Efficient Product-Line Testing Using Cluster-Based Product Prioritization

Mustafa Al-Hajjaji; Jacob Krüger; Sandro Schulze; Thomas Leich; Gunter Saake

doi:10.1109/AST.2017.7

Efficient Product-Line Testing Using Cluster-Based Product Prioritization

Mustafa Al-Hajjaji, Jacob Krüger, Sandro Schulze, Thomas Leich, Gunter Saake

Engineering of Software-Intensive Systems

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/Congresprocedure › Conferentiebijdrage › Academic › peer review

9 Citaten (Scopus)

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A software product-line comprises a set of products that share a common set of features. These features can be reused to customize a product to satisfy specific needs of certain customers or markets. As the number of possible products increases exponentially for new features, testing all products is infeasible. Existing testing approaches reduce their effort by restricting the number of products (sampling) and improve their effectiveness by considering the order of tests (prioritization). In this paper, we propose a cluster-based prioritization technique to sample similar products with respect to the feature selection. We evaluate our approach using feature models of different sizes and show that cluster-based prioritization can enhance the effectiveness of product-line testing.

Originele taal-2	Engels
Titel	International Workshop on Automation of Software Test (AST)
Uitgeverij	IEEE Press
Pagina's	16-22
Aantal pagina's	7
DOI's	https://doi.org/10.1109/AST.2017.7
Status	Gepubliceerd - 2017

Bibliografische nota

DBLP License: DBLP's bibliographic metadata records provided through http://dblp.org/ are distributed under a Creative Commons CC0 1.0 Universal Public Domain Dedication. Although the bibliographic metadata records are provided consistent with CC0 1.0 Dedication, the content described by the metadata records is not. Content may be subject to copyright, rights of privacy, rights of publicity and other restrictions.

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title = "Efficient Product-Line Testing Using Cluster-Based Product Prioritization",

abstract = "A software product-line comprises a set of products that share a common set of features. These features can be reused to customize a product to satisfy specific needs of certain customers or markets. As the number of possible products increases exponentially for new features, testing all products is infeasible. Existing testing approaches reduce their effort by restricting the number of products (sampling) and improve their effectiveness by considering the order of tests (prioritization). In this paper, we propose a cluster-based prioritization technique to sample similar products with respect to the feature selection. We evaluate our approach using feature models of different sizes and show that cluster-based prioritization can enhance the effectiveness of product-line testing.",

author = "Mustafa Al-Hajjaji and Jacob Kr{\"u}ger and Sandro Schulze and Thomas Leich and Gunter Saake",

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AU - Krüger, Jacob

AU - Schulze, Sandro

AU - Leich, Thomas

AU - Saake, Gunter

N1 - DBLP License: DBLP's bibliographic metadata records provided through http://dblp.org/ are distributed under a Creative Commons CC0 1.0 Universal Public Domain Dedication. Although the bibliographic metadata records are provided consistent with CC0 1.0 Dedication, the content described by the metadata records is not. Content may be subject to copyright, rights of privacy, rights of publicity and other restrictions.

PY - 2017

Y1 - 2017

N2 - A software product-line comprises a set of products that share a common set of features. These features can be reused to customize a product to satisfy specific needs of certain customers or markets. As the number of possible products increases exponentially for new features, testing all products is infeasible. Existing testing approaches reduce their effort by restricting the number of products (sampling) and improve their effectiveness by considering the order of tests (prioritization). In this paper, we propose a cluster-based prioritization technique to sample similar products with respect to the feature selection. We evaluate our approach using feature models of different sizes and show that cluster-based prioritization can enhance the effectiveness of product-line testing.

AB - A software product-line comprises a set of products that share a common set of features. These features can be reused to customize a product to satisfy specific needs of certain customers or markets. As the number of possible products increases exponentially for new features, testing all products is infeasible. Existing testing approaches reduce their effort by restricting the number of products (sampling) and improve their effectiveness by considering the order of tests (prioritization). In this paper, we propose a cluster-based prioritization technique to sample similar products with respect to the feature selection. We evaluate our approach using feature models of different sizes and show that cluster-based prioritization can enhance the effectiveness of product-line testing.

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DO - 10.1109/AST.2017.7

M3 - Conference contribution

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BT - International Workshop on Automation of Software Test (AST)

PB - IEEE Press

ER -

Efficient Product-Line Testing Using Cluster-Based Product Prioritization

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