Reverse engineering language product lines from existing DSL variants

Méndez-Acuña, David; Galindo, José; Combemale, Benôıt; Blouin, Arnaud; Baudry, Benoît

doi:10.1016/j.jss.2017.05.042

Cited by 17 publications

(9 citation statements)

References 43 publications

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“…DSLs can be modeled as a family of languages rather than stand-alone monolithic implementations when developed in a LPL fashion. For instance, several works (Tratt 2008;Crane and Dingel 2005;Vacchi et al 2013;Méndez-Acuña et al 2017) showed that the variants of state machine languages can be modeled as a single family of programming (Cazzola and Poletti 2010). Each sub-tree models the variability of a different language construct.…”

Section: Language Product Linesmentioning

confidence: 99%

Towards a recipe for language decomposition: quality assessment of language product lines

Cazzola

Favalli

2022

Empir Software Eng

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Programming languages are complex systems that are usually implemented as monolithic interpreters and compilers. In recent years, researchers and practitioners gained interest in product line engineering to improve the reusability of language assets and the management of variability-rich systems, introducing the notions of language workbenches and language product lines (LPLs). Nonetheless, language development remains a complex activity and design or implementation flaws can easily waste the efforts of decomposing a language specification into language features. Poorly designed language decompositions result in high inter-dependent components, reducing the variability space of the LPL system and its maintainability. One should detect and fix the design flaws posthaste to prevent these risks while minimizing the development overhead. Therefore, various aspects of the quality of a language decomposition should be quantitatively measurable through adequate metrics. The evaluation, analysis and feedback of these measures should be a primary part of the engineering process of a LPL. In this paper, we present an exploratory study trying to capture these aspects by introducing a design methodology for LPLs; we define the properties of a good language decomposition and adapt a set of metrics from the literature to the framework of language workbenches. Moreover, we leverage the LPL engineering environment to perform an empirical evaluation of 26 -based LPLs based on this design methodology. Our contributions form the foundations of a design methodology for -based LPLs. This methodology is comprised of four different elements: i) an engineering process that defines the order in which decisions are made, ii) an integrated development environment for LPL designers and iii) some best practices in the design of well-structured language decomposition when using , supported by iv) a variety of LPL metrics that can be used to detect errors in design decisions.

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Section: Language Product Linesmentioning

confidence: 99%

Towards a recipe for language decomposition: quality assessment of language product lines

Cazzola

Favalli

2022

Empir Software Eng

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“…An approach [49] is presented to extracting complex feature correlations from existing product configurations using association mining techniques. In [33] a reverse engineering technique is proposed to automatically build up language product lines from exiting DSL variants. [13] provides approach to mine a feature model based on the formal conceptual models and configurations.…”

Section: Related Workmentioning

confidence: 99%

Amadeus

Varela-Vaca

Gasca

Carmona-Fombella

et al. 2020

Proceedings of the 24th ACM Conference on Systems and Software Product Line: Volume a - Volume A

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The proper configuration of systems has become a fundamental factor to avoid cybersecurity risks. Thereby, the analysis of cybersecurity vulnerabilities is a mandatory task, but the number of vulnerabilities and system configurations that can be threatened is extremely high. In this paper, we propose a method that uses software product line techniques to analyse the vulnerable configuration of the systems. We propose a solution, entitled AMADEUS, to enable and support the automatic analysis and testing of cybersecurity vulnerabilities of configuration systems based on feature models. AMADEUS is a holistic solution that is able to automate the analysis of the specific infrastructures in the organisations, the existing vulnerabilities, and the possible configurations extracted from the vulnerability repositories. By using this information, AMADEUS generates automatically the feature models, that are used for reasoning capabilities to extract knowledge, such as to determine attack vectors with certain features. AMADEUS has been validated by demonstrating the capacities of feature models to support the threat scenario, in which a wide variety of vulnerabilities extracted from a real repository are involved. Furthermore, we open the door to new applications where software product line engineering and cybersecurity can be empowered. CCS CONCEPTS• Software and its engineering → Software product lines.␣

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“…Similarly, paper [15] proposed a feature-oriented approach to automatically mine legacy system models via comparing, matching and merging artifacts. Recently, [16] proposed an approach that reuses Domain Specific Languages models and synthesizes with the corresponding OVM variability model. K. Czarnecki et al [17] proposed a feature models mining method based on conjunctive and disjunctive association rule mining.…”

Section: A Current Advances In Splementioning

confidence: 99%

A Product Line Systems Engineering Process for Variability Identification and Reduction

Grigg

Dickerson

et al. 2019

IEEE Systems Journal

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Software Product Line Engineering has attracted attention in the last two decades due to its promising capabilities to reduce costs and time to market through reuse of requirements and components. In practice, developing system level product lines in a large-scale company is not an easy task as there may be thousands of variants and multiple disciplines involved. The manual reuse of legacy system models at domain engineering to build reusable system libraries and configurations of variants to derive target products can be infeasible. To tackle this challenge, a Product Line Systems Engineering process is proposed. Specifically, the process extends research in the System Orthogonal Variability Model to support hierarchical variability modeling with formal definitions; utilizes Systems Engineering concepts and legacy system models to build the hierarchy for the variability model and to identify essential relations between variants; and finally, analyzes the identified relations to reduce the number of variation points. The process, which is automated by computational algorithms, is demonstrated through an illustrative example on generalized Rolls-Royce aircraft engine control systems. To evaluate the effectiveness of the process in the reduction of variation points, it is further applied to case studies in different engineering domains at different levels of complexity. Subject to system model availability, reduction of 14% to 40% in the number of variation points are demonstrated in the case studies.

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Reverse engineering language product lines from existing DSL variants

Cited by 17 publications

References 43 publications

Towards a recipe for language decomposition: quality assessment of language product lines

Towards a recipe for language decomposition: quality assessment of language product lines

Amadeus

A Product Line Systems Engineering Process for Variability Identification and Reduction

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