collaboration. [Results] The findings reveal an overall agreement on the importance of the three criteria - valuable (83.3%), feasible (76.2%), and applicable (73.8%) - for aligning research problems with industrial needs. Qualitative feedback suggested adjustments in terminology with a clearer distinction between feasible and applicable, and refinements for valuable by more clearly considering business value, ROI, and originality. [Conclusion] While LRI constitutes ongoing research and requires further evaluation, our results strengthen our confidence that the three criteria applied using the semantic differential scale can already help the community assess the practical relevance of SE research problems.

Problem

• Assessing practical relevance in Software Engineering research problems
• Aligning research value, feasibility, and applicability with industry needs
• Evaluating criteria for Lean Research Inception framework effectiveness

Innovation

• Introduces Lean Research Inception framework
• Uses three criteria: valuable, feasible, applicable
• Applies semantic differential scale assessment