Experimenting with the Comprehension of Feature-Oriented and UML-Based Core Assets

Reinhartz-Berger, Iris; Tsoury, Arava

doi:10.1007/978-3-642-21759-3_34

Cited by 9 publications

(6 citation statements)

References 17 publications

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“…Conducting two experiments, Tsoury and Reinhartz-Berger [16,17] compared the comprehensibility of Cardinality-Based Feature Modeling (CBFM) [18] and Application-based DOmain Modeling (ADOM) [19]. The comparison is based on comprehensibility of commonality-and variability-related concepts, including mandatory and optional elements, dependencies, variation points and variants.…”

Section: Comparison Of Feature Modeling Languagesmentioning

confidence: 99%

Comprehending Feature Models Expressed in CVL

Reinhartz-Berger

Figl

Haugen

2014

Lecture Notes in Computer Science

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Abstract. Feature modeling is a common way to present and manage variability of software and systems. As a prerequisite for effective variability management is comprehensible representation, the main aim of this paper is to investigate difficulties in understanding feature models. In particular, we focus on the comprehensibility of feature models as expressed in Common Variability Language (CVL), which was recommended for adoption as a standard by the Architectural Board of the Object M anagement Group . Using an experimental approach with participants familiar and unfamiliar with feature modeling, we analyzed comprehensibility in terms of comprehension score, time spent to complete tasks, and perceived difficulty of different feature modeling constructs. The results showed that familiarity with feature modeling did not influence the comprehension of mandatory, optional, and alternative features, although unfamiliar modelers perceived these elements more difficult than familiar modelers. OR relations were perceived as difficult regardless of the familiarity level, while constraints were significantly better understood by familiar modelers. The time spent to complete tasks was higher for familiar modelers.

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Section: Comparison Of Feature Modeling Languagesmentioning

confidence: 99%

Comprehending Feature Models Expressed in CVL

Reinhartz-Berger

Figl

Haugen

2014

Lecture Notes in Computer Science

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“…"A variation point identifies a location at which a variable part may occur. It locates the insertion point for the variants and determines the characteristics (attributes) of the variability" [22]. Variation points are also called extension points (e.g., [19]) or hot spots (e.g., [15]).…”

Section: A Model Based On Variation Pointsmentioning

confidence: 99%

Foundations of Coloring Algebra with Consequences for Feature-Oriented Programming

Höfner

Möller

Zelend

2012

Relational and Algebraic Methods in Computer Science

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Abstract. In 2011, simple and concise axioms for feature compositions, interactions and products have been proposed by Batory et al. They were mainly inspired by Kästner's Colored IDE (CIDE) as well as by experience in feature oriented programming over the last decades. However, so far only axioms were proposed; consequences of these axioms such as variability in models have not been studied. In this paper we discuss the proposed axioms from a theoretical point of view, which yields a much better understanding of the proposed algebra and therefore of feature oriented programming. For example, we show that the axioms characterising feature composition are isomorphic to set-theoretic models.

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“…Several works explicitly refer to dependencies between elements in the form of «alternative_or», «alternative_XOR», «requires», and «mutux» stereotypes. In order to evaluate the comprehension and utilization of variability aspects in UML-based methods and to identify factors that may affect these activities, we conducted an empirical study with a method, called Application-based DOmain Modeling (ADOM) [ 26,27]. We chose this method over other UML-based methods since it explicitly refers to extension variability and in particular to the selection and the addition of variants in certain variation points, aspects which other UML-based methods tend to neglect.…”

Section: Variability Modeling In Uml-based Methodsmentioning

confidence: 99%

Evaluating Comprehension and Utilization of Variability Aspects in UML-Based Models

Reinhartz-Berger

Sturm

Tsoury

2012

Lecture Notes in Business Information Processing

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Abstract. In Software Product Line Engineering (SPLE), the ability of a software artifact to be used in different contexts is very essential for productivity. In order to manage and support this ability, different variability modeling methods have been proposed. An important group of such methods are based on UML. These methods typically introduce profiles for specifying mandatory and optional elements, identifying dependencies between elements, and modeling variation points and possible variants. However, the assessment of these methods still lacks. In this work, we have done a first step towards evaluating the comprehension and utilization of variability issues in UMLbased models by suggesting a comparison framework which refers to different aspects of variability specification. Based on this framework, we chose a specific UML-based method -ADOM -and examined how advanced information systems students understood and utilized a model specified using this method. The results showed that the different means for specifying variability were understood and utilized only to a limited extent and that variation points were the least comprehensible variability specification means.

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Experimenting with the Comprehension of Feature-Oriented and UML-Based Core Assets

Cited by 9 publications

References 17 publications

Comprehending Feature Models Expressed in CVL

Comprehending Feature Models Expressed in CVL

Foundations of Coloring Algebra with Consequences for Feature-Oriented Programming

Evaluating Comprehension and Utilization of Variability Aspects in UML-Based Models

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