Dealing with software complexity in individual‐based models

Vedder, Daniel; Ankenbrand, Markus J.; Cabral, Juliano Sarmento

doi:10.1111/2041-210x.13716

Cited by 12 publications

(16 citation statements)

References 70 publications

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“…GeMM is implemented in Julia with the Distributions.jl package (Bezanson et al, 2017 ; Lin et al, 2021 ), while data preparation and analysis for this study was carried out in R 4.0.4 with the tidyverse packages (R Core Team, 2021 ; Wickham et al, 2019 ). Software development and verification followed best practice as described in Vedder, Ankenbrand, and Cabral ( 2021 ). The full model description following the ODD protocol (Grimm et al, 2010 ) can be found in the Supplementary Materials .…”

Section: Methodsmentioning

confidence: 99%

Hybridization may aid evolutionary rescue of an endangered East African passerine

Vedder

Lens

Martin

et al. 2022

Evolutionary Applications

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Introgressive hybridization is a process that enables gene flow across species barriers through the backcrossing of hybrids into a parent population. This may make genetic material, potentially including relevant environmental adaptations, rapidly available in a gene pool. Consequently, it has been postulated to be an important mechanism for enabling evolutionary rescue, that is the recovery of threatened populations through rapid evolutionary adaptation to novel environments. However, predicting the likeli-

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Section: Methodsmentioning

confidence: 99%

Hybridization may aid evolutionary rescue of an endangered East African passerine

Vedder

Lens

Martin

et al. 2022

Evolutionary Applications

Self Cite

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“…Developing software is a highly complex activity and the means that are used to build the final product are extremely volatile. Poorly formulated and dynamic user requirements, the high number of people involved in the process, and the interaction of the program being developed with others in the same system contribute to this complexity [19,20]. San Cristóbal et al [21] add that complex problems are usually difficult to predict or are even unpredictable.…”

Section: From Small-scale To Large-scale Agilementioning

confidence: 99%

Adoption of Large-Scale Scrum Practices through the Use of Management 3.0

Almeida

Espinheira

2022

Informatics

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Software engineering companies have progressively incorporated agile project management methodologies. Initially, this migration occurred mostly in the context of startups, but in recent years it has also sparked interest from other companies with larger and more geographically dispersed teams. One of the frameworks used for large-scale agile implementation is the LeSS framework. This study seeks to explore how Management 3.0 principles can be applied in the context of the ten practices proposed in the LeSS framework. To this end, a qualitative research methodology based on four case studies is used to identify and explore the role of Management 3.0 in software management and development processes that adopt this agile paradigm. The findings show that the principles of Management 3.0 are relevant to the implementation of the LeSS framework practices, especially in fostering team values and personal values; however, distinct principles between the two paradigms are also identified, namely the greater rigidity of processes advocated in the LeSS framework and a greater focus on process automation.

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“…Our kit adds to the efforts of Wilson and colleagues in promoting the “best” [ 9 ] or at least “good enough” [ 10 ] practices in scientific computing. Below, we briefly comment other practices that should be implemented alongside this kit.…”

Section: Introductionmentioning

confidence: 99%

“…We focus on the use of code for modeling, data processing, and presentation. For ecological software, there is a variety of guidelines for publication (e.g., [8][9][10][11]). Moreover, the very work of software development forces authors to apply good practices established in Computer Science to facilitate understanding, such as code documentation and functional programming (i.e., writing your own functions, [9]).…”

Section: Introductionmentioning

confidence: 99%

“…For ecological software, there is a variety of guidelines for publication (e.g., [8][9][10][11]). Moreover, the very work of software development forces authors to apply good practices established in Computer Science to facilitate understanding, such as code documentation and functional programming (i.e., writing your own functions, [9]). However, the use of computationally complicated analytical and modeling methods is increasingly common for students and researchers with little to no experience or knowledge on the good practices of computational work.…”

Section: Introductionmentioning

confidence: 99%

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A simple kit to use computational notebooks for more openness, reproducibility, and productivity in research

2022

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The ubiquitous use of computational work for data generation, processing, and modeling increased the importance of digital documentation in improving research quality and impact. Computational notebooks are files that contain descriptive text, as well as code and its outputs, in a single, dynamic, and visually appealing file that is easier to understand by nonspecialists. Traditionally used by data scientists when producing reports and informing decision-making, the use of this tool in research publication is not common, despite its potential to increase research impact and quality. For a single study, the content of such documentation partially overlaps with that of classical lab notebooks and that of the scientific manuscript reporting the study. Therefore, to minimize the amount of work required to manage all the files related to these contents and optimize their production, we present a starter kit to facilitate the implementation of computational notebooks in the research process, including publication. The kit contains the template of a computational notebook integrated into a research project that employs R, Python, or Julia. Using examples of ecological studies, we show how computational notebooks also foster the implementation of principles of Open Science, such as reproducibility and traceability. The kit is designed for beginners, but at the end we present practices that can be gradually implemented to develop a fully digital research workflow. Our hope is that such minimalist yet effective starter kit will encourage researchers to adopt this practice in their workflow, regardless of their computational background.

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Dealing with software complexity in individual‐based models

Cited by 12 publications

References 70 publications

Hybridization may aid evolutionary rescue of an endangered East African passerine

Hybridization may aid evolutionary rescue of an endangered East African passerine

Adoption of Large-Scale Scrum Practices through the Use of Management 3.0

A simple kit to use computational notebooks for more openness, reproducibility, and productivity in research

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