Design Patterns for Digital Platforms

Zaramenskikh, Evgeny; Oleynik, Alexander

doi:10.1007/978-3-030-71397-3_9

Cited by 2 publications

(1 citation statement)

References 14 publications

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“…The pattern landscape has been enriched by the addition of several patterns, pattern catalogues, pattern repositories, and pattern books. These include object oriented patterns [6], patterns for a specific domain such as patterns for enterprise application architecture [7], patterns for security [8,9], J2EE web services patterns [10], patterns for context awareness [11,12], patterns for embedded systems [13], IoT design patterns [14], Service Oriented Architecture patterns [15], Mobile design patterns [16], Cloud design patterns [17], Machine learning design patterns [18], patterns for digital platforms [19], AI systems [20] and many more. Analytical studies on the impact of applying design patterns on the software design, architecture and quality conclude that the software quality is greatly enhanced by applying the right patterns [21,22].…”

Section: Background and Related Workmentioning

confidence: 99%

Knowledge Discovery for Design Pattern Selection

Ponde¹,

Bharambe²,

Khobragade³

et al. 2023

Advances in Computer Science Research

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Design patterns are useful Software Engineering tools that enable the reuse of expert solutions to recurring problems. There are a large number of patterns, spread in multiple catalogs and in heterogeneous formats. Selecting and applying the right design pattern requires an in-depth understanding of patterns and their classification. The solution architects must either rely on the advice of experts or laboriously go through the available literature to find the relevant patterns. Pattern applicability will improve if the entire pattern knowledge is available in one place and in a standard format. If the pattern data is augmented with additional knowledge to guide the architect on choosing the right patterns for a particular requirement, it will be immensely useful and productive. The objective of the knowledge discovery process on the design pattern landscape is to extract useful relations and groups of patterns to enable users to select and apply patterns effectively. The present work discusses a model for analyzing existing pattern data, extracting knowledge thereof, and representing this knowledge in a format to enable pattern search and its application.

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