Efficient Verification of Evolving Software Product Lines

Sabouri, Hamideh; Khosravi, Ramtin

doi:10.1007/978-3-642-29320-7_24

Cited by 4 publications

(7 citation statements)

References 7 publications

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“…The majority of approaches for family-based model checking apply abstract model checking. Abstract models have been defined using I/O automata , labeled transition systems Sabouri and Khosravi 2012;ter Beek et al 2013;Sabouri and Khosravi 2014], modal transition systems Asirelli et al 2012], featured transition systems Cordy et al 2012a;Cordy et al 2012b;Classen et al 2013;Sabouri and Khosravi 2013a;Cordy et al 2013b;Cordy et al 2013a;Classen et al 2014], featured timed automata , modal sequence diagrams , and actor models [Sabouri and Khosravi 2013b]. In contrast, several authors proposed approaches for family-based software model checking.…”

Section: Family-based Model Checkingmentioning

confidence: 99%

“…Most approaches are based on computation tree logic (CTL) Greenyer et al 2013;Classen et al 2013;Cordy et al 2013a;Classen et al 2014] or linear temporal logic (LTL) Schaefer et al 2010;Cordy et al 2012b;ter Beek et al 2013;Sabouri and Khosravi 2013b;. Gruler et al [2008] and Sabouri and Khosravi [2012] use the µ-calculus as a generalization of CTL and LTL. Cordy et al [2012c] rely on timed CTL, an extension of CTL with support for modeling real-time properties.…”

Section: Family-based Model Checkingmentioning

confidence: 99%

“…These specification techniques have been lifted to product lines using different strategies. The surveyed approaches use domain-independent [Post and Sinz 2008;Sabouri and Khosravi 2013a], family-wide Gruler et al 2008;Schaefer et al 2010;Sabouri and Khosravi 2012;Cordy et al 2012c;Greenyer et al 2013;ter Beek et al 2013;Sabouri and Khosravi 2013b;, feature-based Classen et al 2010;Apel et al 2011;Apel et al 2013c], and family-based specifications Cordy et al 2012a;Cordy et al 2012b;Classen et al 2013;Cordy et al 2013a;Cordy et al 2013b;Classen et al 2014].…”

Section: Family-based Model Checkingmentioning

confidence: 99%

“…First, we found that, in almost all studies, a particular strategy is compared to an unoptimized product-based analysis Schaefer et al 2010;Cordy et al 2012a;Cordy et al 2012c;Sabouri and Khosravi 2012;Greenyer et al 2013;Apel et al 2013c;Classen et al 2013;Sabouri and Khosravi 2013a;Classen et al 2013;Sabouri and Khosravi 2013b;Classen et al 2014;Chen et al 2014] or to the analysis of a single product [Post and Sinz 2008;Delaware et al 2009;Kenner et al 2010;Kästner et al 2011;Kästner et al 2012a;Gazzillo and Grimm 2012]. The advantage of such a standard evaluation is that we can compare different approaches more easily; even if evaluations strongly depend on the size and kind of product line being analyzed.…”

Section: Quantitative Evaluation Of Analysis Strategiesmentioning

confidence: 99%

“…In contrast, family-based type checking does not require to retrieve all valid configurations nor to generate products. Brabrand et al [2013] and Kolesnikov et al [2013] document the performance of each analysis step, while all other empirical comparisons ignore variability-model analysis and product generation [Post and Sinz 2008;Classen et al 2010;Schaefer et al 2010;Delaware et al 2011;Kästner et al 2011;Apel et al 2011;Kästner et al 2012a;Gazzillo and Grimm 2012;Cordy et al 2012a;Cordy et al 2012c;Sabouri and Khosravi 2012;Apel et al 2013c;Liebig et al 2013;Classen et al 2013;Sabouri and Khosravi 2013b;Chen et al 2014;Classen et al 2014]. Especially, sampling may require a considerable amount of time [Liebig et al 2013].…”

Section: Quantitative Evaluation Of Analysis Strategiesmentioning

confidence: 99%

See 4 more Smart Citations

A Classification and Survey of Analysis Strategies for Software Product Lines

et al. 2014

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Software-product-line engineering has gained considerable momentum in the recent years, both in industry and in academia. A software product line is a family of software products that share a common set of features. Software product lines challenge traditional analysis techniques, such as type checking, model checking, and theorem proving, in their quest of ensuring correctness and reliability of software. Simply creating and analyzing all products of a product line is usually not feasible, due to the potentially exponential number of valid feature combinations. Recently, researchers began to develop analysis techniques that take the distinguishing properties of software product lines into account, for example, by checking feature-related code in isolation or by exploiting variability information during analysis. The emerging field of product-line analyses is both broad and diverse, so it is difficult for researchers and practitioners to understand their similarities and differences. We propose a classification of product-line analyses to enable systematic research and application. Based on our insights with classifying and comparing a corpus of 123 research articles, we develop a research agenda to guide future research on product-line analyses.

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Section: Family-based Model Checkingmentioning

confidence: 99%

Section: Family-based Model Checkingmentioning

confidence: 99%

Section: Family-based Model Checkingmentioning

confidence: 99%

Section: Quantitative Evaluation Of Analysis Strategiesmentioning

confidence: 99%

Section: Quantitative Evaluation Of Analysis Strategiesmentioning

confidence: 99%

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A Classification and Survey of Analysis Strategies for Software Product Lines

et al. 2014

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Incremental software product line verification - A performance analysis with dead variable code

et al. 2022

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Verification approaches for Software Product Lines (SPL) aim at detecting variability-related defects and inconsistencies. In general, these analyses take a significant amount of time to provide complete results for an entire, complex SPL. If the SPL evolves, these results potentially become invalid, which requires a time-consuming re-verification of the entire SPL for each increment. However, in previous work we showed that variability-related changes occur rather infrequently and typically only affect small parts of a SPL. In this paper, we utilize this observation and present an incremental dead variable code analysis as an example for incremental SPL verification, which achieves significant performance improvements. It explicitly considers changes and partially updates its previous results by re-verifying changed artifacts only. We apply this approach to the Linux kernel demonstrating that our fastest incremental strategy takes only 3.20 seconds or less for most of the changes, while the non-incremental approach takes 1,020 seconds in median. We also discuss the impact of different variants of our strategy on the overall performance, providing insights into optimizations that are worthwhile.

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Efficient software product-line model checking using induction and a SAT solver

Gao

Yin

2018

Front. Comput. Sci.

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Efficient Verification of Evolving Software Product Lines

Cited by 4 publications

References 7 publications

A Classification and Survey of Analysis Strategies for Software Product Lines

A Classification and Survey of Analysis Strategies for Software Product Lines

Incremental software product line verification - A performance analysis with dead variable code

Efficient software product-line model checking using induction and a SAT solver

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