Alessio Ferrari, G. Spagnolo, S. Gnesi, F. Dell’Orletta
A business subject who wishes to enter an established technological market is required to accurately analyse the features of the products of the different competitors. Such features are normally accessible through natural language (NL) brochures, or NL Web pages, which describe the products to potential customers. Building a feature model that hierarchically summarises the different features available in competing products can bring relevant benefits in market analysis. A company can easily visualise existing features, and reason about aspects that are not covered by the available solutions. However, designing a feature model starting from publicly available documents of existing products is a time consuming and error-prone task. In this paper, we present two tools, namely Commonality Mining Tool (CMT) and Feature Diagram Editor (FDE), which can jointly support the feature model definition process. CMT allows mining common and variant features from NL descriptions of existing products, by leveraging a natural language processing (NLP) approach based on contrastive analysis, which allows identifying domain-relevant terms from NL documents. FDE takes the commonalities and variabilities extracted by CMT, and renders them in a visual form. Moreover, FDE allows the graphical design and refinement of the final feature model, by means of an intuitive GUI.
{"title":"CMT and FDE: tools to bridge the gap between natural language documents and feature diagrams","authors":"Alessio Ferrari, G. Spagnolo, S. Gnesi, F. Dell’Orletta","doi":"10.1145/2791060.2791117","DOIUrl":"https://doi.org/10.1145/2791060.2791117","url":null,"abstract":"A business subject who wishes to enter an established technological market is required to accurately analyse the features of the products of the different competitors. Such features are normally accessible through natural language (NL) brochures, or NL Web pages, which describe the products to potential customers. Building a feature model that hierarchically summarises the different features available in competing products can bring relevant benefits in market analysis. A company can easily visualise existing features, and reason about aspects that are not covered by the available solutions. However, designing a feature model starting from publicly available documents of existing products is a time consuming and error-prone task. In this paper, we present two tools, namely Commonality Mining Tool (CMT) and Feature Diagram Editor (FDE), which can jointly support the feature model definition process. CMT allows mining common and variant features from NL descriptions of existing products, by leveraging a natural language processing (NLP) approach based on contrastive analysis, which allows identifying domain-relevant terms from NL documents. FDE takes the commonalities and variabilities extracted by CMT, and renders them in a visual form. Moreover, FDE allows the graphical design and refinement of the final feature model, by means of an intuitive GUI.","PeriodicalId":339158,"journal":{"name":"Proceedings of the 19th International Conference on Software Product Line","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126838524","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}
Jaime Font, Lorena Arcega, Øystein Haugen, Carlos Cetina
Software Product Lines (SPLs) can be established from a set of similar models. Establishing the Product Line by mechanically finding model differences may not be the best approach. The identified model fragments may not be seen as recognizable units by the application engineers. We propose to identify model patterns by human-in-the-loop and conceptualize them as reusable model fragments. The approach provides the means to identify and extract those model patterns and further apply them to existing product models. Model fragments obtained by applying our approach seem to perform better than mechanically found ones. It turns out that the repetition of a fragment does not guarantee its relevance as reusable asset for the SPL engineers and vice versa, a fragment that has not been repeated yet, may be relevant as a reusable asset. We have validated these ideas with our industrial partner BSH, an induction hobs manufacturer that generates the firmware of their products from a model-driven SPL.
{"title":"Building software product lines from conceptualized model patterns","authors":"Jaime Font, Lorena Arcega, Øystein Haugen, Carlos Cetina","doi":"10.1145/2791060.2791085","DOIUrl":"https://doi.org/10.1145/2791060.2791085","url":null,"abstract":"Software Product Lines (SPLs) can be established from a set of similar models. Establishing the Product Line by mechanically finding model differences may not be the best approach. The identified model fragments may not be seen as recognizable units by the application engineers. We propose to identify model patterns by human-in-the-loop and conceptualize them as reusable model fragments. The approach provides the means to identify and extract those model patterns and further apply them to existing product models. Model fragments obtained by applying our approach seem to perform better than mechanically found ones. It turns out that the repetition of a fragment does not guarantee its relevance as reusable asset for the SPL engineers and vice versa, a fragment that has not been repeated yet, may be relevant as a reusable asset. We have validated these ideas with our industrial partner BSH, an induction hobs manufacturer that generates the firmware of their products from a model-driven SPL.","PeriodicalId":339158,"journal":{"name":"Proceedings of the 19th International Conference on Software Product Line","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126422507","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}
Cyber-Physical Systems (CPSs) are the future generation of highly connected embedded systems having applications in diverse domains including Oil and Gas. Employing Product Line Engineering (PLE) is believed to bring potential benefits with respect to reduced cost, higher productivity, higher quality, and faster time-to-market. However, relatively few industrial field studies are reported regarding the application of PLE to develop large-scale systems, and more specifically CPSs. In this paper, we report about our experiences and insights gained from investigating the application of model-based PLE at a large international organization developing subsea production systems (typical CPSs) to manage the exploitation of oil and gas production fields. We report in this paper 1) how two systematic domain analyses (on requirements engineering and product configuration/derivation) were conducted to elicit CPS PLE requirements and challenges, 2) key results of the domain analysis (commonly observed in other domains), and 3) our initial experience of developing and applying two Model Based System Engineering (MBSE) PLE solution to address some of the requirements and challenges elicited during the domain analyses.
{"title":"Cyber-physical system product line engineering: comprehensive domain analysis and experience report","authors":"T. Yue, Shaukat Ali, B. Selić","doi":"10.1145/2791060.2791067","DOIUrl":"https://doi.org/10.1145/2791060.2791067","url":null,"abstract":"Cyber-Physical Systems (CPSs) are the future generation of highly connected embedded systems having applications in diverse domains including Oil and Gas. Employing Product Line Engineering (PLE) is believed to bring potential benefits with respect to reduced cost, higher productivity, higher quality, and faster time-to-market. However, relatively few industrial field studies are reported regarding the application of PLE to develop large-scale systems, and more specifically CPSs. In this paper, we report about our experiences and insights gained from investigating the application of model-based PLE at a large international organization developing subsea production systems (typical CPSs) to manage the exploitation of oil and gas production fields. We report in this paper 1) how two systematic domain analyses (on requirements engineering and product configuration/derivation) were conducted to elicit CPS PLE requirements and challenges, 2) key results of the domain analysis (commonly observed in other domains), and 3) our initial experience of developing and applying two Model Based System Engineering (MBSE) PLE solution to address some of the requirements and challenges elicited during the domain analyses.","PeriodicalId":339158,"journal":{"name":"Proceedings of the 19th International Conference on Software Product Line","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130055233","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}
Product line engineering derives product variants by selecting features. Understanding the correlation between feature selection and performance is important for stakeholders to acquire a desirable product variant. We infer such a correlation using four regression methods based on small samples of measured configurations, without additional effort to detect feature interactions. We conduct experiments on six real-world case studies to evaluate the prediction accuracy of the regression methods. A key finding in our empirical study is that one regression method, called Bagging, is identified as the best to make accurate and robust predictions for the studied systems.
{"title":"Empirical comparison of regression methods for variability-aware performance prediction","authors":"P. Valov, Jianmei Guo, K. Czarnecki","doi":"10.1145/2791060.2791069","DOIUrl":"https://doi.org/10.1145/2791060.2791069","url":null,"abstract":"Product line engineering derives product variants by selecting features. Understanding the correlation between feature selection and performance is important for stakeholders to acquire a desirable product variant. We infer such a correlation using four regression methods based on small samples of measured configurations, without additional effort to detect feature interactions. We conduct experiments on six real-world case studies to evaluate the prediction accuracy of the regression methods. A key finding in our empirical study is that one regression method, called Bagging, is identified as the best to make accurate and robust predictions for the studied systems.","PeriodicalId":339158,"journal":{"name":"Proceedings of the 19th International Conference on Software Product Line","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114542726","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}
Sabrina Souto, D. Gopinath, Marcelo d’Amorim, D. Marinov, S. Khurshid, D. Batory
A software product line (SPL) is a family of programs that are differentiated by features --- increments in functionality. Systematically testing an SPL is challenging because it requires running each test of a test suite against a combinatorial number of programs. Feature models capture dependencies among features and can (1) reduce the space of programs to test and (2) enable accurate categorization of failing tests as failures of programs or the tests themselves, not as failures due to illegal combinations of features. In practice, sadly, feature models are not always available. We introduce SPLif, the first approach for testing SPLs that does not require the a priori availability of feature models. Our insight is to use a profile of passing and failing test runs to quickly identify failures that are indicative of real problems in test or code rather than specious failures due to illegal feature combinations. Experimental results on five SPLs and one large configurable system (GCC) demonstrate the effectiveness of our approach. SPLif enabled the discovery of five news bugs in GCC, three of which have already been fixed.
{"title":"Faster bug detection for software product lines with incomplete feature models","authors":"Sabrina Souto, D. Gopinath, Marcelo d’Amorim, D. Marinov, S. Khurshid, D. Batory","doi":"10.1145/2791060.2791093","DOIUrl":"https://doi.org/10.1145/2791060.2791093","url":null,"abstract":"A software product line (SPL) is a family of programs that are differentiated by features --- increments in functionality. Systematically testing an SPL is challenging because it requires running each test of a test suite against a combinatorial number of programs. Feature models capture dependencies among features and can (1) reduce the space of programs to test and (2) enable accurate categorization of failing tests as failures of programs or the tests themselves, not as failures due to illegal combinations of features. In practice, sadly, feature models are not always available. We introduce SPLif, the first approach for testing SPLs that does not require the a priori availability of feature models. Our insight is to use a profile of passing and failing test runs to quickly identify failures that are indicative of real problems in test or code rather than specious failures due to illegal feature combinations. Experimental results on five SPLs and one large configurable system (GCC) demonstrate the effectiveness of our approach. SPLif enabled the discovery of five news bugs in GCC, three of which have already been fixed.","PeriodicalId":339158,"journal":{"name":"Proceedings of the 19th International Conference on Software Product Line","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115009625","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}
Automotive manufacturing ranks among the most extreme instances of systems and software product line engineering (PLE). The product family numbers in the millions, each product is highly complex in its own right, and the variation across products is literally astronomical in scale. This paper explores the aspects that make the domain extreme and the very specific implications they have for PLE. These implications include the need for efficient manufacturing, complexity management, concurrent development streams, globally distributed engineering and production, a hierarchical product family tree, multi-level variation binding, constraint management, and a highly robust and integrated PLE tooling environment. Happily, the PLE paradigm supporting these implications brings about a number of opportunities for analysis and automation that provide efficiencies of production previously unattainable. We focus on one example in depth: The management and automated generation of the many thousands of calibration parameters that determine vehicle-specific software behavior. Throughout, we use the vehicle product line at General Motors, which we believe to be the world's largest, to illustrate and ground our journey through automotive PLE.
{"title":"How automotive engineering is taking product line engineering to the extreme","authors":"L. Wozniak, P. Clements","doi":"10.1145/2791060.2791071","DOIUrl":"https://doi.org/10.1145/2791060.2791071","url":null,"abstract":"Automotive manufacturing ranks among the most extreme instances of systems and software product line engineering (PLE). The product family numbers in the millions, each product is highly complex in its own right, and the variation across products is literally astronomical in scale. This paper explores the aspects that make the domain extreme and the very specific implications they have for PLE. These implications include the need for efficient manufacturing, complexity management, concurrent development streams, globally distributed engineering and production, a hierarchical product family tree, multi-level variation binding, constraint management, and a highly robust and integrated PLE tooling environment. Happily, the PLE paradigm supporting these implications brings about a number of opportunities for analysis and automation that provide efficiencies of production previously unattainable. We focus on one example in depth: The management and automated generation of the many thousands of calibration parameters that determine vehicle-specific software behavior. Throughout, we use the vehicle product line at General Motors, which we believe to be the world's largest, to illustrate and ground our journey through automotive PLE.","PeriodicalId":339158,"journal":{"name":"Proceedings of the 19th International Conference on Software Product Line","volume":"243 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124675412","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 give a brief overview on the tutorial "Managing Requirements in Product Lines".
在本文中，我们简要概述了“在产品线中管理需求”这一教程。
{"title":"Managing requirements in product lines","authors":"Danilo Beuche","doi":"10.1145/2791060.2791115","DOIUrl":"https://doi.org/10.1145/2791060.2791115","url":null,"abstract":"In this paper, we give a brief overview on the tutorial \"Managing Requirements in Product Lines\".","PeriodicalId":339158,"journal":{"name":"Proceedings of the 19th International Conference on Software Product Line","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127653223","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}
Although most programming languages naturally share several language features, they are typically implemented as a monolithic product. Language features cannot be plugged and unplugged from a language and reused in another language. Some modular approaches to language construction do exist but composing language features requires a deep understanding of its implementation hampering their use. The choose and pick approach from software product lines provides an easy way to compose a language out of a set of language features. However, current approaches to language product lines are not sufficient enough to cope with the complexity and evolution of real world programming languages. In this work, we propose a general light-weight bottom-up approach to automatically extract a feature model from a set of tagged language components. We applied this approach to the Neverlang language development framework and developed the AiDE tool to guide language developers towards a valid language composition. The approach has been evaluated on a decomposed version of Javascript to highlight the benefits of such a language product line.
{"title":"Choosy and picky: configuration of language product lines","authors":"Thomas Kühn, W. Cazzola, Diego Mathias Olivares","doi":"10.1145/2791060.2791092","DOIUrl":"https://doi.org/10.1145/2791060.2791092","url":null,"abstract":"Although most programming languages naturally share several language features, they are typically implemented as a monolithic product. Language features cannot be plugged and unplugged from a language and reused in another language. Some modular approaches to language construction do exist but composing language features requires a deep understanding of its implementation hampering their use. The choose and pick approach from software product lines provides an easy way to compose a language out of a set of language features. However, current approaches to language product lines are not sufficient enough to cope with the complexity and evolution of real world programming languages. In this work, we propose a general light-weight bottom-up approach to automatically extract a feature model from a set of tagged language components. We applied this approach to the Neverlang language development framework and developed the AiDE tool to guide language developers towards a valid language composition. The approach has been evaluated on a decomposed version of Javascript to highlight the benefits of such a language product line.","PeriodicalId":339158,"journal":{"name":"Proceedings of the 19th International Conference on Software Product Line","volume":"132 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132374335","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}
Bernhard Rumpe, Christoph Schulze, Michael von Wenckstern, Jan Oliver Ringert, Peter Manhart
Embedded software systems, e.g. automotive, robotic or automation systems are highly configurable and consist of many software components being available in different variants and versions. To identify the degree of reusability between these different occurrences of a component, it is necessary to determine the functional backward and forward compatibility between them. Based on this information it is possible to identify in which system context a component can be replaced safely by another version, e.g. exchanging an older component, or variant, e.g. introducing new features, to achieve the same functionality. This paper presents a model checking approach to determine behavioral compatibility of Simulink models, obtained from different component variants or during evolution. A prototype for automated compatibility checking demonstrates its feasibility. In addition implemented optimizations make the analysis more efficient, when the compared variants or versions are structurally similar. A case study on a driver assistance system provided by Daimler AG shows the effectiveness of the approach to automatically compare Simulink components.
{"title":"Behavioral compatibility of simulink models for product line maintenance and evolution","authors":"Bernhard Rumpe, Christoph Schulze, Michael von Wenckstern, Jan Oliver Ringert, Peter Manhart","doi":"10.1145/2791060.2791077","DOIUrl":"https://doi.org/10.1145/2791060.2791077","url":null,"abstract":"Embedded software systems, e.g. automotive, robotic or automation systems are highly configurable and consist of many software components being available in different variants and versions. To identify the degree of reusability between these different occurrences of a component, it is necessary to determine the functional backward and forward compatibility between them. Based on this information it is possible to identify in which system context a component can be replaced safely by another version, e.g. exchanging an older component, or variant, e.g. introducing new features, to achieve the same functionality. This paper presents a model checking approach to determine behavioral compatibility of Simulink models, obtained from different component variants or during evolution. A prototype for automated compatibility checking demonstrates its feasibility. In addition implemented optimizations make the analysis more efficient, when the compared variants or versions are structurally similar. A case study on a driver assistance system provided by Daimler AG shows the effectiveness of the approach to automatically compare Simulink components.","PeriodicalId":339158,"journal":{"name":"Proceedings of the 19th International Conference on Software Product Line","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130616130","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}
Developing a Software Product Line is a significant investment since domain experts must work together with software developers to understand and model a specific domain and then transform those models into a working software system. A product line increases the essential complexity of software assets because of the widespread variability among the member applications and the requirement to configure an application by its desired features. We seek mechanisms and theories to reduce the manual effort in writing the software. This workshop focuses on a broad range of approaches that increase the amount of synthesized code in both the shared code assets of the product line as well as individual member applications. We are especially interested in modular approaches that provide a theory of composition for assembling together modular units (such as classes, mixins, combinators, aspects, and modules).
{"title":"Modular synthesis of product lines (ModSyn-PL)","authors":"J. Rehof, G. Heineman","doi":"10.1145/2791060.2791061","DOIUrl":"https://doi.org/10.1145/2791060.2791061","url":null,"abstract":"Developing a Software Product Line is a significant investment since domain experts must work together with software developers to understand and model a specific domain and then transform those models into a working software system. A product line increases the essential complexity of software assets because of the widespread variability among the member applications and the requirement to configure an application by its desired features. We seek mechanisms and theories to reduce the manual effort in writing the software. This workshop focuses on a broad range of approaches that increase the amount of synthesized code in both the shared code assets of the product line as well as individual member applications. We are especially interested in modular approaches that provide a theory of composition for assembling together modular units (such as classes, mixins, combinators, aspects, and modules).","PeriodicalId":339158,"journal":{"name":"Proceedings of the 19th International Conference on Software Product Line","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114234157","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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