An important theme that emerged from this Research Topic is the toxicological safety assessment of novel foods including genotoxicity and repeated dose toxicity. Schreppler et al., employed a standard battery of in vitro genotoxicity tests (bacterial reverse mutation assay, in vitro mouse lymphoma TK gene mutation assay, and in vitro micronucleus assay) to assess the genotoxic potential of short-, medium-, and longchain triacylglycerides 1 . This synthetic mixture of triacyglycerides showed no evidence of mutagenic, clastogenic, or aneugenic activity. Overall, the available data indicated that this novel food did not exhibit genotoxic potential under the tested conditions supporting its safety as a dietary fat ingredient. Mahadevan et al., demonstrated the safety of Hericium erinaceus and Trametes versicolor mushroom powders in acute and subchronic oral toxicity studies, as well as in in vitro and in vivo genotoxicity assays 2 .Long-term safety of the consumption of novel foods was further addressed by Punvittayagul et al., who evaluated formulated Thai rice instant granules containing turmeric extract and Phyllanthus emblica fruit pulp in a 6-month repeated-dose oral toxicity study and revealed no adverse ePects 3 . Given the presence of plant-based bioactive compounds, the expression profile of hepatic antioxidant genes was examined and found to be upregulated. Especially their work on molecular docking to identify binding aPinity interactions between major bioactive compounds and key antioxidant enzymes provides an example of the application of mechanistic toxicology to gain insights into the antioxidant potential of these bioactive constituents present in the granules.Mechanistic insights into the antioxidant potential of bioactive compounds in novel foods were further provided by Giambastiani et al., who investigated the ePects of dietary supplementation with the microalga Chlorella vulgaris in an animal study 4 . The findings showed elevated activity of hepatic xenobiotic-metabolizing cytochrome P450 (CYP) enzymes together with antioxidant and detoxification enzymes without signs of liver and kidney toxicity. The antioxidant potential of C. vulgaris was supported by compositional data indicating its richness in phenolic compounds and carotenoids. Additionally, their work illustrated anti-inflammatory and antioxidant ePects of C. vulgaris in a murine model of chronic pulmonary inflammation. These findings further support the need for comprehensive toxicological evaluations on the long-term ePects of novel foods containing bioactive compounds with pharmacological activities.Another important theme emerging from this Research Topic concerns the complexity of the safety assessment in cases of products of cellular agriculture and the increasing importance of the application of New Approach Methodologies (NAMs). Felicianna et al., investigated the chemical characterization and toxicity of plant cell cultures from scurvy grass (Cochlearia danica) and rowan (Sorbus aucuparia) and demonstrated that they are nutritionally comparable to other berry cell lines without toxic ePects 5 . By applying proteomics analysis to identify potential allergens, the study showcases how NAMs are incorporated in the allergenicity safety assessment of novel foods. Their findings also emphasized the need for further work to evaluate the outcomes of proteomics, and the ePects from phytohormone accumulation used in the growth media on the quality and safety of these plant cell culture foods.The allergenicity assessment of novel foods was also addressed by Calcinai et al., who performed protein profiling of chia seeds (Salvia hispanica) followed by in-silico homology analysis between identified chia peptides and sesame protein sequences 6 . The potential cross-reactivity with characterised linear epitopes from sesame allergens was further corroborated in vitro by IgE-binding assays using sera from sesame-allergic individuals. This study highlights the challenges faced in the assessment of the allergenic potential of novel proteins including the lack of comprehensive protein sequence data and the insuPicient characterization of potential allergenic epitopes.Complementing these studies, Laganaro et al. reviewed the data requirements for allergenicity safety assessment of novel foods within the EU framework, identifying key uncertainties and research needs 7 . The assessment should first consider the nature of the novel food, whether proteins are involved in its production, and whether its source is known to be allergenic. Literature findings, together with protein digestibility and stability data, also inform the evaluation of its allergenic potential. Where uncertainty remains, a tiered approach is applied to investigate potential cross-reactivity with known allergens, encompassing in silico, in vitro and, where necessary, in vivo approaches. The review underscores the value of integrating bioinformatic predictions with experimental validation to strengthen the evidence base for allergenicity assessment, while also highlighting the need for consensus on the interpretation of results, standardised and validated methods, and development of de novo sensitization assays.Addressing limitations and data gaps in the safety assessment of novel foods is crucial for food innovation without compromising public health. The next generation of safety assessment is expected to increasingly integrate NAMs and AI, while addressing the need for method standardisation and validation to support fit-for-purpose regulatory decisionmaking. Overall, the contributions assembled in this Research Topic reflect the breadth of approaches for toxicological and allergenicity assessment and illustrate the ongoing evolution towards more mechanistic, predictive and biologically relevant methodologies.Author contributions MG: Writing -original draft, Writing -review and editing, LP: Writing -review and editing
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