Exploring feature interactions without specifications: a controlled experiment

Soares, Larissa Rocha; Meinicke, Jens; Nadi, Sarah; Kästner, Christian; Almeida, Eduardo Santana de

doi:10.1145/3278122.3278127

Cited by 6 publications

(6 citation statements)

References 35 publications

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“…Their criteria are about the statements whose (non-)execution is necessary for the failure to be exposed/masked. Quality Assurance for Configurable Code There are various studies about variability-aware analysis for the purpose of type checking [66], [67], testing [51], [68], and control/data flow analysis [67], [69]. In addition, to improve the efficiency of the QA process, several approaches about configuration selection [70], [71] and configuration prioritization [7], [72] have been proposed.…”

Section: Related Workmentioning

confidence: 99%

A Variability Fault Localization Approach for Software Product Lines

Nguyen,

Ngo,

Nguyen

et al. 2021

Preprint

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Software fault localization is one of the most expensive, tedious, and time-consuming activities in program debugging. This activity becomes even much more challenging in Software Product Line (SPL) systems due to variability of failures. These unexpected behaviors are induced by variability faults which can only be exposed under some combinations of system features. The interaction among these features causes the failures of the system. Although localizing bugs in single-system engineering has been studied in-depth, variability fault localization in SPL systems still remains mostly unexplored. In this article, we present VARCOP, a novel and effective variability fault localization approach. For an SPL system failed by variability bugs, VARCOP isolates suspicious code statements by analyzing the overall test results of the sampled products and their source code. The isolated suspicious statements are the statements related to the interaction among the features which are necessary for the visibility of the bugs in the system. In VARCOP, the suspiciousness of each isolated statement is assessed based on both the overall test results of the products containing the statement as well as the detailed results of the test cases executed by the statement in these products. On a large public dataset of buggy SPL systems, our empirical evaluation shows that VARCOP significantly improves two state-of-the-art techniques by 33% and 50% in ranking the incorrect statements in the systems containing a single bug each. In about two-thirds of the cases, VARCOP correctly ranks the buggy statements at the top-3 positions in the ranked lists. For the cases containing multiple bugs, VARCOP outperforms the state-of-the-art approaches 2 times and 10 times in the proportion of bugs localized at the top-1 positions. Especially, in 22% and 65% of the buggy versions, VARCOP correctly ranks at least one bug in a system at the top-1 and top-5 positions.

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Section: Related Workmentioning

confidence: 99%

A Variability Fault Localization Approach for Software Product Lines

Nguyen,

Ngo,

Nguyen

et al. 2021

Preprint

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“…For many real-world software product lines and most configurable systems, disallowed combinations of features or configuration options are not specified or are not available to developers [60].…”

Section: An Unwanted Feature Interaction In a System Without Feature-...mentioning

confidence: 99%

“…Since multiple studies have shown that most feature interactions involve two features, our aim is to detect pairwise unwanted feature interactions [69,51,39,57,58,60,36,2]. In our proposed approach to detecting unwanted feature interactions in the absence of constraint specifications, we use feature-related data flow dependencies to learn feature dependencies and present that information to developers.…”

Section: An Unwanted Feature Interaction In a System Without Feature-...mentioning

confidence: 99%

“…Regarding feature interactions in highly configurable systems without specifications, Soares, et al [60] used dynamic analysis based on the data and control flow execution of Java-based configurable systems. Our work reported here differs in that we focus on analyzing data flow and static analysis of C-based configurable systems and do not require availability of test cases.…”

Section: Related Workmentioning

confidence: 99%

“…The need to identify unwanted or undetected feature interactions has driven multiple approaches to be proposed in the literature [12,2,60,67].…”

Section: Introductionmentioning

confidence: 99%

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Learning Feature Interactions With and Without Specifications

Khoshmanesh,

Yavuz,

Lutz

2021

Preprint

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Features in product lines and highly configurable systems can interact in ways that are contrary to developers' intent. Current methods to identify such unanticipated feature interactions are costly and inadequate. To address this problem we propose a new approach to learn feature interactions, both in those product lines where constraints on feature combinations are specified and in feature-rich configurable systems where such specifications often are not available. The contribution of the paper is to use program analysis to extract feature-relevant learning models from the source code in order to detect unwanted feature interactions. Where specifications of feature constraints are unavailable, our approach infers the constraints using feature-related data-flow dependency information. Evaluation in experiments on three software product line benchmarks and a highly configurable system shows that this approach is fast and effective. The contribution is to support developers by automatically detecting feature combinations in a new product or version that can interact in unwanted or unrecognized ways. This enables better understanding of latent interactions and identifies software components that should be tested together because their features interact in some configurations.

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