DIRECTDEBUG: A software package for the automated testing and debugging of feature models

Viet-Man Le; Alexander Felfernig; Thi Ngoc Trang Tran; Müslüm Atas; Mathias Uta; David Benavides; José Galindo

doi:10.1016/j.simpa.2021.100085

DIRECTDEBUG: A software package for the automated testing and debugging of feature models

Viet-Man Le, Alexander Felfernig, Thi Ngoc Trang Tran, Müslüm Atas, Mathias Uta, David Benavides, José Galindo

Institute of Software Technology (7160)

Research output: Contribution to journal › Article › peer-review

Abstract

Complex and large-scale feature models can become faulty, i.e., do not represent the expected variability properties of the underlying software artifact. In this paper, we propose the DirectDebug algorithm that supports the automated testing and debugging of variability models. Our approach assists software engineers in identifying an adaptation hint (diagnosis) that makes all test cases consistent with the knowledge base. We also develop the software package so-called d2bug_eval to evaluate the DirectDebug’s performance. The software package can be re-produced thoroughly to evaluate consistency-based algorithms.

Original language	English
Article number	100085
Number of pages	4
Journal	Software Impacts
Volume	9
DOIs	https://doi.org/10.1016/j.simpa.2021.100085
Publication status	Published - Aug 2021

Keywords

Automated testing and debugging
Conflict detection
Diagnosis
Feature models
Variability models

ASJC Scopus subject areas

Software

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10.1016/j.simpa.2021.100085Licence: CC BY-NC-ND 4.0

Cite this

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title = "DIRECTDEBUG: A software package for the automated testing and debugging of feature models",

abstract = "Complex and large-scale feature models can become faulty, i.e., do not represent the expected variability properties of the underlying software artifact. In this paper, we propose the DirectDebug algorithm that supports the automated testing and debugging of variability models. Our approach assists software engineers in identifying an adaptation hint (diagnosis) that makes all test cases consistent with the knowledge base. We also develop the software package so-called d2bug_eval to evaluate the DirectDebug{\textquoteright}s performance. The software package can be re-produced thoroughly to evaluate consistency-based algorithms.",

keywords = "Automated testing and debugging, Conflict detection, Diagnosis, Feature models, Variability models",

author = "Viet-Man Le and Alexander Felfernig and Tran, {Thi Ngoc Trang} and M{\"u}sl{\"u}m Atas and Mathias Uta and David Benavides and Jos{\'e} Galindo",

year = "2021",

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doi = "10.1016/j.simpa.2021.100085",

language = "English",

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T2 - A software package for the automated testing and debugging of feature models

AU - Le, Viet-Man

AU - Felfernig, Alexander

AU - Tran, Thi Ngoc Trang

AU - Atas, Müslüm

AU - Uta, Mathias

AU - Benavides, David

AU - Galindo, José

PY - 2021/8

Y1 - 2021/8

N2 - Complex and large-scale feature models can become faulty, i.e., do not represent the expected variability properties of the underlying software artifact. In this paper, we propose the DirectDebug algorithm that supports the automated testing and debugging of variability models. Our approach assists software engineers in identifying an adaptation hint (diagnosis) that makes all test cases consistent with the knowledge base. We also develop the software package so-called d2bug_eval to evaluate the DirectDebug’s performance. The software package can be re-produced thoroughly to evaluate consistency-based algorithms.

AB - Complex and large-scale feature models can become faulty, i.e., do not represent the expected variability properties of the underlying software artifact. In this paper, we propose the DirectDebug algorithm that supports the automated testing and debugging of variability models. Our approach assists software engineers in identifying an adaptation hint (diagnosis) that makes all test cases consistent with the knowledge base. We also develop the software package so-called d2bug_eval to evaluate the DirectDebug’s performance. The software package can be re-produced thoroughly to evaluate consistency-based algorithms.

KW - Automated testing and debugging

KW - Conflict detection

KW - Diagnosis

KW - Feature models

KW - Variability models

UR - https://doi.org/10.1016/j.simpa.2021.100085

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DO - 10.1016/j.simpa.2021.100085

M3 - Article

VL - 9

JO - Software Impacts

JF - Software Impacts

M1 - 100085

ER -

DIRECTDEBUG: A software package for the automated testing and debugging of feature models

Abstract

Keywords

ASJC Scopus subject areas

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