Karsten Saller, Sebastian Oster, Andy Schürr, Julia Schroeter, Malte Lochau
Mobile devices like smartphones are getting increasingly important in our daily lifes. They are used in various environments and have to dynamically adapt themselves accordingly in order to provide an optimal runtime behavior. Naturally, adapting to continuously changing environmental conditions is a challenging task because mobile devices are always limited in their resources and have to adapt in real-time. In this paper, we introduce an approach that enables resource limited devices to adapt to changing conditions using dynamic software product lines techniques. Therefore, feature models are reduced to a specific hardware context before installing the adaptive mobile application on the device. This reduces the amount of possible configurations that are compatible with the device and, thereby, minimizes the costs and the duration of an adaptation during runtime.
{"title":"Reducing feature models to improve runtime adaptivity on resource limited devices","authors":"Karsten Saller, Sebastian Oster, Andy Schürr, Julia Schroeter, Malte Lochau","doi":"10.1145/2364412.2364435","DOIUrl":"https://doi.org/10.1145/2364412.2364435","url":null,"abstract":"Mobile devices like smartphones are getting increasingly important in our daily lifes. They are used in various environments and have to dynamically adapt themselves accordingly in order to provide an optimal runtime behavior. Naturally, adapting to continuously changing environmental conditions is a challenging task because mobile devices are always limited in their resources and have to adapt in real-time. In this paper, we introduce an approach that enables resource limited devices to adapt to changing conditions using dynamic software product lines techniques. Therefore, feature models are reduced to a specific hardware context before installing the adaptive mobile application on the device. This reduces the amount of possible configurations that are compatible with the device and, thereby, minimizes the costs and the duration of an adaptation during runtime.","PeriodicalId":339444,"journal":{"name":"Software Product Lines Conference","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121929411","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}
In this paper, we share practical experiences from an ongoing effort towards adopting a feature-centric method that enhances reuse of requirements at TRW Automotive's slip control system department (based in Koblenz, Germany). After introducing identified challenges in detail, key solution factors and a technical reuse concept for managing and deriving product-specific requirements are presented. Then, we demonstrate one way of implementing this solution approach based on industry-standard tools. In addition, identified pitfalls and lessons learned are discussed.
{"title":"Adopting feature-centric reuse of requirements assets: an industrial experience report","authors":"Mahdi Derakhshanmanesh, Joachim Fox, J. Ebert","doi":"10.1145/2364412.2364414","DOIUrl":"https://doi.org/10.1145/2364412.2364414","url":null,"abstract":"In this paper, we share practical experiences from an ongoing effort towards adopting a feature-centric method that enhances reuse of requirements at TRW Automotive's slip control system department (based in Koblenz, Germany). After introducing identified challenges in detail, key solution factors and a technical reuse concept for managing and deriving product-specific requirements are presented. Then, we demonstrate one way of implementing this solution approach based on industry-standard tools. In addition, identified pitfalls and lessons learned are discussed.","PeriodicalId":339444,"journal":{"name":"Software Product Lines Conference","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115538101","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}
This paper describes a demonstration of the product line engineering tool and framework Gears from BigLever software. Gears provides a single feature modeling language, a single variation point mechanism, and a single automated product configurator that are used to configure a product portfolio's shared engineering assets appropriately for each product in the portfolio. The result is an automated production line capability that can quickly produce any product in the portfolio from the same, single set of shared assets.
{"title":"Systems and software product line engineering with BigLever software gears","authors":"C. Krueger, P. Clements","doi":"10.1145/2364412.2364458","DOIUrl":"https://doi.org/10.1145/2364412.2364458","url":null,"abstract":"This paper describes a demonstration of the product line engineering tool and framework Gears from BigLever software. Gears provides a single feature modeling language, a single variation point mechanism, and a single automated product configurator that are used to configure a product portfolio's shared engineering assets appropriately for each product in the portfolio. The result is an automated production line capability that can quickly produce any product in the portfolio from the same, single set of shared assets.","PeriodicalId":339444,"journal":{"name":"Software Product Lines Conference","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115606924","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}
We demonstrate an experimental tool for the modeling and analysis of behavioral variability in product families.
我们展示了一个实验工具，用于建模和分析产品族中的行为变异性。
{"title":"Demonstration of a model checker for the analysis of product variability","authors":"M. T. Beek, S. Gnesi, F. Mazzanti","doi":"10.1145/2364412.2364454","DOIUrl":"https://doi.org/10.1145/2364412.2364454","url":null,"abstract":"We demonstrate an experimental tool for the modeling and analysis of behavioral variability in product families.","PeriodicalId":339444,"journal":{"name":"Software Product Lines Conference","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122423051","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}
Variability modeling is one of the key disciplines in software product line engineering and has been addressed by academic and industrial research over the past twenty years. While the research community's focus was on creating notations and tools, most of which based on feature modeling, there are relatively few empirical studies that aim at understanding the actual use of these techniques. In this light, we present empirical work that investigates variability modeling in the context of software product lines. We study concepts and semantics of real-world variability languages and the usage of these concepts in real, large-scale variability models. We further extend our discussion to variability in software ecosystems, which target inter-organizational reuse and are often seen as natural successors of software product lines. We provide empirical evidence that the well-researched concepts of feature modeling are used in practice, but also that more advanced concepts are needed. We observe that some assumptions about realistic variability models in the literature do not hold. Further, our findings indicate that variability models are not suited for software ecosystems, and that particular kinds of dependencies are needed to enable growth of such ecosystems.
{"title":"Variability modeling in the wild","authors":"T. Berger","doi":"10.1145/2364412.2364452","DOIUrl":"https://doi.org/10.1145/2364412.2364452","url":null,"abstract":"Variability modeling is one of the key disciplines in software product line engineering and has been addressed by academic and industrial research over the past twenty years. While the research community's focus was on creating notations and tools, most of which based on feature modeling, there are relatively few empirical studies that aim at understanding the actual use of these techniques.\u0000 In this light, we present empirical work that investigates variability modeling in the context of software product lines. We study concepts and semantics of real-world variability languages and the usage of these concepts in real, large-scale variability models. We further extend our discussion to variability in software ecosystems, which target inter-organizational reuse and are often seen as natural successors of software product lines. We provide empirical evidence that the well-researched concepts of feature modeling are used in practice, but also that more advanced concepts are needed. We observe that some assumptions about realistic variability models in the literature do not hold. Further, our findings indicate that variability models are not suited for software ecosystems, and that particular kinds of dependencies are needed to enable growth of such ecosystems.","PeriodicalId":339444,"journal":{"name":"Software Product Lines Conference","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123336850","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}
Wolfgang Heider, Rick Rabiser, P. Grünbacher, Daniela Rabiser
Industrial product lines are typically maintained for a long time and evolve continuously to address changing requirements and new technologies. Already derived products often have to be re-derived after such changes to benefit from new and updated features. Product line engineers thus frequently need to analyze the impact of changes to variability models to prevent unexpected changes of re-derived products. In this paper we present a tool-supported approach that informs engineers about the impacts of variability model changes on existing products. Regression tests are used to determine whether existing product configurations and generated product outputs can be re-derived without unexpected effects. We evaluate the feasibility of the approach based on changes observed in a real-world software product line. More specifically, we show how our approach helps engineers performing specific evolution tasks to analyze the change impacts on existing products. We also evaluate the performance and scalability of our approach. Our results show that variability change impact analyses can be automated using model regression testing and can help reducing the gap between domain engineering and application engineering.
{"title":"Using regression testing to analyze the impact of changes to variability models on products","authors":"Wolfgang Heider, Rick Rabiser, P. Grünbacher, Daniela Rabiser","doi":"10.1145/2362536.2362563","DOIUrl":"https://doi.org/10.1145/2362536.2362563","url":null,"abstract":"Industrial product lines are typically maintained for a long time and evolve continuously to address changing requirements and new technologies. Already derived products often have to be re-derived after such changes to benefit from new and updated features. Product line engineers thus frequently need to analyze the impact of changes to variability models to prevent unexpected changes of re-derived products. In this paper we present a tool-supported approach that informs engineers about the impacts of variability model changes on existing products. Regression tests are used to determine whether existing product configurations and generated product outputs can be re-derived without unexpected effects. We evaluate the feasibility of the approach based on changes observed in a real-world software product line. More specifically, we show how our approach helps engineers performing specific evolution tasks to analyze the change impacts on existing products. We also evaluate the performance and scalability of our approach. Our results show that variability change impact analyses can be automated using model regression testing and can help reducing the gap between domain engineering and application engineering.","PeriodicalId":339444,"journal":{"name":"Software Product Lines Conference","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129010265","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}
The traditional focus of Product Line Engineering (PIE) is on the customization of whole software solutions. So far, the combination of cloud computing with PLE techniques has hardly been discussed. In this paper, we discuss different approaches to cloud computing and their relation to product line technologies. We also describe both, specific opportunities and drawbacks, of these approaches. We also provide a discussion of different combinations of these approaches as a way to combine their strengths.
{"title":"Cloud-based software product lines","authors":"Klaus Schmid, A. Rummler","doi":"10.1145/2364412.2364440","DOIUrl":"https://doi.org/10.1145/2364412.2364440","url":null,"abstract":"The traditional focus of Product Line Engineering (PIE) is on the customization of whole software solutions. So far, the combination of cloud computing with PLE techniques has hardly been discussed. In this paper, we discuss different approaches to cloud computing and their relation to product line technologies. We also describe both, specific opportunities and drawbacks, of these approaches.\u0000 We also provide a discussion of different combinations of these approaches as a way to combine their strengths.","PeriodicalId":339444,"journal":{"name":"Software Product Lines Conference","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129935100","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}
Joseph Gillain, Stéphane Faulkner, P. Heymans, Ivan Jureta, M. Snoeck
In this paper we propose a mathematical program able to optimize the product portfolio scope of a software product line and sketch both a development and a release planning. Our model is based on the description of customer needs in terms of goals. We show that this model can be instantiated in several contexts such as a market customization strategy or a mass-customization strategy. It can deal with Software Product Line development from scratch as well as starting from a legacy software base. We demonstrate its applicability with an example based on a case study.
{"title":"Product portfolio scope optimization based on features and goals","authors":"Joseph Gillain, Stéphane Faulkner, P. Heymans, Ivan Jureta, M. Snoeck","doi":"10.1145/2362536.2362559","DOIUrl":"https://doi.org/10.1145/2362536.2362559","url":null,"abstract":"In this paper we propose a mathematical program able to optimize the product portfolio scope of a software product line and sketch both a development and a release planning. Our model is based on the description of customer needs in terms of goals. We show that this model can be instantiated in several contexts such as a market customization strategy or a mass-customization strategy. It can deal with Software Product Line development from scratch as well as starting from a legacy software base. We demonstrate its applicability with an example based on a case study.","PeriodicalId":339444,"journal":{"name":"Software Product Lines Conference","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116379032","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}
P. Hofman, Tobias Stenzel, Thomas Pohley, Michael Kircher, A. Bermann
This paper summarizes our experience with introducing feature modeling into a product line for imaging and therapy systems in the Siemens Healthcare Sector. Determining and negotiating the scope in a product line that spans several business units with their own economic goals is challenging. Feature modeling offers a good way to do variability/commonality analysis for complex product lines. A precondition for feature modeling is the identification of all features supporting the product line. To identify these features, we developed a method for systematically deriving a feature model top down based on domain know-how. We call this method domain specific feature modeling. As the primary artifact to describe the problem space, a domain specific feature model additionally improves the requirement understanding for all stakeholders by considerably improving the scoping, traceability, testing, efficiency and transparency of planning activities and making the development efforts easier to estimate. In this paper, we share our experience with domain specific feature modeling in a large platform project and describe the lessons learned. We describe our general approach that can also be used for other domains.
{"title":"Domain specific feature modeling for software product lines","authors":"P. Hofman, Tobias Stenzel, Thomas Pohley, Michael Kircher, A. Bermann","doi":"10.1145/2362536.2362568","DOIUrl":"https://doi.org/10.1145/2362536.2362568","url":null,"abstract":"This paper summarizes our experience with introducing feature modeling into a product line for imaging and therapy systems in the Siemens Healthcare Sector. Determining and negotiating the scope in a product line that spans several business units with their own economic goals is challenging. Feature modeling offers a good way to do variability/commonality analysis for complex product lines. A precondition for feature modeling is the identification of all features supporting the product line. To identify these features, we developed a method for systematically deriving a feature model top down based on domain know-how. We call this method domain specific feature modeling. As the primary artifact to describe the problem space, a domain specific feature model additionally improves the requirement understanding for all stakeholders by considerably improving the scoping, traceability, testing, efficiency and transparency of planning activities and making the development efforts easier to estimate. In this paper, we share our experience with domain specific feature modeling in a large platform project and describe the lessons learned. We describe our general approach that can also be used for other domains.","PeriodicalId":339444,"journal":{"name":"Software Product Lines Conference","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132204188","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}
Traditional requirements engineering involves analyzing tradeoffs between available alternatives. In the context of Software Product Lines (SPLs) application engineers have to instantiate variability by evaluating a set of options available from the platform. In this position paper, we propose the adoption of multi-criteria decision-making for instantiating a variability model in application requirements engineering amenable to the adoption of a Product Lines approach.
{"title":"On adopting multi-criteria decision-making approaches for variability management in software product lines","authors":"A. K. Thurimella, S. Ramaswamy","doi":"10.1145/2364412.2364418","DOIUrl":"https://doi.org/10.1145/2364412.2364418","url":null,"abstract":"Traditional requirements engineering involves analyzing tradeoffs between available alternatives. In the context of Software Product Lines (SPLs) application engineers have to instantiate variability by evaluating a set of options available from the platform. In this position paper, we propose the adoption of multi-criteria decision-making for instantiating a variability model in application requirements engineering amenable to the adoption of a Product Lines approach.","PeriodicalId":339444,"journal":{"name":"Software Product Lines Conference","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133799625","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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