Functional dependencies and feature interactions in automotive software systems are a major source of erroneous and deficient behavior. To overcome these problems, many approaches exist that focus on modeling these functional dependencies in early stages of system design. However, there are only few empirical studies that report on the extent of such dependencies in industrial software systems and how they are considered in an industrial development context. In this paper, we analyze the functional architecture of a real automotive software system with the aim to assess the extent, awareness and importance of interactions between features of a future vehicle. Our results show that within the functional architecture at least 85% of the analyzed vehicle features depend on each other. They furthermore show that the developers are not aware of a large number of these dependencies when they are modeled solely on an architectural level. Therefore, the developers mention the need for a more precise specification of feature interactions, e.g., for the execution of comprehensive impact analyses. These results challenge the current development methods and emphasize the need for an extensive modeling of features and their dependencies in requirements engineering.
{"title":"Why feature dependencies challenge the requirements engineering of automotive systems: An empirical study","authors":"Andreas Vogelsang, Steffen Fuhrmann","doi":"10.1109/RE.2013.6636728","DOIUrl":"https://doi.org/10.1109/RE.2013.6636728","url":null,"abstract":"Functional dependencies and feature interactions in automotive software systems are a major source of erroneous and deficient behavior. To overcome these problems, many approaches exist that focus on modeling these functional dependencies in early stages of system design. However, there are only few empirical studies that report on the extent of such dependencies in industrial software systems and how they are considered in an industrial development context. In this paper, we analyze the functional architecture of a real automotive software system with the aim to assess the extent, awareness and importance of interactions between features of a future vehicle. Our results show that within the functional architecture at least 85% of the analyzed vehicle features depend on each other. They furthermore show that the developers are not aware of a large number of these dependencies when they are modeled solely on an architectural level. Therefore, the developers mention the need for a more precise specification of feature interactions, e.g., for the execution of comprehensive impact analyses. These results challenge the current development methods and emphasize the need for an extensive modeling of features and their dependencies in requirements engineering.","PeriodicalId":6342,"journal":{"name":"2013 21st IEEE International Requirements Engineering Conference (RE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2013-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86804584","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
L. Pasquale, Y. Yu, M. Salehie, Luca Cavallaro, T. Tun, B. Nuseibeh
We propose the use of forensic requirements to drive the automation of a digital forensics process. We augment traditional reactive digital forensics processes with proactive evidence collection and analysis activities, and provide immediate investigative suggestions before an investigation starts. These activities adapt depending on suspicious events, which in turn might require the collection and analysis of additional evidence. The reactive activities of a traditional digital forensics process are also adapted depending on the investigation findings.
{"title":"Requirements-driven adaptive digital forensics","authors":"L. Pasquale, Y. Yu, M. Salehie, Luca Cavallaro, T. Tun, B. Nuseibeh","doi":"10.1109/RE.2013.6636745","DOIUrl":"https://doi.org/10.1109/RE.2013.6636745","url":null,"abstract":"We propose the use of forensic requirements to drive the automation of a digital forensics process. We augment traditional reactive digital forensics processes with proactive evidence collection and analysis activities, and provide immediate investigative suggestions before an investigation starts. These activities adapt depending on suspicious events, which in turn might require the collection and analysis of additional evidence. The reactive activities of a traditional digital forensics process are also adapted depending on the investigation findings.","PeriodicalId":6342,"journal":{"name":"2013 21st IEEE International Requirements Engineering Conference (RE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2013-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75319456","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Requirements engineering research is undertaken to propose innovative solutions, to develop concepts, algorithms, processes, and technologies, to validate effective solutions for important requirements-related problems, and ultimately to support the transition of important findings to practice. However prior studies have shown that successful projects often take from 20-25 years to reach the stage of full industry adoption, while many other projects fizzle out and never advance beyond the initial research phase. This panel provides the opportunity for practitioners and academics to engage in a meaningful discussion around the topic of technology transfer. In this third offering of the Ready-Set-Transfer panel, three research groups will present products that they believe to be industry-ready to a panel of industrial practitioners. Each team will receive feedback from the panelists. The long-term goal of the panel is to increase technology transfer in the requirements engineering domain.
{"title":"Ready-Set-Transfer: Technology transfer in the requirements engineering domain","authors":"J. Cleland-Huang, S. Ghaisas","doi":"10.1109/RE.2013.6636747","DOIUrl":"https://doi.org/10.1109/RE.2013.6636747","url":null,"abstract":"Requirements engineering research is undertaken to propose innovative solutions, to develop concepts, algorithms, processes, and technologies, to validate effective solutions for important requirements-related problems, and ultimately to support the transition of important findings to practice. However prior studies have shown that successful projects often take from 20-25 years to reach the stage of full industry adoption, while many other projects fizzle out and never advance beyond the initial research phase. This panel provides the opportunity for practitioners and academics to engage in a meaningful discussion around the topic of technology transfer. In this third offering of the Ready-Set-Transfer panel, three research groups will present products that they believe to be industry-ready to a panel of industrial practitioners. Each team will receive feedback from the panelists. The long-term goal of the panel is to increase technology transfer in the requirements engineering domain.","PeriodicalId":6342,"journal":{"name":"2013 21st IEEE International Requirements Engineering Conference (RE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2013-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85009820","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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