Titlebook: Managed Software Evolution; Ralf Reussner,Michael Goedicke,Lukas Märtin Book‘‘‘‘‘‘‘‘ 2019 The Editor(s) (if applicable) and the Author(s)

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书目名称Managed Software Evolution影响因子(影响力)




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书目名称Managed Software Evolution网络公开度学科排名




书目名称Managed Software Evolution被引频次




书目名称Managed Software Evolution被引频次学科排名




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书目名称Managed Software Evolution读者反馈学科排名

火花

Addressed Challengesftware and processes tailored for software and systems evolution. Firstly, the discovery and externalization of knowledge about requirements, the recording and representation of design decisions, and the learning from past experiences in evolution form the human perspective, including developers, op

征税

Introduction to Case Studiesnt research that supports sharing of knowledge and resources. In order to support joint research, collaboration and replication in empirical studies based on common evolution scenarios and artefacts are required. These studies are rarely reusable as important artefacts (e.g. requirements, design dec

使乳化

Tacit Knowledge in Software Evolution, within long-living and continuously evolving systems. During the design time of a software system, heuristics and machine learning classifiers can be used to identify and externalise tacit knowledge. For instance, externalised tacit security knowledge supports requirement engineers to understand s

oracle

翅膀拍动

Model-Based Round-Trip Engineering and Testing of Evolving Software Product Lineshe product-line architecture consists of a feature diagram as configuration model and a preprocessor-based C code implementation comprising all software variants. As quality-assurance methodology, we consider white-box testing, where test suites are automatically generated for product-line implement

incontinence

Performance Analysis Strategies for Software Variants and Versionsoftware variation, that is a large space of software variants and versions, that challenges state-of-the-art analysis techniques for software. We give an overview on strategies to cope with software variation, which mostly focuses either on configuration (variants) or evolution (versions). Interesti

GAVEL

inflame

Learning from Evolution for Evolutions chapter presents several approaches to automate the acquisition of knowledge about the system’s past, for example past evolution steps, and its present, for example models of its behaviour. Based on these results, further approaches support the validation and verification of evolution steps, as we

Ferritin

Formal Verification of Evolutionary Changesevolution. First, we discuss the opportunities that formal methods offer, particularly when dealing with the evolution of automated production systems, but also which special needs this particular domain requires from the formal methods to be applied. We exemplarily present three approaches that suc