A software product line (SPL) is a set of products that is produced by an organization or organizations using shared assets. My position in the context of this workshop is that students cannot fully grasp the concepts of SPL until they see the interplay between the technical aspects of product design and implementation with the business aspects of planning a set of products as a unit instead of a single product at a time. We developed the Arcade Game Maker Pedagogical Product Line (PPL) as support for software product line education. The PPL has been used by several organizations and in various instructional and research contexts. I will relate several experiences in the construction and use of the PPL. The PPL has served its purpose well and continues to be used.
{"title":"Ten years of the arcade game maker pedagogical product line","authors":"J. McGregor","doi":"10.1145/2647908.2655962","DOIUrl":"https://doi.org/10.1145/2647908.2655962","url":null,"abstract":"A software product line (SPL) is a set of products that is produced by an organization or organizations using shared assets. My position in the context of this workshop is that students cannot fully grasp the concepts of SPL until they see the interplay between the technical aspects of product design and implementation with the business aspects of planning a set of products as a unit instead of a single product at a time. We developed the Arcade Game Maker Pedagogical Product Line (PPL) as support for software product line education. The PPL has been used by several organizations and in various instructional and research contexts. I will relate several experiences in the construction and use of the PPL. The PPL has served its purpose well and continues to be used.","PeriodicalId":339444,"journal":{"name":"Software Product Lines Conference","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114906011","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}
Adoption of SPLE techniques is challenging and expensive. Hence, automation in the adoption process is desirable, especially with respect to variability management. Different methods have been suggested for (semi-)automatically generating feature models from requirements or textual descriptions of products. However, while there are different ways to represent the same SPL in feature models, addressing different stakeholders' needs and preferences, existing methods usually follow fixed, predefined ways to generate feature models. As a result, the generated feature models may represent perspectives less relevant to the given tasks. In this paper we suggest an ontological approach that measures the semantic similarity, extracts variability, and automatically generates feature models that represent structural (objects-related) or functional (actions-related) perspectives. The stakeholders are able to control the perspective of the generated feature models, considering their needs and preferences for given tasks.
{"title":"Generating feature models from requirements: structural vs. functional perspectives","authors":"Nili Itzik, Iris Reinhartz-Berger","doi":"10.1145/2647908.2655966","DOIUrl":"https://doi.org/10.1145/2647908.2655966","url":null,"abstract":"Adoption of SPLE techniques is challenging and expensive. Hence, automation in the adoption process is desirable, especially with respect to variability management. Different methods have been suggested for (semi-)automatically generating feature models from requirements or textual descriptions of products. However, while there are different ways to represent the same SPL in feature models, addressing different stakeholders' needs and preferences, existing methods usually follow fixed, predefined ways to generate feature models. As a result, the generated feature models may represent perspectives less relevant to the given tasks.\u0000 In this paper we suggest an ontological approach that measures the semantic similarity, extracts variability, and automatically generates feature models that represent structural (objects-related) or functional (actions-related) perspectives. The stakeholders are able to control the perspective of the generated feature models, considering their needs and preferences for given tasks.","PeriodicalId":339444,"journal":{"name":"Software Product Lines Conference","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128648558","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 variability model checker VMC accepts a product family specified as a Modal Transition System (MTS) with additional variability constraints. Consequently, it offers behavioral variability analyses over both the family and its valid product behavior. This ranges from product derivation and simulation to efficient on-the-fly model checking of logical properties expressed in a variability-aware version of action-based CTL. In this paper, we first explain the reasons and assumptions underlying the choice for a modeling and analysis framework based on MTSs. Subsequently, we present recent advances on proving inheritance of behavioral analysis properties from a product family to its valid products. Finally, we illustrate challenges remaining for the future.
{"title":"VMC: recent advances and challenges ahead","authors":"M. T. Beek, F. Mazzanti","doi":"10.1145/2647908.2655969","DOIUrl":"https://doi.org/10.1145/2647908.2655969","url":null,"abstract":"The variability model checker VMC accepts a product family specified as a Modal Transition System (MTS) with additional variability constraints. Consequently, it offers behavioral variability analyses over both the family and its valid product behavior. This ranges from product derivation and simulation to efficient on-the-fly model checking of logical properties expressed in a variability-aware version of action-based CTL. In this paper, we first explain the reasons and assumptions underlying the choice for a modeling and analysis framework based on MTSs. Subsequently, we present recent advances on proving inheritance of behavioral analysis properties from a product family to its valid products. Finally, we illustrate challenges remaining for the future.","PeriodicalId":339444,"journal":{"name":"Software Product Lines Conference","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121911851","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}
Michael Wagner, G. Dudeck, Christian Hein, Nikolay Tcholtchev, C. Gebhardt, Andreas Korff
Even though product line technologies and methods are well established in today's development environments, various challenges still remain. Different ways of handling variability in system development tools have arisen posing an integration challenge to today's tool chains. This issue is further amplified by the variety of integration approaches. The VARIES framework addresses these challenges through technology adaptation, i.e. the utilization of model transformations and traceability support.
{"title":"VARIES framework to support tool integration in product line engineering","authors":"Michael Wagner, G. Dudeck, Christian Hein, Nikolay Tcholtchev, C. Gebhardt, Andreas Korff","doi":"10.1145/2647908.2655975","DOIUrl":"https://doi.org/10.1145/2647908.2655975","url":null,"abstract":"Even though product line technologies and methods are well established in today's development environments, various challenges still remain. Different ways of handling variability in system development tools have arisen posing an integration challenge to today's tool chains. This issue is further amplified by the variety of integration approaches. The VARIES framework addresses these challenges through technology adaptation, i.e. the utilization of model transformations and traceability support.","PeriodicalId":339444,"journal":{"name":"Software Product Lines Conference","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121947815","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}
Software product line engineering is an emerging methodology for the development of variant-rich software systems. As software product lines are viable for this purpose, testing them is complicated in contrast to non-variable systems, as there is an increasingly amount of possible products due to the number of features. There exist many methods proposed for testing software product lines, but seldom the quality of the resulting tests was assessed. For assessing test quality mutation analysis is a well-known technique and is frequently applied to non-variable software systems. However, mutation analysis cannot be applied straight-forward onto software product lines. We present a mutation system for assessing the quality of software product line tests by means of fault detection capability. Our mutation system comprises model-based mutation operators, test case adaption, automated model and test execution, and automated mutation analysis. So far, we developed several mutation operators for feature models, UML state machines, and mapping models. We evaluated the mutation operators against tests that were generated from the specifications and applied them for three case studies. From the results we draw conclusions about the effectiveness of the individual mutation operators.
{"title":"Towards the assessment of software product line tests: a mutation system for variable systems","authors":"H. Lackner, Martin Schmidt","doi":"10.1145/2647908.2655968","DOIUrl":"https://doi.org/10.1145/2647908.2655968","url":null,"abstract":"Software product line engineering is an emerging methodology for the development of variant-rich software systems. As software product lines are viable for this purpose, testing them is complicated in contrast to non-variable systems, as there is an increasingly amount of possible products due to the number of features. There exist many methods proposed for testing software product lines, but seldom the quality of the resulting tests was assessed. For assessing test quality mutation analysis is a well-known technique and is frequently applied to non-variable software systems. However, mutation analysis cannot be applied straight-forward onto software product lines.\u0000 We present a mutation system for assessing the quality of software product line tests by means of fault detection capability. Our mutation system comprises model-based mutation operators, test case adaption, automated model and test execution, and automated mutation analysis. So far, we developed several mutation operators for feature models, UML state machines, and mapping models. We evaluated the mutation operators against tests that were generated from the specifications and applied them for three case studies. From the results we draw conclusions about the effectiveness of the individual mutation operators.","PeriodicalId":339444,"journal":{"name":"Software Product Lines Conference","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133784075","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}
A. Murguzur, Rafael Capilla, Salvador Trujillo, Óscar Ortiz, R. Lopez-Herrejon
In emerging domains such as Cloud-based Industrial Control Systems (ICSs) and SCADA systems where data-intensive and high performance computing are needed, a higher degree of flexibility is being demanded to meet new stakeholder requirements, context changes and intrinsic complexity. In this light, Dynamic Software Product Lines (DSPLs) provide a way to build self-managing systems exploiting traditional product line engineering concepts at runtime. Although context-awareness is widely perceived to be a first-class concern in such runtime variability mechanisms, existing approaches do not provide the necessary level of formalization to model and enact context variability for DSPLs. This is crucial for operational analytics processes since variant configuration could differ from context to context depending on diverse data values linked to context features and cross-tree constraints in a feature model. In this paper, we propose a context variability modeling approach, demonstrate its applicability and usability via a wind farm use case, and present the fundamental building blocks of a framework for enabling context variability in service-based DSPLs which provide Workflow as a Service (WFaaS).
{"title":"Context variability modeling for runtime configuration of service-based dynamic software product lines","authors":"A. Murguzur, Rafael Capilla, Salvador Trujillo, Óscar Ortiz, R. Lopez-Herrejon","doi":"10.1145/2647908.2655957","DOIUrl":"https://doi.org/10.1145/2647908.2655957","url":null,"abstract":"In emerging domains such as Cloud-based Industrial Control Systems (ICSs) and SCADA systems where data-intensive and high performance computing are needed, a higher degree of flexibility is being demanded to meet new stakeholder requirements, context changes and intrinsic complexity. In this light, Dynamic Software Product Lines (DSPLs) provide a way to build self-managing systems exploiting traditional product line engineering concepts at runtime. Although context-awareness is widely perceived to be a first-class concern in such runtime variability mechanisms, existing approaches do not provide the necessary level of formalization to model and enact context variability for DSPLs. This is crucial for operational analytics processes since variant configuration could differ from context to context depending on diverse data values linked to context features and cross-tree constraints in a feature model. In this paper, we propose a context variability modeling approach, demonstrate its applicability and usability via a wind farm use case, and present the fundamental building blocks of a framework for enabling context variability in service-based DSPLs which provide Workflow as a Service (WFaaS).","PeriodicalId":339444,"journal":{"name":"Software Product Lines Conference","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124726154","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}
Jens Meinicke, Thomas Thüm, R. Schröter, Fabian Benduhn, G. Saake
A software product line is a set of different software products that share commonalities. For a selection of features, specialized products of one domain can be generated automatically from domain artifacts. However, analyses of software product lines need to handle a large number of products that can be exponential in the number of features. In the last decade, many approaches have been proposed to analyze software product lines efficiently. For some of these approaches tool support is available. Based on a recent survey on analysis for software product lines, we provide a first overview on such tools. While our discussion is limited to analysis tools, we provide an accompanying website covering further tools for product-line development. We compare tools according to their analysis and implementation strategy to identify underrepresented areas. In addition, we want to ease the reuse of existing tools for researchers and students, and to simplify research transfer to practice.
{"title":"An overview on analysis tools for software product lines","authors":"Jens Meinicke, Thomas Thüm, R. Schröter, Fabian Benduhn, G. Saake","doi":"10.1145/2647908.2655972","DOIUrl":"https://doi.org/10.1145/2647908.2655972","url":null,"abstract":"A software product line is a set of different software products that share commonalities. For a selection of features, specialized products of one domain can be generated automatically from domain artifacts. However, analyses of software product lines need to handle a large number of products that can be exponential in the number of features. In the last decade, many approaches have been proposed to analyze software product lines efficiently. For some of these approaches tool support is available. Based on a recent survey on analysis for software product lines, we provide a first overview on such tools. While our discussion is limited to analysis tools, we provide an accompanying website covering further tools for product-line development. We compare tools according to their analysis and implementation strategy to identify underrepresented areas. In addition, we want to ease the reuse of existing tools for researchers and students, and to simplify research transfer to practice.","PeriodicalId":339444,"journal":{"name":"Software Product Lines Conference","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125315127","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 research of cognitive psychology, experiments to measure cognitive processes may be run in many similar yet slightly different configurations. Variability engineering offers techniques to handle variable configurations both conceptually and technically. However, these techniques are largely unknown to cognitive psychologists so that experiment configurations are specified informally or too coarse grain. This is problematic, because it becomes difficult to get an overview of paradigm configurations used in the so far conducted experiments. Variability engineering techniques provide, i.a., concise notations for capturing variability in software and can also be used to express the configurable nature of a wide range of experiments in cognitive psychology. Furthermore, it enables cognitive psychologists to structure configuration knowledge, to identify suitably similar experiment setups and to more efficiently identify individual configuration options as relevant reasons for a particular effect in the outcome of an experiment. In this paper, we present experiences with teaching variability engineering to cognitive psychologists along with a suitable curriculum.
{"title":"Teaching variability engineering to cognitive psychologists","authors":"C. Seidl, I. Domachowska","doi":"10.1145/2647908.2655961","DOIUrl":"https://doi.org/10.1145/2647908.2655961","url":null,"abstract":"In research of cognitive psychology, experiments to measure cognitive processes may be run in many similar yet slightly different configurations. Variability engineering offers techniques to handle variable configurations both conceptually and technically. However, these techniques are largely unknown to cognitive psychologists so that experiment configurations are specified informally or too coarse grain. This is problematic, because it becomes difficult to get an overview of paradigm configurations used in the so far conducted experiments. Variability engineering techniques provide, i.a., concise notations for capturing variability in software and can also be used to express the configurable nature of a wide range of experiments in cognitive psychology. Furthermore, it enables cognitive psychologists to structure configuration knowledge, to identify suitably similar experiment setups and to more efficiently identify individual configuration options as relevant reasons for a particular effect in the outcome of an experiment. In this paper, we present experiences with teaching variability engineering to cognitive psychologists along with a suitable curriculum.","PeriodicalId":339444,"journal":{"name":"Software Product Lines Conference","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129503592","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 Model Based Testing (MBT), test cases are generated automatically from a partial representation of expected behaviour of the System Under Test (SUT) (i.e., the model). For most industrial systems, it is impossible to generate all the possible test cases from the model. The test engineer recourse to generation algorithms that maximize a given coverage criterion, a metric indicating the percentage of possible behaviours of the SUT covered by the test cases. Our previous work redefined classical Transition Systems (TSs) criteria for SPLs, using Featured Transition Systems (FTSs), a mathematical structure to compactly represent the behaviour of a SPL, as model for test case generation. In this paper, we provide one all-states coverage driven generation algorithm and discuss its scalability and efficiency with respect to random generation. All-states and random generation are compared on fault-seeded FTSs.
{"title":"Abstract test case generation for behavioural testing of software product lines","authors":"Xavier Devroey, Gilles Perrouin, Pierre-Yves Schobbens","doi":"10.1145/2647908.2655971","DOIUrl":"https://doi.org/10.1145/2647908.2655971","url":null,"abstract":"In Model Based Testing (MBT), test cases are generated automatically from a partial representation of expected behaviour of the System Under Test (SUT) (i.e., the model). For most industrial systems, it is impossible to generate all the possible test cases from the model. The test engineer recourse to generation algorithms that maximize a given coverage criterion, a metric indicating the percentage of possible behaviours of the SUT covered by the test cases. Our previous work redefined classical Transition Systems (TSs) criteria for SPLs, using Featured Transition Systems (FTSs), a mathematical structure to compactly represent the behaviour of a SPL, as model for test case generation. In this paper, we provide one all-states coverage driven generation algorithm and discuss its scalability and efficiency with respect to random generation. All-states and random generation are compared on fault-seeded FTSs.","PeriodicalId":339444,"journal":{"name":"Software Product Lines Conference","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134182492","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}
Sönke Holthusen, David Wille, Christoph Legat, Simon Beddig, Ina Schaefer, B. Vogel‐Heuser
Automation systems are mostly individual highly customized system variants, consisting both of hardware and software. In order to reduce development effort, it is a common practice to use a clone-and-own approach by modifying an existing variant to fit the changed requirements of a new variant. The information about the commonalities and differences between those variants is usually not well documented and leads to problems in maintenance, testing and evolution. To alleviate these problems, in this paper, we present an improved version of a family mining approach for automatically discovering commonality and variability between related system variants. We apply this approach to function block diagrams used to develop automation software and show its feasibility by a manufacturing case study.
{"title":"Family model mining for function block diagrams in automation software","authors":"Sönke Holthusen, David Wille, Christoph Legat, Simon Beddig, Ina Schaefer, B. Vogel‐Heuser","doi":"10.1145/2647908.2655965","DOIUrl":"https://doi.org/10.1145/2647908.2655965","url":null,"abstract":"Automation systems are mostly individual highly customized system variants, consisting both of hardware and software. In order to reduce development effort, it is a common practice to use a clone-and-own approach by modifying an existing variant to fit the changed requirements of a new variant. The information about the commonalities and differences between those variants is usually not well documented and leads to problems in maintenance, testing and evolution. To alleviate these problems, in this paper, we present an improved version of a family mining approach for automatically discovering commonality and variability between related system variants. We apply this approach to function block diagrams used to develop automation software and show its feasibility by a manufacturing case study.","PeriodicalId":339444,"journal":{"name":"Software Product Lines Conference","volume":"257 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116017999","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：