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Classification and Comparison of Architecture Evolution Reuse Knowledge - A Systematic Review

机译:建筑演化重用知识的分类与比较-系统评价

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摘要

Context: Architecture-centric software evolution (ACSE) enables changes in system's structure and behaviour while maintaining a global view of the software to address evolution-centric trade-offs. The existing research and practices for ACSE primarily focus on design-time evolution and runtime adaptations to accommodate changing requirements in existing architectures.Objectives: We aim to identify, taxonomically classify and systematically compare the existing research focused on enabling or enhancing change reuse to support ACSE.Method: We conducted a systematic literature review of 32 qualitatively selected studies and taxonomically classified these studies based on solutions that enable (i) empirical acquisition and (ii) systematic application of architecture evolution reuse knowledge (AERK) to guide ACSE.Results: We identified six distinct research themes that support acquisition and application of AERK. We investigated (i) how evolution reuse knowledge is defined, classified and represented in the existing research to support ACSE and (ii) what are the existing methods, techniques and solutions to support empirical acquisition and systematic application of AERK.Conclusions: Change patterns (34% of selected studies) represent a predominant solution, followed by evolution styles (25%) and adaptation strategies and policies (22%) to enable application of reuse knowledge. Empirical methods for acquisition of reuse knowledge represent 19% including pattern discovery, configuration analysis, evolution and maintenance prediction techniques (approximately 6% each). A lack of focus on empirical acquisition of reuse knowledge suggests the need of solutions with architecture change mining as a complementary and integrated phase for architecture change execution
机译:背景信息:以体系结构为中心的软件演化(ACSE)可以更改系统的结构和行为,同时保持软件的全局视图以解决以演化为中心的折衷方案。 ACSE的现有研究和实践主要侧重于设计时演进和运行时适应,以适应现有体系结构中不断变化的需求。目的:我们旨在识别,分类分类和系统地比较现有研究,以支持或增强变更重用来支持ACSE。方法:我们对32项定性选择的研究进行了系统的文献综述,并基于能够(i)经验获取和(ii)系统应用架构演化重用知识(AERK)来指导ACSE的解决方案对这些研究进行分类分类。结果:确定了支持AERK的获取和应用的六个不同的研究主题。我们研究了(i)如何在现有研究中定义,分类和表示进化重用知识以支持ACSE,以及(ii)现有哪些方法,技术和解决方案来支持经验获取和系统应用AERK。选定研究的34%)代表了主要解决方案,其次是进化风格(25%)以及适应策略和政策(22%)以使重用知识的应用成为可能。获取重用知识的经验方法占19%,包括模式发现,配置分析,演进和维护预测技术(每种约占6%)。对重用知识的经验获取缺乏关注表明,需要将架构变更挖掘作为架构变更执行的补充和集成阶段的解决方案

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