{"title":"探索可解释性:定义、模型和知识目录","authors":"Larissa Chazette, Wasja Brunotte, Timo Speith","doi":"10.1109/RE51729.2021.00025","DOIUrl":null,"url":null,"abstract":"The growing complexity of software systems and the influence of software-supported decisions in our society awoke the need for software that is transparent, accountable, and trust-worthy. Explainability has been identified as a means to achieve these qualities. It is recognized as an emerging non-functional requirement (NFR) that has a significant impact on system quality. However, in order to incorporate this NFR into systems, we need to understand what explainability means from a software engineering perspective and how it impacts other quality aspects in a system. This allows for an early analysis of the benefits and possible design issues that arise from interrelationships between different quality aspects. Nevertheless, explainability is currently under-researched in the domain of requirements engineering and there is a lack of conceptual models and knowledge catalogues that support the requirements engineering process and system design. In this work, we bridge this gap by proposing a definition, a model, and a catalogue for explainability. They illustrate how explainability interacts with other quality aspects and how it may impact various quality dimensions of a system. To this end, we conducted an interdisciplinary Systematic Literature Review and validated our findings with experts in workshops.","PeriodicalId":440285,"journal":{"name":"2021 IEEE 29th International Requirements Engineering Conference (RE)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"38","resultStr":"{\"title\":\"Exploring Explainability: A Definition, a Model, and a Knowledge Catalogue\",\"authors\":\"Larissa Chazette, Wasja Brunotte, Timo Speith\",\"doi\":\"10.1109/RE51729.2021.00025\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The growing complexity of software systems and the influence of software-supported decisions in our society awoke the need for software that is transparent, accountable, and trust-worthy. Explainability has been identified as a means to achieve these qualities. It is recognized as an emerging non-functional requirement (NFR) that has a significant impact on system quality. However, in order to incorporate this NFR into systems, we need to understand what explainability means from a software engineering perspective and how it impacts other quality aspects in a system. This allows for an early analysis of the benefits and possible design issues that arise from interrelationships between different quality aspects. Nevertheless, explainability is currently under-researched in the domain of requirements engineering and there is a lack of conceptual models and knowledge catalogues that support the requirements engineering process and system design. In this work, we bridge this gap by proposing a definition, a model, and a catalogue for explainability. They illustrate how explainability interacts with other quality aspects and how it may impact various quality dimensions of a system. To this end, we conducted an interdisciplinary Systematic Literature Review and validated our findings with experts in workshops.\",\"PeriodicalId\":440285,\"journal\":{\"name\":\"2021 IEEE 29th International Requirements Engineering Conference (RE)\",\"volume\":\"5 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-08-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"38\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE 29th International Requirements Engineering Conference (RE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/RE51729.2021.00025\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE 29th International Requirements Engineering Conference (RE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RE51729.2021.00025","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Exploring Explainability: A Definition, a Model, and a Knowledge Catalogue
The growing complexity of software systems and the influence of software-supported decisions in our society awoke the need for software that is transparent, accountable, and trust-worthy. Explainability has been identified as a means to achieve these qualities. It is recognized as an emerging non-functional requirement (NFR) that has a significant impact on system quality. However, in order to incorporate this NFR into systems, we need to understand what explainability means from a software engineering perspective and how it impacts other quality aspects in a system. This allows for an early analysis of the benefits and possible design issues that arise from interrelationships between different quality aspects. Nevertheless, explainability is currently under-researched in the domain of requirements engineering and there is a lack of conceptual models and knowledge catalogues that support the requirements engineering process and system design. In this work, we bridge this gap by proposing a definition, a model, and a catalogue for explainability. They illustrate how explainability interacts with other quality aspects and how it may impact various quality dimensions of a system. To this end, we conducted an interdisciplinary Systematic Literature Review and validated our findings with experts in workshops.