Analyzing the Impact of Feature Changes in Linux

Ziegler, Andreas; Rothberg, Valentin; Lohmann, Daniel

doi:10.1145/2866614.2866618

Cited by 10 publications

(8 citation statements)

References 15 publications

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“…Recent research analyzed and categorized evolution of product lines and, in particular, the mapping between variability model and artifacts [27,31,42,43]. However, the guided configuration evolution is more generic and helps to update configurations.…”

Section: Related Workmentioning

confidence: 99%

“…In the mentioned research [27,31,42] categorizations of commits are considered, but the guided configuration evolution is more generic and helps to update configurations. Ziegler et al analyze the Linux kernel evolution and identify artifacts affected by changes to the variability model [43]. These results are incorporated in regression testing of configurations mapped to changed artifacts.…”

Section: Related Workmentioning

confidence: 99%

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Guiding the evolution of product-line configurations

et al. 2021

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A product line is an approach for systematically managing configuration options of customizable systems, usually by means of features. Products are generated for configurations consisting of selected features. Product-line evolution can lead to unintended changes to product behavior. We illustrate that updating configurations after product-line evolution requires decisions of both, domain engineers responsible for product-line evolution as well as application engineers responsible for configurations. The challenge is that domain and application engineers might not be able to interact with each other. We propose a formal foundation and a methodology that enables domain engineers to guide application engineers through configuration evolution by sharing knowledge on product-line evolution and by defining automatic update operations for configurations. As an effect, we enable knowledge transfer between those engineers without the need for interactions. We evaluate our methodology on four large-scale industrial product lines. The results of the qualitative evaluation indicate that our method is flexible enough for real-world product-line evolution. The quantitative evaluation indicates that we detect product behavior changes for up to $$55.3\%$$ 55.3 % of the configurations which would not have been detected using existing methods.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Guiding the evolution of product-line configurations

et al. 2021

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“…Recent research analyzed and categorized evolution of product lines and, in particular, the mapping between variability model and artifacts [6,8,17,35]. However, the guided configuration evolution is more generic and helps to update configurations.…”

Section: Related Workmentioning

confidence: 99%

GuyDance

Nieke

Sampaio

Thüm

et al. 2020

Proceedings of the 24th ACM International Systems and Software Product Line Conference - Volume B

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A product line is an approach for systematically managing configuration options of customizable systems, usually by means of features. Products are generated by utilizing configurations consisting of selected features. Product-line evolution can lead to unintended changes to product behavior. We illustrate that updating configurations after product-line evolution requires decisions of both, domain engineers responsible for product-line evolution as well as application engineers responsible for configurations. The challenge is that domain and application engineers might not be able to talk to each other. We propose a formal foundation and a methodology that enables domain engineers to guide application engineers through configuration evolution by sharing knowledge on product-line evolution and by defining configuration update operations. As an effect, we enable knowledge transfer between those engineers without the need to talk to each other. We evaluate our method by providing formal proofs that show product behavior of configurations can be preserved for typical evolution scenarios. CCS CONCEPTS • Software and its engineering → Software product lines; Software evolution; Maintaining software; Software configuration management and version control systems.

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“…Undertaker [6] is a suite of tools to carry out variability-aware static analysis of Linux kernel source code for dead code and related bugs introduced by C preprocessor directives. Vampyr [80] is a part of the Undertaker suite that performs variability-aware static coverage analysis of kernel drivers. KConfigReader [26] uses Undertaker to analyze a Linux kernel variability model (kconfig files) and translate it into a propositional formula for automated reasoning with SAT solvers.…”

Section: Variability-aware Code Analysismentioning

confidence: 99%

Automating Patching of Vulnerable Open-Source Software Versions in Application Binaries

Duan

Bijlani

Yang

et al. 2019

Proceedings 2019 Network and Distributed System Security Symposium

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Mobile application developers rely heavily on opensource software (OSS) to offload common functionalities such as the implementation of protocols and media format playback. Over the past years, several vulnerabilities have been found in popular open-source libraries like OpenSSL and FFmpeg. Mobile applications that include such libraries inherit these flaws, which make them vulnerable. Fortunately, the open-source community is responsive and patches are made available within days. However, mobile application developers are often left unaware of these flaws. The App Security Improvement Program (ASIP) is a commendable effort by Google to notify application developers of these flaws, but recent work has shown that many developers do not act on this information. Our work addresses vulnerable mobile applications through automatic binary patching from source patches provided by the OSS maintainers and without involving the developers. We propose novel techniques to overcome difficult challenges like patching feasibility analysis, source-code-to-binary-code matching, and in-memory patching. Our technique uses a novel variabilityaware approach, which we implement as OSSPATCHER. We evaluated OSSPATCHER with 39 OSS and a collection of 1,000 Android applications using their vulnerable versions. OSSPATCHER generated 675 function-level patches that fixed the affected mobile applications without breaking their binary code. Further, we evaluated 10 vulnerabilities in popular apps such as Chrome with public exploits, which OSSPATCHER was able to mitigate and thwart their exploitation.

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Analyzing the Impact of Feature Changes in Linux

Cited by 10 publications

References 15 publications

Guiding the evolution of product-line configurations

Guiding the evolution of product-line configurations

GuyDance

Automating Patching of Vulnerable Open-Source Software Versions in Application Binaries

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