Agile Software Development: Principles, Patterns, and Practices

By R. Winter. 2014

1,293 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Information Systems

View Paper: https://www.semanticscholar.org/paper/282bbb03538f51ca858f824d897168cf9f6e90ab

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In Computer Networks and Communications

In Information Systems

Citations in the corpus

Self-Organizing Roles on Agile Software Development Teams (2013, methodology): “Self-organizing teams are at the heart of Agile software development [2], [3], [1], [4], [5], [6].”
Predicting the Price of Bitcoin Using Machine Learning (2018, result): “As a result, analogously it also reflects an Agile methodology (41).”
Best Practices for Scientific Computing (2012, background): “While these practices have been around for decades, they gained prominence starting in the late 1990s under the banner of agile development [40, 36].”
CLoDSA: a tool for augmentation in classification, localization, detection, semantic segmentation and instance segmentation tasks (2019, methodology): “To this aim, several design patterns, like the Factory pattern [24], and software engineering principles, such as dependency inversion or open/closed [25], have been applied.”
Realizing the Potential of Behavioral Intervention Technologies (2013, methodology): “…low-fidelity prototyping (Rudd, Stern, & Isensee, 1996), A/B testing (Hekler et al., 2013), iterative design (Pagliari, 2007), and agile development (Martin, 2003) to more rapidly create and refine BITs before evaluation with traditional psychological methods (e.g., randomized controlled trials).”
On micro-services architecture (2014, background): “We should mention in this case the Single Responsible Principle (SRP) pattern [9].”
Software fault prediction metrics: A systematic literature review (2013, methodology): “In [82], MOOD metrics were evaluated and compared with the Martin suite [43] and CK metrics.”
HistoRAG: Embedding Historical Methodology in Retrieval-Augmented Generation Through Critical Technical Practice (2026, unknown): “…of the dependency inversion principle, in which the core and each application both depend on the Corpus abstraction rather than on one another (Martin, 2003), and it reflects the FAIR principles for research software, under which software should be reusable, able to be understood, built upon,…”