Recovering Feature-to-Code Mappings in Mixed-Variability Software Systems

Linsbauer, Lukas; Angerer, Florian; Grünbacher, Paul; Lettner, Daniela; Prähofer, Herbert; Lopez-Herrejon, Roberto E.; Egyed, Alexander

doi:10.1109/icsme.2014.67

Cited by 20 publications

(9 citation statements)

References 10 publications

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“…ECCO provides hints, for instance, to indicate that the implementation of some new modules cannot be fully automated [12,13,25]. Based on the input received manually, ECCO updates and refines its traces.…”

Section: The Human In the Loopmentioning

confidence: 99%

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Genetic Improvement for Software Product Lines

Lopez-Herrejon

Linsbauer

Assunção

et al. 2015

Proceedings of the Companion Publication of the 2015 Annual Conference on Genetic and Evolutionary Computation

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Software Product Lines (SPLs) are families of related software systems that provide different combinations of features. Extensive research and application attest to the significant economical and technological benefits of employing SPL practices. However, there are still several challenges that remain open. Salient among them is reverse engineering SPLs from existing variants of software systems and their subsequent evolution. In this paper, we aim at sketching connections between research on these open SPL challenges and ongoing work on Genetic Improvement. Our hope is that by drawing such connections we can spark the interest of both research communities on the exciting synergies at the intersection of these subject areas.

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Section: The Human In the Loopmentioning

confidence: 99%

“…We now describe this form of sensitivity analysis based on our traceability work [27], which is part of our Extraction and Composition for Clone-and-Own (ECCO) approach [12,13,25]. ECCO works under two simple premises.…”

Section: Feature-level Functional Sensitivity Analysismentioning

confidence: 99%

Genetic Improvement for Software Product Lines

Lopez-Herrejon

Linsbauer

Assunção

et al. 2015

Proceedings of the Companion Publication of the 2015 Annual Conference on Genetic and Evolutionary Computation

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“…Other employed terminology is less generic and they specifically refers to the concrete artefact types that they are dealing with. Linsbauer et al [62] and Salman et al [34] refer to blocks as potential feature-to-code mappings or traces. AL-msie'deen et al call them object-oriented building elements sets [63] and atomic blocks [64].…”

Section: Related Workmentioning

confidence: 99%

Feature location benchmark for extractive software product line adoption research using realistic and synthetic Eclipse variants

Martínez

Ziadi

Papadakis

et al. 2018

Information and Software Technology

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Context: It is common belief that high impact research in software reuse requires assessment in non-trivial, comparable, and reproducible settings. However, software artefacts and common representations are usually unavailable. Also, establishing a representative ground truth is a challenging and debatable subject. Feature location in the context of software families, which is key for software product line adoption, is a research field that is becoming more mature with a high proliferation of techniques. Objective: We present EFLBench, a benchmark and a framework to provide a common ground for the evaluation of feature location techniques in families of systems. Method: EFLBench leverages the efforts made by the Eclipse Community which provides feature-based family artefacts and their plugin-based implementations. Eclipse is an active and non-trivial project and thus, it establishes an unbiased ground truth which is realistic and challenging. Results: EFLBench is publicly available and supports all tasks for feature location techniques integration, benchmark construction and benchmark usage. We demonstrate its usage, simplicity and reproducibility by comparing four techniques in Eclipse releases. As an extension of our previously published work, we consider a decade of Eclipse releases and we also contribute an approach to automatically generate synthetic Eclipse variants to benchmark feature location techniques in tailored settings. We present and discuss three strategies for this automatic generation and we present the results using different settings. Conclusion: EFLBench is a contribution to foster the research in feature location in families of systems providing a common framework and a set of baseline techniques and results.

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“…Our previous work presented a framework and workflow that combines extraction and composition support for clone-andown [15]. Also, we have applied our extraction work to a mixed-variability system from industry [24]. In this type of system, variability is realized in multiple artifact types and with several variability techniques, for example at compile time using custom configuration tools or preprocessors, or during runtime via configuration files.…”

Section: Related Workmentioning

confidence: 99%

“…Unfortunately, while every SPL has inherent variability, the information about it is often not explicitly available as many SPLs are the result of ad hoc development. Variability information can be spread out across several places and implemented using various different techniques like preprocessors, configuration files, runtime constructs, and hidden in custom product line configuration tools [24].…”

Section: Introductionmentioning

confidence: 99%

Variability extraction and modeling for product variants

Linsbauer

Lopez-Herrejon

Egyed

2018

Proceedings of the 22nd International Systems and Software Product Line Conference - Volume 1

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Fast-changing hardware and software technologies in addition to larger and more specialized customer bases demand software tailored to meet very diverse requirements. Software development approaches that aim at capturing this diversity on a single consolidated platform often require large upfront investments, e.g., time or budget. Alternatively, companies resort to developing one variant of a software product at a time by reusing as much as possible from already-existing product variants. However, identifying and extracting the parts to reuse is an error-prone and inefficient task compounded by the typically large number of product variants. Hence, more disciplined and systematic approaches are needed to cope with the complexity of developing and maintaining sets of product variants. Such approaches require detailed information about the product variants, the features they provide and their relations. In this paper, we present an approach to extract such variability information from product variants. It identifies traces from features and feature interactions to their implementation artifacts, and computes their dependencies. This work can be useful in many scenarios ranging from ad hoc development approaches such as cloneand-own to systematic reuse approaches such as software product lines. We applied our variability extraction approach to six case studies and provide a detailed evaluation. The Communicated by Prof. results show that the extracted variability information is consistent with the variability in our six case study systems given by their variability models and available product variants.

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Recovering Feature-to-Code Mappings in Mixed-Variability Software Systems

Cited by 20 publications

References 10 publications

Genetic Improvement for Software Product Lines

Genetic Improvement for Software Product Lines

Feature location benchmark for extractive software product line adoption research using realistic and synthetic Eclipse variants

Variability extraction and modeling for product variants

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