The articles collected in this Research Topic highlight the growing integration of genomics and microbial ecology in advancing plant disease management and soil health. Together, they demonstrate how molecular approaches can reveal the mechanisms that shape microbial communities, uncover the genetic basis of pathogen virulence, and support the development of innovative and durable disease-control strategies.One of the recurring themes across this collection is the critical role of soil microbial communities in maintaining agricultural productivity and ecosystem stability. Han et al. (2025) explored how continuous maize cropping influences microbial community assembly over a cultivation period extending from one to twenty-five years. Their study provides compelling evidence that long-term monoculture substantially alters both bacterial and fungal communities. As cropping duration increased, bacterial communities became increasingly dominated by specific taxa, whereas dominant fungal groups gradually declined. Importantly, the authors demonstrated that microbial community assembly shifted from being largely stochastic to being increasingly governed by deterministic processes, particularly heterogeneous environmental selection. Changes in microbial co-occurrence networks further suggested that long-term continuous cropping reshapes ecological interactions within soil microbiomes. These findings deepen our understanding of how intensive agricultural practices influence microbial succession and provide a valuable ecological framework for designing sustainable soil-management strategies.The importance of agricultural management practices in shaping soil microbial ecology is further illustrated by the work of Tang et al. (2025) who investigated the effects of different rice strawreturn methods in karst paddy fields. By combining field experiments with 16S rRNA sequencing, the authors demonstrated that straw incorporation not only improved soil fertility but also influenced bacterial community composition, assembly processes, and interaction networks. Different straw-return methods generated distinct ecological outcomes, highlighting the importance of selecting management practices according to production goals. While rotary tillage incorporation produced the highest rice yield, no-till mulching and bioreactor treatments enhanced soil organic matter and nutrient accumulation while promoting more structured microbial communities. Their results further revealed that bacterial β-diversity and total nitrogen were among the strongest determinants of rice productivity. This study emphasizes that crop performance is shaped by the combined effects of soil physicochemical properties and microbial ecological processes, reinforcing the importance of microbiome-informed management approaches for sustainable agriculture.Beyond soil microbial ecology, this Research Topic also showcases the transformative role of genomics in understanding plant pathogens and improving disease control. Duan et al. ( 2025) provide the first whole-genome sequence of Phomopsis asparagi (Diaporthe asparagi), the fungal pathogen responsible for asparagus stem blight. This work represents a significant step forward in understanding the biology of an economically important disease that affects asparagus production worldwide. Through genome annotation and comparative transcriptomic analyses, the authors identified a range of virulence-associated pathways linked to oxidative stress responses, reactive oxygen species metabolism, cell-wall degradation, and programmed cell death. Their investigation of pathogen responses under elevated temperature conditions revealed a sophisticated molecular adaptation system involving stress signaling, metabolic reprogramming, DNA repair, and enzymatic activities associated with host colonization. These genomic resources and mechanistic insights establish a valuable foundation for future research aimed at developing more effective and targeted disease-management strategies.Advances in understanding pathogen biology are closely linked to innovations in plant resistance breeding. In this regard, Senthilraja et al. ( 2025) review emerging strategies that target pathogen effector proteins to achieve durable disease resistance. Effectors play a central role in plantpathogen interactions by manipulating host cellular processes and suppressing immune responses. The authors discuss a range of promising approaches, including susceptibility-gene modification, CRISPR/Cas-based genome editing, RNA interference technologies, and the use of synthetic decoys to enhance immune recognition. By focusing on effector biology, these approaches offer opportunities to develop crop varieties with broader and more durable resistance while reducing reliance on chemical control measures. The review highlights how advances in molecular genetics and biotechnology are reshaping plant protection strategies and contributing to long-term food security.Collectively, the studies presented in this Research Topic illustrate the increasingly interconnected nature of microbial ecology, genomics, and plant pathology. Although they address different biological systems and agricultural contexts, they converge on a common objective: understanding biological processes at molecular, genomic, and community levels to support more sustainable crop production systems. The studies on microbial communities demonstrate how agricultural practices shape soil ecosystem functioning and crop performance, while the genomics-focused contributions reveal the molecular mechanisms underlying pathogen virulence and plant resistance.Several broader messages emerge from this body of work. First, sustainable disease management cannot be achieved by focusing solely on pathogens; it must also account for the broader soil microbiome and its ecological functions. Second, advances in sequencing technologies continue
Some claim that especially in the field of agile software development the research lags years behind of the practice. In this paper, we characterize the status and main challenges for research on agile software development, and propose a preliminary roadmap, focusing on providing more empirical research, primarily on experienced agile teams and organizations, connecting better to existing streams of research in more established fields, giving more attention to management-oriented approaches, and finally give more emphasis to the core ideas in agile software development in order to increase our understanding. We hope that this preliminary roadmap serves as a starting point for creating a common research agenda and enables the generation of fruitful discussions and research results from the field.
Torgeir Dingsøyr, T. Dybå, P. Abrahamsson· Agile Conference· 91 citations· ⚡7
The happy-productive worker thesis states that happy workers are more productive. Recent research in software engineering supports the thesis, and the ideal of flourishing happiness among software developers is often expressed among industry practitioners. However, the literature suggests that a cost-effective way to foster happiness and productivity among workers could be to limit unhappiness. Psychological disorders such as job burnout and anxiety could also be reduced by limiting the negative experiences of software developers. Simultaneously, a baseline assessment of (un)happiness and knowledge about how developers experience it are missing. In this paper, we broaden the understanding of unhappiness among software developers in terms of (1) the software developer population distribution of (un)happiness, and (2) the causes of unhappiness while developing software. We conducted a large-scale quantitative and qualitative survey, incorporating a psychometrically validated instrument for measuring (un)happiness, with 2 220 developers, yielding a rich and balanced sample of 1318 complete responses. Our results indicate that software developers are a slightly happy population, but the need for limiting the unhappiness of developers remains. We also identified 219 factors representing causes of unhappiness while developing software. Our results, which are available as open data, can act as guidelines for practitioners in management positions and developers in general for fostering happiness on the job. We suggest considering happiness in future studies of both human and technical aspects in software engineering.
D. Graziotin, Fabian Fagerholm, Xiaofeng Wang et al.· International Conference on...· 84 citations· ⚡6
To compete in this age of disruption, large companies cannot rely on cost efficiency, lead time reduction and quality improvement. They are now looking for ways to innovate like startups. Meanwhile, the awareness and use of the Lean startup approach have grown rapidly amongst the software startup community in recent years. This study investigates how Lean internal startup facilitates software product innovation in large companies and identifies its enablers and inhibitors. A multiple case study approach is followed in the investigation. Two software product innovation projects from two large companies are examined, using a conceptual framework that is based on the method-in-action framework and extended with the previously developed Lean-Internal Corporate Venture model. Seven face-to-face in-depth interviews of the employees with different roles are conducted. Within-case analysis and cross-case comparison are applied to draw the findings from the cases. A generic process flow summarises the common key processes of Lean internal startups. The findings suggest that an internal startup that is initiated management or employees faces different challenges. A list of enablers of applying Lean startup in large companies are identified, including top management support and cross-functional team. Both cases face different inhibitors due to the different process of inception, objective of the team and type of the product. Our contributions are threefold. First, this study is one of the first attempt to investigate the use of Lean startup approach in large companies empirically. Second, the study shows the potential of the method-in-action framework to investigate the Lean startup approach in non-startup context. The third is a general process of Lean internal startup and the evidence of the enablers and inhibitors of implementing it, which are both theory-informed and empirically grounded.
Henry Edison, Nina M. Smørsgård, Xiaofeng Wang et al.· Journal of Systems and Softw...· 78 citations· ⚡6
In this paper, we present a novel approach to improving software quality and efficiency through a Large Language Model (LLM)-based model designed to review code and identify potential issues. Our proposed LLM-based AI agent model is trained on large code repositories. This training includes code reviews, bug reports, and documentation of best practices. It aims to detect code smells, identify potential bugs, provide suggestions for improvement, and optimize the code. Unlike traditional static code analysis tools, our LLM-based AI agent has the ability to predict future potential risks in the code. This supports a dual goal of improving code quality and enhancing developer education by encouraging a deeper understanding of best practices and efficient coding techniques. Furthermore, we explore the model's effectiveness in suggesting improvements that significantly reduce post-release bugs and enhance code review processes, as evidenced by an analysis of developer sentiment toward LLM feedback. For future work, we aim to assess the accuracy and efficiency of LLM-generated documentation updates in comparison to manual methods. This will involve an empirical study focusing on manually conducted code reviews to identify code smells and bugs, alongside an evaluation of best practice documentation, augmented by insights from developer discussions and code reviews. Our goal is to not only refine the accuracy of our LLM-based tool but also to underscore its potential in streamlining the software development lifecycle through proactive code improvement and education.
Z. Rasheed, Malik Abdul Sami, Muhammad Waseem et al.· arXiv.org· 62 citations· ⚡3
Agile methods continue to gain popularity. In particular, the Scrum method appears to be on the verge of becoming a de-facto standard in the industry, leading the so called Agile movement. While there are success stories and recommendations, there is little scientifically valid evidence of the challenges in the adoption of Agile methods in general, and Scrum in particular. Little, if anything, is empirically known about the application and adoption of Scrum in a multi-team and multi-project situation. The authors carried out an ethnographically informed longitudinal case study in industrial settings and closely followed how the Scrum method was adopted in a 20-person department, working in a simultaneous multi-project R&D environment. Altogether 10 challenges pertinent to the case of multi-team multi-project Scrum adoption were identified in the study. The authors contend that these results carry great relevance for other industrial teams. Future research avenues arising from the study are indicated.
A. Marchenko, P. Abrahamsson· Agile Conference· 59 citations· ⚡11
Molecular dynamics simulations hold great promise for providing insight into the microscopic behavior of complex molecular systems. However, their effectiveness is often constrained by long timescales associated with rare events. Enhanced sampling methods have been developed to address these challenges, and recent years have seen a growing integration with machine learning techniques. This Review provides a comprehensive overview of how they are reshaping the field, with a particular focus on the data-driven construction of collective variables. Furthermore, these techniques have also improved biasing schemes and unlocked novel strategies via reinforcement learning and generative approaches. In addition to methodological advances, we highlight applications spanning different areas, such as biomolecular processes, ligand binding, catalytic reactions, and phase transitions. We conclude by outlining future directions aimed at enabling more automated strategies for rare-event sampling.
Kai Zhu, Enrico Trizio, Jintu Zhang et al.· Chemical Reviews· 54 citations