Beyond Patchwork: Why Software Engineering Research Needs a Systems Reset

by

Author: Denis Avetisyan

A new review argues that incremental improvements to software engineering research are failing to address fundamental problems within the field’s evaluation and publication practices.

The paper analyzes software engineering research as a complex ecosystem and advocates for systemic reform based on a theory of change approach.

Despite substantial productivity, software engineering research continues to grapple with persistent challenges-from overburdened peer review to distorted publication incentives. This paper, ‘SE Research is a Complex Ecosystem: Isolated Fixes Keep Failing — and Systems Thinking Shows Why’, argues these issues aren’t isolated incidents, but symptoms of deeper structural dynamics within the research ecosystem itself. By framing these challenges through the lens of complex systems and theory of change, we reveal reinforcing feedback loops and identify more effective leverage points for reform beyond piecemeal solutions. Can a holistic, ecosystem-level approach finally unlock meaningful and sustainable progress in software engineering research?

The Cracks in the Foundation: A System Under Strain

Software engineering research functions on a largely unspoken agreement: that public and private investment in innovation is justified by the promise of tangible benefits to society. This social contract underpins the entire field, driving inquiry into more reliable, efficient, and user-friendly technologies. The expectation is that research efforts will ultimately translate into improvements across diverse sectors, from healthcare and education to infrastructure and communication. However, the increasing pressures within the research ecosystem – exemplified by a surge in publications and emerging concerns regarding research integrity – are beginning to test the strength of this foundational agreement, raising questions about whether the pursuit of novelty is consistently aligned with genuine societal good and long-term impact.

The foundations of software engineering research are facing unprecedented strain due to a rapidly escalating volume of published papers-a phenomenon researchers term a ‘publication tsunami’. Recent data indicates a significant increase in researcher output, with 18% reporting the publication of over 20 papers in just the last three years. This surge overwhelms established quality control measures, particularly the peer review process, designed to validate research rigor and originality. Consequently, the system struggles to effectively assess the true contribution of each work, creating vulnerabilities and raising concerns about the overall quality and reliability of the published body of knowledge within the field. The sheer quantity of submissions diminishes the time reviewers can dedicate to each paper, potentially leading to superficial evaluations and a compromised ability to detect flawed methodologies or unsubstantiated claims.

The escalating volume of software engineering research presents critical vulnerabilities within the field’s quality control systems. Recent data indicates that half of surveyed researchers are experiencing pressures related to publication, fostering an environment where questionable practices can flourish. This is increasingly evident in the emergence of ‘paper mills’ – operations dedicated to producing and selling fabricated research – and the potential for misuse of generative AI tools to create plausible but ultimately unsubstantiated findings. The sheer quantity of submissions overwhelms traditional peer review, diminishing its effectiveness and raising concerns about the reliability of published work. This situation not only threatens the integrity of the research itself, but also undermines the social contract underpinning software engineering innovation – the promise of delivering societal benefit through rigorously validated knowledge.

A Web of Dependencies: Beyond Linear Progress

The software engineering (SE) research ecosystem functions as a complex system, deviating from a simple linear model of progression from research input to practical application. This systemic nature is defined by interdependencies between constituent parts – researchers, institutions, funding sources, publishers, and industry – where actions within one component directly and indirectly influence others. For example, funding priorities shape research directions, which subsequently impact publication output, and ultimately affect the types of innovations adopted by industry. These interactions are not isolated; rather, they form a web of relationships where the performance of the entire system relies on the coordinated function of its individual components and the strength of the connections between them. Consequently, understanding the ecosystem requires analyzing these relationships, rather than focusing solely on isolated elements.

Non-linear feedback loops within the SE research ecosystem describe situations where the results of an action alter and recirculate as inputs to the same or other system components, creating effects disproportionate to the initial cause. This means a small change in one area – for example, increased funding for a specific research direction – can trigger a cascade of consequences, potentially exacerbating existing inequalities or creating new bottlenecks. Conversely, seemingly minor obstacles, such as delays in peer review, can compound over time, hindering progress and impacting researcher productivity. These loops are not always predictable; positive feedback amplifies effects, while negative feedback attempts to counteract them, but the interplay can generate emergent behaviors and unintended consequences that are difficult to anticipate through linear analysis.

Applying Ecosystems Theory and Complex Systems Theory to the software engineering research landscape allows for a more nuanced understanding of interdependencies beyond simple linear models. These frameworks facilitate the identification of critical vulnerabilities by recognizing that components within the system-research funding, publication venues, researcher time, and peer review-are interconnected and subject to emergent behavior. Notably, a recent survey indicated that 40% of respondents identified publication as their greatest stressor, suggesting this component represents a significant point of strain and a potential failure mode within the broader research ecosystem. Analyzing publication pressures through a complex systems lens can reveal how this stressor propagates through the system, impacting research quality, researcher wellbeing, and overall innovation rates, and allows for targeted interventions to improve systemic resilience.

Beyond Counting Papers: Evaluating Real Impact

Traditional bibliometric indicators, such as journal impact factor and citation counts, primarily assess the quantity of published work rather than its qualitative impact or relevance within complex systems. These metrics often fail to account for negative results, methodological rigor, or the broader societal implications of research. They are also susceptible to manipulation, such as self-citation and citation cartels, and do not effectively capture interdisciplinary contributions or the impact of research outside of academic circles. Consequently, relying solely on these indicators can lead to a skewed understanding of research quality and may not accurately reflect the true value of scientific endeavors, particularly within fields dealing with multifaceted and interconnected problems.

Systematic Literature Reviews (SLRs) represent a more structured and comprehensive approach to synthesizing research findings than traditional narrative reviews, employing predefined search strategies, explicit inclusion/exclusion criteria, and quality assessment of included studies. However, SLRs are not without limitations in fully capturing research impact. They primarily focus on evaluating evidence related to specific, pre-defined research questions and may struggle to assess broader, indirect, or long-term consequences not explicitly addressed in the included studies. Furthermore, SLRs can be susceptible to publication bias, where studies with statistically significant or positive results are more likely to be included, potentially overestimating the overall effect. The inherent scope of an SLR, while rigorous, may therefore prove insufficient for evaluating the holistic impact of research, particularly within complex systems where effects are often multi-faceted and emergent.

Evaluating research necessitates a focus on long-term consequences, extending beyond immediate citation counts or journal impact factors. This is increasingly critical given the escalating volume of scholarly output; projections estimate over 600 software engineering papers will be published by ACM/IEEE journals in 2025 alone. Consequently, robust data and methodological preservation, alongside transparent reporting, are essential for enabling future validation, replication, and building upon existing work. Without a commitment to stewardship, the sheer volume of research risks diminishing the ability to effectively synthesize knowledge and assess true, lasting impact.

The Promise of Integration: Building a Better Future

Software engineering’s ultimate significance resides not solely within its technical advancements, but in its capacity to address tangible societal challenges and catalyze positive transformation. The discipline’s true value is realized when innovations seamlessly integrate with real-world needs, impacting areas such as healthcare, education, and environmental sustainability. This requires a deliberate shift in focus, moving beyond purely technical metrics to prioritize outcomes that demonstrably improve lives and contribute to the common good. By actively seeking opportunities to connect research with practical applications, software engineering can evolve from a field primarily concerned with building systems, to one dedicated to building a better future, fostering inclusivity, and driving progress across all sectors of society.

Sustainable innovation demands a deliberate shift towards knowledge creation, moving beyond mere application of existing principles. This necessitates cultivating environments that encourage innovative thinking, not just within isolated disciplines, but through collaborative exploration that bridges academic silos and engages diverse perspectives. Responsible development is paramount; research must proactively address potential societal impacts, ensuring that advancements align with ethical considerations and contribute to equitable outcomes. By prioritizing the generation of new understandings and fostering a holistic approach to problem-solving, the field can unlock its full potential for positive change and lasting societal benefit.

The ultimate impact of software engineering research hinges on effective knowledge transfer, necessitating strategies that extend beyond traditional academic publishing. While specialized journals like Computing Surveys serve a critical role, their limited reach – a mere five papers published in 2025 – highlights a significant bottleneck in disseminating vital findings to those who can apply them. This restricted access hinders informed decision-making in industry and policy, underscoring the urgent need for broader dissemination channels. Researchers must actively pursue methods to translate complex findings into accessible formats, engage with practitioners, and foster collaborations that ensure research insights translate into tangible societal benefits and drive meaningful innovation beyond the confines of academia.

The pursuit of isolated improvements in software engineering research, as detailed in the article, frequently yields diminishing returns. One expects as much. Grace Hopper famously observed, “It’s easier to ask forgiveness than it is to get permission.” This rings true because systemic issues, like those impacting publication practices and research evaluation, inevitably constrain even the most elegant theoretical advances. The article rightly points to the need for a coordinated, holistic approach; optimization, after all, will one day be optimized back. Architecture isn’t a diagram, it’s a compromise that survived deployment, and the same holds for research ecosystems-a series of necessary concessions to navigate a messy reality.

What’s Next?

The assertion that software engineering research suffers from systemic failings isn’t novel, yet the persistence of isolated ‘solutions’ suggests a certain stubbornness within the field. The paper highlights the mismatch between theoretical elegance and the messy reality of production systems – a gap that will likely widen as complexity increases. Expect more papers proposing ‘revolutionary’ frameworks, each destined to become tomorrow’s technical debt. Tests, as always, will remain a form of faith, not certainty.

Future work will inevitably focus on quantifying the ‘health’ of the research ecosystem itself. Metrics will be proposed, dashboards will be built, and the very act of measurement will introduce new, unforeseen distortions. The call for a ‘theory of change’ is reasonable, but the field should prepare for the fact that even well-articulated theories struggle when confronted with the inherent unpredictability of large-scale software development.

Ultimately, the most promising path may lie not in grand unified theories, but in embracing a kind of pragmatic resilience. Systems will fail. Processes will be circumvented. The challenge isn’t to prevent these failures, but to build systems – and research practices – that degrade gracefully when they inevitably occur. Automation, it should be noted, has a habit of deleting production data.

Original article: https://arxiv.org/pdf/2601.16363.pdf

Contact the author: https://www.linkedin.com/in/avetisyan/

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2026-01-26 20:01