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|Titel DE=Modeling and Selection of Software Service Variants
 
|Titel DE=Modeling and Selection of Software Service Variants
 
|Titel EN=Modeling and Selection of Software Service Variants
 
|Titel EN=Modeling and Selection of Software Service Variants
|Beschreibung DE=Software services are increasingly relevant for companies, public administrations, and end users. Major challenges for them are to be developed and delivered to meet possibly diverse consumer requirements and preferences. This requires the modeling of variants, addressing diverse consumer needs, and their selection. Existing approaches to deal with variability from software product line engineering fall short in this regard because they do not consider service-specifics like the involved roles, the changed delivery model, or the needs for participation and collaboration.
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|Beschreibung DE=The development and delivery of software services rises the challenge to meet diverse consumer requirements and preferences. One approach to tackle this challenge is to the model, select, and realize service variants. Variants are alternative instances of a service’s design, implementation, deployment, or operation. They bear potential for participation and increased reuse of artifacts in software development, and for delivering services to diverse or changing consumer needs. Existing approaches to deal with variability from software product line engineering, however, lack desirable capabilities regarding participation, collaboration, and representation of quality attributes. Further, they need extensions to address the delivery models, artifacts, and distinct roles in services.
 
 
 
This thesis presents service feature modeling, a novel approach consisting of a variability modeling language and a set of corresponding methods to model and select software service variants.
 
This thesis presents service feature modeling, a novel approach consisting of a variability modeling language and a set of corresponding methods to model and select software service variants.
 +
The service feature modeling language extends standard feature modeling from software product line engineering. A typology of feature types differentiates the semantics of features with the goal to utilize service feature models (SFMs) in novel ways. Attribute types represent concerns common to multiple attributes within an SFM to reduce modeling efforts and for attribute aggregation. A novel modeling method considers SFMs to be composed by services, addressing the collaboration of experts in modeling and the integration of software services to contribute parts of an SFM.
 +
Making use of SFMs, a set of methods is flexibly combined for decision-makers to determine which variant to develop or deliver. A configuration set determination method, extending existing approaches with attribute aggregation, produces all valid service variants represented by an SFM. Determined configuration sets are narrowed down with a novel, fuzzy requirements filter. Skyline filtering, adapted from database systems, dismisses service variants that are dominated by others. Preference-based ranking applies a well-known multi-criteria decision making approach to rank service variants based on their fulfillment of preferences. Through abstractions, it aims to enable participation by involving non-technical decision-makers in service variant selection.
 +
This thesis presents an evaluation of the outlined concepts, consisting of multiple parts. A proof- of-concept implementation and a performance evaluation of a SFM tool suite show the realizability and applicability of service feature modeling, including collaborative modeling and all outlined us- age methods. A first use case concerns the development of public services under consideration of service variants, whose selection was driven by citizen participation. A second use case concerns the modeling and selection of Infrastructure as a Service (IaaS) configurations and their automatic consumption and usage, illustrating how service feature modeling can drive the realization of selected service variants. Finally, an empirical evaluation indicates good acceptance, expressiveness, and usefulness and interpretability of service feature modeling.
  
The service feature modeling language extends standard feature modeling from software product line engineering. A typology of feature types differentiates the semantics of features and enables service feature models (SFMs) to be utilized in novel ways. Attribute types represent concerns common to multiple attributes within an SFM, thus reducing modeling efforts and avoiding redundancies, and allowing for the aggregation of attributes. A novel modeling method considers SFMs to be composed by services, allowing modelers to collaborate and to integrate software services to contribute parts of an SFM.
 
 
Making use of SFMs, a set of methods is flexibly combined to allow decision-makers to determine which variant to develop or deliver. Configuration set determination produces all valid service variants represented by an SFM. Determined configuration sets are narrowed down via requirements filtering, which dismisses service variants that do not fulfill the needs of decision-makers. Skyline filtering dismisses a configuration set of service variants that are dominated by others. Preference-based ranking applies multi-criteria decision making approaches to rank service variants based on their modeled fulfillment of preferences stated in polls. Through the abstraction of polls, preference-based ranking allows non-technical decision-makers to take part in service variant selection, thus enabling participation.
 
  
This thesis presents an evaluation of the outlined concepts that consists of multiple parts. A proof-of-concept implementation and a performance evaluation of a SFM tool suite show the realizability and applicability of service feature modeling. Two use cases further assert the applicability of the approach. The first one concerns the development of public services under consideration of service variants, whose selection was driven through citizen participation. The second use case concerns the modeling and selection of Infrastructure as a Service (IaaS) configurations and their automatic consumption and usage, illustrating how service feature modeling can drive the realization of selected service variants. Finally, an empirical evaluation indicates good acceptance, expressiveness, and usefulness and interpretability of service feature modeling.
 
|Beschreibung EN=Software services are increasingly relevant for companies, public administrations, and end users. Major challenges for them are to be developed and delivered to meet possibly diverse consumer requirements and preferences. This requires the modeling of variants, addressing diverse consumer needs, and their selection. Existing approaches to deal with variability from software product line engineering fall short in this regard because they do not consider service-specifics like the involved roles, the changed delivery model, or the needs for participation and collaboration.
 
  
 +
|Beschreibung EN=The development and delivery of software services rises the challenge to meet diverse consumer requirements and preferences. One approach to tackle this challenge is to the model, select, and realize service variants. Variants are alternative instances of a service’s design, implementation, deployment, or operation. They bear potential for participation and increased reuse of artifacts in software development, and for delivering services to diverse or changing consumer needs. Existing approaches to deal with variability from software product line engineering, however, lack desirable capabilities regarding participation, collaboration, and representation of quality attributes. Further, they need extensions to address the delivery models, artifacts, and distinct roles in services.
 
This thesis presents service feature modeling, a novel approach consisting of a variability modeling language and a set of corresponding methods to model and select software service variants.
 
This thesis presents service feature modeling, a novel approach consisting of a variability modeling language and a set of corresponding methods to model and select software service variants.
 +
The service feature modeling language extends standard feature modeling from software product line engineering. A typology of feature types differentiates the semantics of features with the goal to utilize service feature models (SFMs) in novel ways. Attribute types represent concerns common to multiple attributes within an SFM to reduce modeling efforts and for attribute aggregation. A novel modeling method considers SFMs to be composed by services, addressing the collaboration of experts in modeling and the integration of software services to contribute parts of an SFM.
 +
Making use of SFMs, a set of methods is flexibly combined for decision-makers to determine which variant to develop or deliver. A configuration set determination method, extending existing approaches with attribute aggregation, produces all valid service variants represented by an SFM. Determined configuration sets are narrowed down with a novel, fuzzy requirements filter. Skyline filtering, adapted from database systems, dismisses service variants that are dominated by others. Preference-based ranking applies a well-known multi-criteria decision making approach to rank service variants based on their fulfillment of preferences. Through abstractions, it aims to enable participation by involving non-technical decision-makers in service variant selection.
 +
This thesis presents an evaluation of the outlined concepts, consisting of multiple parts. A proof- of-concept implementation and a performance evaluation of a SFM tool suite show the realizability and applicability of service feature modeling, including collaborative modeling and all outlined us- age methods. A first use case concerns the development of public services under consideration of service variants, whose selection was driven by citizen participation. A second use case concerns the modeling and selection of Infrastructure as a Service (IaaS) configurations and their automatic consumption and usage, illustrating how service feature modeling can drive the realization of selected service variants. Finally, an empirical evaluation indicates good acceptance, expressiveness, and usefulness and interpretability of service feature modeling.
  
The service feature modeling language extends standard feature modeling from software product line engineering. A typology of feature types differentiates the semantics of features and enables service feature models (SFMs) to be utilized in novel ways. Attribute types represent concerns common to multiple attributes within an SFM, thus reducing modeling efforts and avoiding redundancies, and allowing for the aggregation of attributes. A novel modeling method considers SFMs to be composed by services, allowing modelers to collaborate and to integrate software services to contribute parts of an SFM.
 
 
Making use of SFMs, a set of methods is flexibly combined to allow decision-makers to determine which variant to develop or deliver. Configuration set determination produces all valid service variants represented by an SFM. Determined configuration sets are narrowed down via requirements filtering, which dismisses service variants that do not fulfill the needs of decision-makers. Skyline filtering dismisses a configuration set of service variants that are dominated by others. Preference-based ranking applies multi-criteria decision making approaches to rank service variants based on their modeled fulfillment of preferences stated in polls. Through the abstraction of polls, preference-based ranking allows non-technical decision-makers to take part in service variant selection, thus enabling participation.
 
 
This thesis presents an evaluation of the outlined concepts that consists of multiple parts. A proof-of-concept implementation and a performance evaluation of a SFM tool suite show the realizability and applicability of service feature modeling. Two use cases further assert the applicability of the approach. The first one concerns the development of public services under consideration of service variants, whose selection was driven through citizen participation. The second use case concerns the modeling and selection of Infrastructure as a Service (IaaS) configurations and their automatic consumption and usage, illustrating how service feature modeling can drive the realization of selected service variants. Finally, an empirical evaluation indicates good acceptance, expressiveness, and usefulness and interpretability of service feature modeling.
 
 
|Veranstaltungsart=Graduiertenkolloquium
 
|Veranstaltungsart=Graduiertenkolloquium
 
|Start=2014/02/12 15:45:00
 
|Start=2014/02/12 15:45:00

Aktuelle Version vom 4. Februar 2014, 10:13 Uhr

Modeling and Selection of Software Service Variants

Veranstaltungsart:
Graduiertenkolloquium




The development and delivery of software services rises the challenge to meet diverse consumer requirements and preferences. One approach to tackle this challenge is to the model, select, and realize service variants. Variants are alternative instances of a service’s design, implementation, deployment, or operation. They bear potential for participation and increased reuse of artifacts in software development, and for delivering services to diverse or changing consumer needs. Existing approaches to deal with variability from software product line engineering, however, lack desirable capabilities regarding participation, collaboration, and representation of quality attributes. Further, they need extensions to address the delivery models, artifacts, and distinct roles in services. This thesis presents service feature modeling, a novel approach consisting of a variability modeling language and a set of corresponding methods to model and select software service variants. The service feature modeling language extends standard feature modeling from software product line engineering. A typology of feature types differentiates the semantics of features with the goal to utilize service feature models (SFMs) in novel ways. Attribute types represent concerns common to multiple attributes within an SFM to reduce modeling efforts and for attribute aggregation. A novel modeling method considers SFMs to be composed by services, addressing the collaboration of experts in modeling and the integration of software services to contribute parts of an SFM. Making use of SFMs, a set of methods is flexibly combined for decision-makers to determine which variant to develop or deliver. A configuration set determination method, extending existing approaches with attribute aggregation, produces all valid service variants represented by an SFM. Determined configuration sets are narrowed down with a novel, fuzzy requirements filter. Skyline filtering, adapted from database systems, dismisses service variants that are dominated by others. Preference-based ranking applies a well-known multi-criteria decision making approach to rank service variants based on their fulfillment of preferences. Through abstractions, it aims to enable participation by involving non-technical decision-makers in service variant selection. This thesis presents an evaluation of the outlined concepts, consisting of multiple parts. A proof- of-concept implementation and a performance evaluation of a SFM tool suite show the realizability and applicability of service feature modeling, including collaborative modeling and all outlined us- age methods. A first use case concerns the development of public services under consideration of service variants, whose selection was driven by citizen participation. A second use case concerns the modeling and selection of Infrastructure as a Service (IaaS) configurations and their automatic consumption and usage, illustrating how service feature modeling can drive the realization of selected service variants. Finally, an empirical evaluation indicates good acceptance, expressiveness, and usefulness and interpretability of service feature modeling.

(Erik Wittern)




Start: 12. Februar 2014 um 15:45
Ende: 12. Februar 2014 um 16:45


Im Gebäude 11.40, Raum: 231

Veranstaltung vormerken: (iCal)


Veranstalter: Forschungsgruppe(n) Ökonomie und Technologie der eOrganisation
Information: Media:12 2 14 Wittern.pdf