Software product line engineering and variability management: achievements and challenges

Metzger, Andreas; Pohl, Klaus

doi:10.1145/2593882.2593888

Cited by 134 publications

(94 citation statements)

References 91 publications

(124 reference statements)

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“…A software product line (SPL) [20]- [25] [41] [42] is a set of software intensive systems that share a common and managed set of features satisfying the specific needs of a particular market segment developed from a common set of core assets in a prescribed way [21] [23]. SPL engineering aims at: effective utilization of software assets, reducing the time required to deliver a product, improving quality, and decreasing the cost of software products.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Furthermore, as the requirement of SECO to support adaptation capabilities of systems is increasing in importance [20] it is recommended such adaptive features be included within software product lines (SPL) [21] [22] [23] [24]. The SPL concept is appealing to organizations dealing with software development that aims to provide a comprehensive model for an organization building applications based on a common architecture and core assets [20] [21].…”

Section: Introductionmentioning

confidence: 99%

“…The SPL concept is appealing to organizations dealing with software development that aims to provide a comprehensive model for an organization building applications based on a common architecture and core assets [20] [21].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A Semantic Metadata Enrichment Software Ecosystem (SMESE) Based on a Multi-Platform Metadata Model for Digital Libraries

Brisebois¹,

Abran²,

Nadembéga³

2017

JSEA

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Software industry has evolved to multi-product and multi-platform development based on a mix of proprietary and open source components. Such integration has occurred in software ecosystems through a software product line engineering (SPLE) process. However, metadata are underused in the SPLE and interoperability challenge. The proposed method is first, a semantic metadata enrichment software ecosystem (SMESE) to support multi-platform metadata driven applications, and second, based on mapping ontologies SMESE aggregates and enriches metadata to create a semantic master metadata catalogue (SMMC). The proposed SPLE process uses a component-based software development approach for integrating distributed content management enterprise applications, such as digital libraries. To perform interoperability between existing metadata models (such as Dublin Core, UNIMARC, MARC21, RDF/RDA and BIBFRAME), SMESE implements an ontology mapping model. SMESE consists of nine sub-systems: 1) Metadata initiatives & concordance rules; 2) Harvesting of web metadata & data; 3) Harvesting of authority metadata & data; 4) Rule-based semantic metadata external enrichment; 5) Rule-based semantic metadata internal enrichment; 6) Semantic metadata external & internal enrichment synchronization; 7) User interest-based gateway; 8) Semantic master catalogue. To conclude, this paper proposes a decision support process, called SPLE decision support process (SPLE-DSP) which is then used by SMESE to support dynamic reconfiguration. SPLE-DSP consists of a dynamic and optimized metadata-based reconfiguration model. SPLE-DSP takes into account runtime metadata-based variability functionalities, context-awareness and self-adaptation. It also presents the design and implementation of a working prototype of SMESE applied to a semantic digital library.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A Semantic Metadata Enrichment Software Ecosystem (SMESE) Based on a Multi-Platform Metadata Model for Digital Libraries

Brisebois¹,

Abran²,

Nadembéga³

2017

JSEA

View full text Add to dashboard Cite

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“…Software Product Lines (SPL) is a branch of Software Engineering that aims at designing software products based on a composition of pre-defined software artefacts, increasing the reusability and personalisation of software products [5]. Software architects, when they design new products or adapt existing products, navigate a set of features in a Feature Model (FM).…”

Section: Introductionmentioning

confidence: 99%

Preliminary Study of Multi-objective Features Selection for Evolving Software Product Lines

Brevet

Saber

Botterweck

et al. 2016

Search Based Software Engineering

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Abstract. When dealing with software-intensive systems, it is often beneficial to consider families of similar systems together. A common task is then to identify the particular product that best fulfils a given set of desired product properties. Software Product Lines Engineering (SPLE) provides techniques to design, implement and evolve families of similar systems in a systematic fashion, with variability choices explicitly represented, e.g., as Feature Models. The problem of picking the 'best' product then becomes a question of optimising the Feature Configuration. When considering multiple properties at the same time, we have to deal with multi-objective optimisation, which is even more challenging. While change and evolution of software systems is the common case, to the best of our knowledge there has been no evaluation of the problem of multi-objective optimisation of evolving Software Product Lines. In this paper we present a benchmark of large scale evolving Feature Models and we study the behaviour of the state-of-the-art algorithm (SATIBEA). In particular, we show that we can improve both the execution time and the quality of SATIBEA by feeding it with the previous configurations: our solution converges nearly 10 times faster and gets an 113% improvement after one generation of genetic algorithm.

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“…PLE publications over the last 20 years have mainly concentrated on the software domain [2][3][4][5][6], therefore PLE, as it has so far been referred to, should actually be called Software Product Line Engineering (SPLE). A well-known definition for a Software Product Line is given by [7]: "A software product line is a set of softwareintensive systems that share a common, managed set of features satisfying the specific needs of a particular market segment or mission and that are developed from a common set of core assets in a prescribed way."…”

Section: Introductionmentioning

confidence: 99%

Model-based systems product line engineering with physical design variability for aircraft systems

Guan

Dickerson

et al. 2016

2016 11th System of Systems Engineering Conference (SoSE)

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Abstract-Software Product Line Engineering (SPLE) has drawn large amounts of attention during the last two decades as it offers the benefits of reducing cost and time to market by reusing requirements and components. Recently, more and more large scale industries start to implement SPLE in their domains (combining SPLE with model-based modelling methods). However, the problem of how to combine SPLE with ModelBased System Engineering is still a challenge, as systems are much broader than the software domain. Unlike software engineering, system engineering has to consider the physical resources aspect. This paper classifies typical types of physical variability and provides general modelling solutions for each type of physical variation at the system design stage. Specifically, this approach combines a variability model with a SysML Block Definition Diagram and an Internal Block Diagram to model the contextual variability, architectural variability, connector variability, instance number variability, component variability, location variability and evolutional variability of physical designs. Variability is modelled separately to help reduce the complexity of design models. Last but not least, the proposed method is illustrated by an aircraft system case study.

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Software product line engineering and variability management: achievements and challenges

Cited by 134 publications

References 91 publications

A Semantic Metadata Enrichment Software Ecosystem (SMESE) Based on a Multi-Platform Metadata Model for Digital Libraries

A Semantic Metadata Enrichment Software Ecosystem (SMESE) Based on a Multi-Platform Metadata Model for Digital Libraries

Preliminary Study of Multi-objective Features Selection for Evolving Software Product Lines

Model-based systems product line engineering with physical design variability for aircraft systems

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