It is common for organizations to maintain multiple variants of a given business process, such as multiple sales processes for different products or multiple bookkeeping processes for different countries. Conventional business process modeling languages [2] do not explicitly support the representation of such families of process variants, requiring one of two paths to be chosen. Either each variant is modeled separately or multiple variants are modeled together. The former option results in duplication as the variants have much in common, potential inconsistencies as the variants are modified independently of each other, and missed opportunities for identifying shared IT services that can support these business processes. The latter option leads to highly complex consolidated models, which hamper the analysis and maintenance of individual process model variants. These shortcomings triggered significant research efforts over the last two decades, leading to an array of approaches to business process variability modeling [1]. A common trait of these approaches is that they extend a conventional process modeling language with constructs to represent customizable process models. A customizable process model captures a family of process model variants in a way that the individual variants can be derived by adding or deleting fragments according to customization parameters or to a domain model. Accordingly, a customizable process model encapsulates customization decisions between process variants that need to be made either at design-time or run-time. Designtime customization decisions lead to a customized process model that is intended to be executed in a particular organizational setting. Hence, these decisions affect all instances of the customized process executed in this setting. The timeframe associated with these decisions may be long (e.g. months or years). In contrast, run-time customization decisions are punctual and affect only one or a few process instances. Such decisions may be visualized on top of a process model, but they are not intended to modify the executed process model itself, beyond its effects on the process instance(s) where the decision is applied. This talk retraces the last two decades of research in modeling business process variability via customizable process models. The talk draws up a taxonomy and comparative analysis of approaches in this area, shedding light on strengths and weaknesses of each approach, with the ultimate goal of distilling relative trade-offs and practical criteria for selection. Are there still research gaps in modeling business process variability, or are we done with it?
{"title":"Modeling Business Process Variability: Are We Done Yet?","authors":"M. Rosa","doi":"10.1145/3106195.3106196","DOIUrl":"https://doi.org/10.1145/3106195.3106196","url":null,"abstract":"It is common for organizations to maintain multiple variants of a given business process, such as multiple sales processes for different products or multiple bookkeeping processes for different countries. Conventional business process modeling languages [2] do not explicitly support the representation of such families of process variants, requiring one of two paths to be chosen. Either each variant is modeled separately or multiple variants are modeled together. The former option results in duplication as the variants have much in common, potential inconsistencies as the variants are modified independently of each other, and missed opportunities for identifying shared IT services that can support these business processes. The latter option leads to highly complex consolidated models, which hamper the analysis and maintenance of individual process model variants. These shortcomings triggered significant research efforts over the last two decades, leading to an array of approaches to business process variability modeling [1]. A common trait of these approaches is that they extend a conventional process modeling language with constructs to represent customizable process models. A customizable process model captures a family of process model variants in a way that the individual variants can be derived by adding or deleting fragments according to customization parameters or to a domain model. Accordingly, a customizable process model encapsulates customization decisions between process variants that need to be made either at design-time or run-time. Designtime customization decisions lead to a customized process model that is intended to be executed in a particular organizational setting. Hence, these decisions affect all instances of the customized process executed in this setting. The timeframe associated with these decisions may be long (e.g. months or years). In contrast, run-time customization decisions are punctual and affect only one or a few process instances. Such decisions may be visualized on top of a process model, but they are not intended to modify the executed process model itself, beyond its effects on the process instance(s) where the decision is applied. This talk retraces the last two decades of research in modeling business process variability via customizable process models. The talk draws up a taxonomy and comparative analysis of approaches in this area, shedding light on strengths and weaknesses of each approach, with the ultimate goal of distilling relative trade-offs and practical criteria for selection. Are there still research gaps in modeling business process variability, or are we done with it?","PeriodicalId":339444,"journal":{"name":"Software Product Lines Conference","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127874313","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 resource requirements of Big Data applications may vary dramatically over time, depending on changes in the context. If resources should not be defined for the maximum case, but available resources are mostly static, there is a need to adapt resource usage by modifying the processing behavior. The QualiMaster project researches such an approach for the analysis of systemic risks in the financial markets.
{"title":"Resource-optimizing adaptation for big data applications","authors":"Holger Eichelberger, Klaus Schmid","doi":"10.1145/2647908.2655958","DOIUrl":"https://doi.org/10.1145/2647908.2655958","url":null,"abstract":"The resource requirements of Big Data applications may vary dramatically over time, depending on changes in the context. If resources should not be defined for the maximum case, but available resources are mostly static, there is a need to adapt resource usage by modifying the processing behavior. The QualiMaster project researches such an approach for the analysis of systemic risks in the financial markets.","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":"123468112","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 mCRL2 language and supporting software provide a state-of-the-art tool suite for the verification of distributed systems. In this paper, we present the general principles, extrapolated from [7,8], which make us believe that mCRL2 can also be used for behavioral variability analysis of product families. The mCRL2 data language allows to smoothly deal with feature sets and attributes, its process language is sufficiently rich to model feature selection, as well as product behavior based on an FTS-like semantics. Because of the feature-orientation, our modeling strategy allows a natural refactoring of the semantic model of a product family into a parallel composition of components that reflects coherent sets of features. This opens the way for dedicated abstraction and reduction techniques that strengthen the prospect of a scalable verification approach to software product lines. In this paper, we sketch how to model product families in mCRL2 and how to apply a modular verification method, preparing the ground to further assess the scalability of our approach, in particular regarding model checking.
{"title":"Software product line analysis with mCRL2","authors":"M. T. Beek, E. Vink","doi":"10.1145/2647908.2655970","DOIUrl":"https://doi.org/10.1145/2647908.2655970","url":null,"abstract":"The mCRL2 language and supporting software provide a state-of-the-art tool suite for the verification of distributed systems. In this paper, we present the general principles, extrapolated from [7,8], which make us believe that mCRL2 can also be used for behavioral variability analysis of product families. The mCRL2 data language allows to smoothly deal with feature sets and attributes, its process language is sufficiently rich to model feature selection, as well as product behavior based on an FTS-like semantics. Because of the feature-orientation, our modeling strategy allows a natural refactoring of the semantic model of a product family into a parallel composition of components that reflects coherent sets of features. This opens the way for dedicated abstraction and reduction techniques that strengthen the prospect of a scalable verification approach to software product lines. In this paper, we sketch how to model product families in mCRL2 and how to apply a modular verification method, preparing the ground to further assess the scalability of our approach, in particular regarding model checking.","PeriodicalId":339444,"journal":{"name":"Software Product Lines Conference","volume":"265 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":"132190781","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 gears from BigLever software","authors":"C. Krueger, P. Clements","doi":"10.1145/2647908.2655976","DOIUrl":"https://doi.org/10.1145/2647908.2655976","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":"85 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":"121945309","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. Collet, Sébastien Mosser, Simon Urli, M. Blay-Fornarino, Philippe Lahire
Teaching software engineering is an activity that needs to constantly evolve to cope with new paradigms, principles and techniques. In this paper, we briefly report on several years of experience in teaching both generative techniques in a model-driven engineering context and variability modeling related to software-product line engineering. Our current practice relies on making students progress on running projects that they evolve with different techniques along a semester. We also discuss the obtained benefits and some perspectives.
{"title":"Experiences in teaching variability modeling and model-driven generative techniques","authors":"P. Collet, Sébastien Mosser, Simon Urli, M. Blay-Fornarino, Philippe Lahire","doi":"10.1145/2647908.2655963","DOIUrl":"https://doi.org/10.1145/2647908.2655963","url":null,"abstract":"Teaching software engineering is an activity that needs to constantly evolve to cope with new paradigms, principles and techniques. In this paper, we briefly report on several years of experience in teaching both generative techniques in a model-driven engineering context and variability modeling related to software-product line engineering. Our current practice relies on making students progress on running projects that they evolve with different techniques along a semester. We also discuss the obtained benefits and some perspectives.","PeriodicalId":339444,"journal":{"name":"Software Product Lines Conference","volume":"7 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":"131002363","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}
Guillaume Bécan, Sana Ben Nasr, M. Acher, B. Baudry
Feature Models (FMs) are the de-facto standard for documenting, model checking, and reasoning about the configurations of a software system. This paper introduces WebFML a comprehensive environment for synthesizing FMs from various kinds of artefacts (e.g. propositional formula, dependency graph, FMs or product comparison matrices). A key feature of WebFML is an interactive support (through ranking lists, clusters, and logical heuristics) for choosing a sound and meaningful hierarchy. WebFML opens avenues for numerous practical applications (e.g., merging multiple product lines, slicing a configuration process, reverse engineering configurable systems).
{"title":"WebFML: synthesizing feature models everywhere","authors":"Guillaume Bécan, Sana Ben Nasr, M. Acher, B. Baudry","doi":"10.1145/2647908.2655974","DOIUrl":"https://doi.org/10.1145/2647908.2655974","url":null,"abstract":"Feature Models (FMs) are the de-facto standard for documenting, model checking, and reasoning about the configurations of a software system. This paper introduces WebFML a comprehensive environment for synthesizing FMs from various kinds of artefacts (e.g. propositional formula, dependency graph, FMs or product comparison matrices). A key feature of WebFML is an interactive support (through ranking lists, clusters, and logical heuristics) for choosing a sound and meaningful hierarchy. WebFML opens avenues for numerous practical applications (e.g., merging multiple product lines, slicing a configuration process, reverse engineering configurable systems).","PeriodicalId":339444,"journal":{"name":"Software Product Lines Conference","volume":"86 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":"132570469","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 software from scratch is a high cost and error-prone activity. A possible solution to reduce time-to-market and produce high quality software is the reuse of existing software. But when the number of features in the system grows, the maintenance becomes more complex. In such cases, to adopt a systematic approach, such as Software Product Line Engineering, is necessary. Existing systems are generally migrated to a product line, allowing systematic reuse of artefacts and easing maintenance. To this end, some approaches have been proposed in the literature in the last years. A mapping of works on this subject and the identification of some research gaps can lead to an improvement of such approaches. This paper describes the main outcomes of a systematic mapping study on the evolution and migration of systems to SPL. The main works found are presented and classified according to adopted strategy, artefacts used, and evaluation conducted. Analysis of the evolution along the past years are also presented. At the end, we summarize some trends and open issues to serve as reference to new researches.
{"title":"Feature location for software product line migration: a mapping study","authors":"W. K. Assunção, S. Vergilio","doi":"10.1145/2647908.2655967","DOIUrl":"https://doi.org/10.1145/2647908.2655967","url":null,"abstract":"Developing software from scratch is a high cost and error-prone activity. A possible solution to reduce time-to-market and produce high quality software is the reuse of existing software. But when the number of features in the system grows, the maintenance becomes more complex. In such cases, to adopt a systematic approach, such as Software Product Line Engineering, is necessary. Existing systems are generally migrated to a product line, allowing systematic reuse of artefacts and easing maintenance. To this end, some approaches have been proposed in the literature in the last years. A mapping of works on this subject and the identification of some research gaps can lead to an improvement of such approaches. This paper describes the main outcomes of a systematic mapping study on the evolution and migration of systems to SPL. The main works found are presented and classified according to adopted strategy, artefacts used, and evaluation conducted. Analysis of the evolution along the past years are also presented. At the end, we summarize some trends and open issues to serve as reference to new researches.","PeriodicalId":339444,"journal":{"name":"Software Product Lines Conference","volume":"44 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":"122662525","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}
Ahmed Eid El Yamany, Mohamed Shaheen, Abdel Salam Sayyad
Opti-Select is an Interactive Multi-objective feature analysis and optimization tool for software product lines configuration and feature models optimization based on an innovative UIL (User-In-the-loop) idea. In this tool, the experience of system analysts and stakeholders are merged with optimization techniques and algorithms. Opti-Select interactive tool is an integrated set of techniques providing step by step feature model and attribute configuration, selecting and excluding features, solution set optimization, and user interaction utilities that can all together reach satisfactory set of solutions that fits stakeholder preferences.
{"title":"OPTI-SELECT: an interactive tool for user-in-the-loop feature selection in software product lines","authors":"Ahmed Eid El Yamany, Mohamed Shaheen, Abdel Salam Sayyad","doi":"10.1145/2647908.2655977","DOIUrl":"https://doi.org/10.1145/2647908.2655977","url":null,"abstract":"Opti-Select is an Interactive Multi-objective feature analysis and optimization tool for software product lines configuration and feature models optimization based on an innovative UIL (User-In-the-loop) idea. In this tool, the experience of system analysts and stakeholders are merged with optimization techniques and algorithms.\u0000 Opti-Select interactive tool is an integrated set of techniques providing step by step feature model and attribute configuration, selecting and excluding features, solution set optimization, and user interaction utilities that can all together reach satisfactory set of solutions that fits stakeholder preferences.","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":"134015187","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 diversity of requirements elicited from different customers leads to the development of many variants. Furthermore, compliance with safety standards as mandated for safety-critical systems requires high test efforts for each variant. Model-based testing aims to reduce test efforts by automatically generating test cases from test models. In this paper, we introduce variability management to usage models, a widely used model-based testing formalism. We present an approach that allows to derive usage model variants from a desired set of features and thus generate test cases for each variant. The approach is integrated in the industrial model-based testing tool chain MaTeLo and exemplified using an industrial case study from the aerospace domain.
{"title":"MPLM - MaTeLo product line manager: [relating variability modelling and model-based testing]","authors":"Hamza Samih, Ralf Bogusch","doi":"10.1145/2647908.2655980","DOIUrl":"https://doi.org/10.1145/2647908.2655980","url":null,"abstract":"The diversity of requirements elicited from different customers leads to the development of many variants. Furthermore, compliance with safety standards as mandated for safety-critical systems requires high test efforts for each variant. Model-based testing aims to reduce test efforts by automatically generating test cases from test models.\u0000 In this paper, we introduce variability management to usage models, a widely used model-based testing formalism. We present an approach that allows to derive usage model variants from a desired set of features and thus generate test cases for each variant. The approach is integrated in the industrial model-based testing tool chain MaTeLo and exemplified using an industrial case study from the aerospace domain.","PeriodicalId":339444,"journal":{"name":"Software Product Lines Conference","volume":"301 2 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":"114392617","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}
Holger Eichelberger, Sascha El-Sharkawy, Christian Kröher, Klaus Schmid
Development of software product lines requires tool support, e.g., to define variability models, to check variability models for consistency and to derive the artifacts for a specific product. Further capabilities are required when product lines are combined to software ecosystems, i.e., management and development of distributed product lines across multiple different organizations. In this paper, we describe EASy-Producer, a prototypical tool set for the development of software product lines in general and variant-rich ecosystems in particular. To support the product line engineer, EASy-Producer differentiates between simplified views limiting the capabilities and expert views unleashing its full power. We will discuss how these two views support the definition of variability models, the derivation of product configurations and the instantiation of artifacts.
{"title":"EASy-producer: product line development for variant-rich ecosystems","authors":"Holger Eichelberger, Sascha El-Sharkawy, Christian Kröher, Klaus Schmid","doi":"10.1145/2647908.2655979","DOIUrl":"https://doi.org/10.1145/2647908.2655979","url":null,"abstract":"Development of software product lines requires tool support, e.g., to define variability models, to check variability models for consistency and to derive the artifacts for a specific product. Further capabilities are required when product lines are combined to software ecosystems, i.e., management and development of distributed product lines across multiple different organizations.\u0000 In this paper, we describe EASy-Producer, a prototypical tool set for the development of software product lines in general and variant-rich ecosystems in particular. To support the product line engineer, EASy-Producer differentiates between simplified views limiting the capabilities and expert views unleashing its full power. We will discuss how these two views support the definition of variability models, the derivation of product configurations and the instantiation of artifacts.","PeriodicalId":339444,"journal":{"name":"Software Product Lines Conference","volume":"88 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":"126372225","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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