1,720,978 research outputs found
Verification of migrated product lines
No full textMaintaining several code bases (e.g., clones) of software variants in an application domain remains a widespread development practice, though costly and error-prone. Despite the many benefits that come with using the product-line approach, many companies are hesitant to migrate to an integrated platform for their product variants because such a migration is considered challenging and risky. Often this perception is because the migration is seen as a drastic change that is not easy to verify and assure developers that the migrated products still operate as before. In this research we propose to develop a language structure (or abstract representation) of artifacts in a software asset base that would facilitate an incremental migration of several code bases to an integrated platform. We further seek to propose and evaluate techniques for verifying the migrated product line with respect to its original code bases
Understanding Variability-Aware Analysis in Low-Maturity Variant-Rich Systems
Get PDFContext: Software systems often exist in many variants to support varying stakeholder requirements, such as specific market segments or hardware constraints. Systems with many variants (a.k.a. variant-rich systems) are highly complex due to the variability introduced to support customization. As such, assuring the quality of these systems is also challenging since traditional single-system analysis techniques do not scale when applied. To tackle this complexity, several variability-aware analysis techniques have been conceived in the last two decades to assure the quality of a branch of variant-rich systems called software product lines. Unfortunately, these techniques find little application in practice since many organizations do use product-line engineering techniques, but instead rely on low-maturity \clo~strategies to manage their software variants. For instance, to perform an analysis that checks that all possible variants that can be configured by customers (or vendors) in a car personalization system conform to specified performance requirements, an organization needs to explicitly model system variability. However, in low-maturity variant-rich systems, this and similar kinds of analyses are challenging to perform due to (i) immature architectures that do not systematically account for variability, (ii) redundancy that is not exploited to reduce analysis effort, and (iii) missing essential meta-information, such as relationships between features and their implementation in source code.Objective: The overarching goal of the PhD is to facilitate quality assurance in low-maturity variant-rich systems. Consequently, in the first part of the PhD (comprising this thesis) we focus on gaining a better understanding of quality assurance needs in such systems and of their properties.Method: Our objectives are met by means of (i) knowledge-seeking research through case studies of open-source systems as well as surveys and interviews with practitioners; and (ii) solution-seeking research through the implementation and systematic evaluation of a recommender system that supports recording the information necessary for quality assurance in low-maturity variant-rich systems. With the former, we investigate, among other things, industrial needs and practices for analyzing variant-rich systems; and with the latter, we seek to understand how to obtain information necessary to leverage variability-aware analyses.Results: Four main results emerge from this thesis: first, we present the state-of-practice in assuring the quality of variant-rich systems, second, we present our empirical understanding of features and their characteristics, including information sources for locating them; third, we present our understanding of how best developers\u27 proactive feature location activities can be supported during development; and lastly, we present our understanding of how features are used in the code of non-modular variant-rich systems, taking the case of feature scattering in the Linux kernel.Future work: In the second part of the PhD, we will focus on processes for adapting variability-aware analyses to low-maturity variant-rich systems.Keywords:\ua0Variant-rich Systems, Quality Assurance, Low Maturity Software Systems, Recommender Syste
Understanding Variability-Aware Analysis in Low-Maturity Variant-Rich Systems
No full textContext: Software systems often exist in many variants to support varying stakeholder requirements, such as specific market segments or hardware constraints. Systems with many variants (a.k.a., variant-rich systems) are highly complex due to the variability introduced to support customization. As such, assuring quality of these systems is also challenging since traditional single-system analysis techniques do not scale when applied. To tackle this complexity, several variability-aware analysis techniques have been conceived in the last two decades to assure the quality of a branch of variant-rich systems called software product lines. Unfortunately, many organizations do not use product-line engineering techniques, but instead rely on low-maturity clone-and-own strategies to manage their software variants. Hence, they cannot apply the proposed analysis techniques. For instance, to perform an analysis that checks that all possible variants that can be configured by customers (or vendors) in a car personalization system conform to specified performance requirements, an organization needs to explicitly model system variability. However, in low-maturity variant-rich systems, this and similar kinds of analyses are challenging to perform due to (i) immature architectures that do not systematically account for variability, (ii) redundancy that is not exploited to reduce analysis effort, and (iii) missing essential meta-information, such as relationships between features and their implementation in source code. Objective: The overarching goal of the PhD is to facilitate quality assurance in low-maturity variant-rich systems. Consequently, in the first part of the PhD (comprising this thesis) we focus on gaining a better understanding of quality assurance needs in such systems and of their properties. Method: Our objectives are met by means of (i) knowledge-seeking research through case studies of open-source systems as well as surveys and interviews with practitioners; and (ii) solution-seeking research through the implementation and systematic evaluation of a recommender system that supports recording the information necessary for quality assurance in low-maturity variant-rich systems. With the former, we investigate, among other things, industrial needs and practices for analyzing variant-rich systems; and with the latter, we seek to understand how to obtain information necessary to leverage variability-aware analyses. Results and Conclusions: Four main results emerge from this thesis: first, we present the state-of-practice in assuring the quality of variant-rich systems, second, we present our empirical understanding of features and their characteristics, including information sources for locating them; third, we present our understanding of how best developers' proactive feature location activities can be supported during development; and lastly, we present our understanding of how features are used in the code of non-modular variant-rich systems, taking the case of feature scattering in the Linux kernel. Future work: In the second part of the PhD, we will focus on processes for adapting variability-aware analyses to low-maturity variant-rich systems
Facilitating Feature-Oriented Quality Assurance in Low-Maturity Variant-rich Systems
No full textContext: Many software systems exist in several variants customized for specific stakeholder requirements, such as different market segments or hardware constraints. This customization introduces a high level of complexity that renders traditional single-system quality assurance techniques inapplicable, since they need to consider variations and constraints between a system’s features—a.k.a feature-oriented or variability-aware analysis. While several analysis techniques have been conceived in the last two decades for this purpose, they mostly target a branch of variant-rich systems called software product lines, and are less applicable to systems that still rely on cloning strategies to engineer variants—a.k.a low-maturity variant-rich systems. Among other reasons, this is because such systems exhibit: immature architectures that do not systematically account for variability, redundancy that is not exploited to reduce analysis effort, and missing essential meta-information such as feature constraints and locations of features in source code. Objective: This research aims to facilitate quality assurance in low-maturity variant-rich systems. Through analysis of the state-of-practice, we propose techniques that can improve maturity and help developers of such systems mitigate some challenges posed by redundancy. Method: First, we conducted a survey and interviews with practitioners to identify industrial needs and practices for analyzing variant-rich systems, followed by a case study of some open source systems to understand where developers record information necessary for feature-oriented analysis. Then, we designed and systematically evaluated a technique and a tool that can improve the maturity of variant rich systems by supporting feature recording, and two techniques that can reduce analysis effort. Results: Our results stem from two main contributions: our analysis of the state-of-practice and techniques we propose for improving maturity to facilitate feature-oriented analysis in low-maturity variant-rich systems. For the former, we present results of a survey and interviews targeting 27 practitioners from 18 companies in 8 countries to understand industrial practices and needs for analyzing variant-rich systems. Then, we present our empirical understanding of features and their characteristics (facets) based on a case study of two industrial open-source systems. For the latter, we present design decisions and an evaluation of a tool and technique that help developers proactively and continuously record features. Then, we present empirical data on the potential of two techniques for reducing QA effort: one for predicting software defects at the level of features (evaluated on 13 open-source systems), and another for propagating test cases across forked projects, i.e., projects with similar but cloned features (evaluated on over 426,000 test cases from 2,153 projects). Conclusion: This thesis identifies the lack of adoption of feature-oriented quality assurance techniques in industry, and addresses the problem through tools and techniques for feature recording and quality assurance effort reduction
Facilitating Feature-Oriented Quality Assurance in Low-Maturity Variant-rich Systems
No full textContext: Many software systems exist in several variants customized for specific stakeholder requirements, such as different market segments or hardware constraints. This customization introduces a high level of complexity that renders traditional single-system quality assurance techniques inapplicable, since they need to consider variations and constraints between a system’s features—a.k.a feature-oriented or variability-aware analysis. While several analysis techniques have been conceived in the last two decades for this purpose, they mostly target a branch of variant-rich systems called software product lines, and are less applicable to systems that still rely on cloning strategies to engineer variants—a.k.a low-maturity variant-rich systems. Among other reasons, this is because such systems exhibit: immature architectures that do not systematically account for variability, redundancy that is not exploited to reduce analysis effort, and missing essential meta-information such as feature constraints and locations of features in source code.
Objective: This research aims to facilitate quality assurance in low-maturity variant-rich systems. Through analysis of the state-of-practice, we propose techniques that can improve maturity and help developers of such systems mitigate some challenges posed by redundancy.
Method: First, we conducted a survey and interviews with practitioners to identify industrial needs and practices for analyzing variant-rich systems, followed by a case study of some open source systems to understand where developers record information necessary for feature-oriented analysis. Then, we designed and systematically evaluated a technique and a tool that can improve the maturity of variant rich systems by supporting feature recording, and two techniques that can reduce analysis effort.
Results: Our results stem from two main contributions: our analysis of the state-of-practice and techniques we propose for improving maturity to facilitate feature-oriented analysis in low-maturity variant-rich systems. For the former, we present results of a survey and interviews targeting 27 practitioners from 18 companies in 8 countries to understand industrial practices and needs for analyzing variant-rich systems. Then, we present our empirical understanding of features and their characteristics (facets) based on a case study of two industrial open-source systems. For the latter, we present design decisions and an evaluation of a tool and technique that help developers proactively and continuously record features. Then, we present empirical data on the potential of two techniques for reducing QA effort: one for predicting software defects at the level of features (evaluated on 13 open-source systems), and another for propagating test cases across forked projects, i.e., projects with similar but cloned features (evaluated on over 426,000 test cases from 2,153 projects).
Conclusion: This thesis identifies the lack of adoption of feature-oriented quality assurance techniques in industry, and addresses the problem through tools and techniques for feature recording and quality assurance effort reduction
Understanding Variability-Aware Analysis in Low-Maturity Variant-Rich Systems [Elektronisk resurs]
No full textContext : Software systems often exist in many variants to support varying stakeholder requirements, such as specific market segments or hardware constraints. Systems with many variants (a.k.a. variant-rich systems) are highly complex due to the variability introduced to support customization. As such, assuring the quality of these systems is also challenging since traditional single-system analysis techniques do not scale when applied. To tackle this complexity, several variability-aware analysis techniques have been conceived in the last two decades to assure the quality of a branch of variant-rich systems called software product lines. Unfortunately, these techniques find little application in practice since many organizations do use product-line engineering techniques, but instead rely on low-maturity \clo~strategies to manage their software variants. For instance, to perform an analysis that checks that all possible variants that can be configured by customers (or vendors) in a car personalization system conform to specified performance requirements, an organization needs to explicitly model system variability. However, in low-maturity variant-rich systems, this and similar kinds of analyses are challenging to perform due to (i) immature architectures that do not systematically account for variability, (ii) redundancy that is not exploited to reduce analysis effort, and (iii) missing essential meta-information, such as relationships between features and their implementation in source code. Objective : The overarching goal of the PhD is to facilitate quality assurance in low-maturity variant-rich systems. Consequently, in the first part of the PhD (comprising this thesis) we focus on gaining a better understanding of quality assurance needs in such systems and of their properties. Method : Our objectives are met by means of (i) knowledge-seeking research through case studies of open-source systems as well as surveys and interviews with practitioners; and (ii) solution-seeking research through the implementation and systematic evaluation of a recommender system that supports recording the information necessary for quality assurance in low-maturity variant-rich systems. With the former, we investigate, among other things, industrial needs and practices for analyzing variant-rich systems; and with the latter, we seek to understand how to obtain information necessary to leverage variability-aware analyses. Results : Four main results emerge from this thesis: first, we present the state-of-practice in assuring the quality of variant-rich systems, second, we present our empirical understanding of features and their characteristics, including information sources for locating them; third, we present our understanding of how best developers' proactive feature location activities can be supported during development; and lastly, we present our understanding of how features are used in the code of non-modular variant-rich systems, taking the case of feature scattering in the Linux kernel. Future work : In the second part of the PhD, we will focus on processes for adapting variability-aware analyses to low-maturity variant-rich systems. Keywords : Variant-rich Systems, Quality Assurance, Low Maturity Software Systems, Recommender Syste
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
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