Software Product Lines: Engineering, Services, and Management
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ItemApplying End User Software Product Line Engineering for Smart Spaces( 2018-01-03)Smart spaces are physical environments equipped with pervasive technology that sense and react to human activities and changes in the environment. End User Development (EUD) skills vary significantly among end users who want to develop software applications for their smart spaces. This paper presents a systematic approach for adopting reuse in EUD for smart spaces by using Software Product Line (SPL) concepts. End User (EU) SPL designers develop EU SPLs for smart spaces whereas end users derive their individual smart space applications from these SPLs. In particular, this paper presents a systematic approach for EU SPL designers to develop EU SPLs and end users to derive software applications for their spaces, an EUD environment that supports EU SPL development and application derivation, and a testing approach for testing EU SPLs and derived applications.
ItemFlexible Ambiguity Resolution and Incompleteness Detection in Requirements Descriptions via an Indicator-Based Configuration of Text Analysis Pipelines( 2018-01-03)Natural language software requirements descriptions enable end users to formulate their wishes and expectations for a future software product without much prior knowledge in requirements engineering. However, these descriptions are susceptible to linguistic inaccuracies such as ambiguities and incompleteness that can harm the development process. There is a number of software solutions that can detect deficits in requirements descriptions and partially solve them, but they are often hard to use and not suitable for end users. For this reason, we develop a software system that helps end-users to create unambiguous and complete requirements descriptions by combining existing expert tools and controlling them using automatic compensation strategies. In order to recognize the necessity of individual compensation methods in the descriptions, we have developed linguistic indicators, which we present in this paper. Based on these indicators, the whole text analysis pipeline is ad-hoc configured and thus adapted to the individual circumstances of a requirements description.