Studying and Understanding the Tradeoffs Between Generality and Reduction in Software Debloating

Qi, Xin; Zhang, Qirun; Orso, Alessandro

doi:10.1145/3551349.3556970

Cited by 12 publications

(6 citation statements)

References 47 publications

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“…The existing technologies for removing code, such as dead code, technical debt, or software bloat, perhaps can be adapted to a certain extent. But, our call is for removing variability, which is different from disabling it, debloating system binaries [26,33], or removing an unreachable piece of code.…”

Section: How To Remove Variabilitymentioning

confidence: 99%

“…Software debloating has been recently explored to reduce the size of deployed containers [23], or reduce the attack surface of specific programs (e.g., [7,11,12,21,25,26,31,32]). Often, proposed approaches debloat a system compiled binaries [20,33], remove its unused libraries [27], and rarely configuration options [12]. Existing approaches are all heirs of existing works in program specialization [15], so the idea of removing code is not completely new.…”

Section: How To Remove Variabilitymentioning

confidence: 99%

“…One possible scenario is to remove all variability (a.k.a., based on a usage profile), for example, fixing a configuration once and for all and forbidding any reconfiguration at run-time. This scenario is extreme and not applicable in many contexts, since users would lack the needed flexibility for their systems [33]. Another scenario is to find the unused variability units (e.g., stale feature toggles) and remove them.…”

Section: How To Remove Variabilitymentioning

confidence: 99%

See 2 more Smart Citations

A Call for Removing Variability

Acher

Lesoil

Randrianaina

et al. 2023

Proceedings of the 17th International Working Conference on Variability Modelling of Software-Intensive Systems

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Software variability is largely accepted and explored in software engineering and seems to have become a norm and a must, if only in the context of product lines. Yet, the removal of superfluous or unneeded software artefacts and functionalities is an inevitable trend. It is frequently investigated in relation to software bloat. This paper is essentially a call to the community on software variability to devise methods and tools that will facilitate the removal of unneeded variability from software systems. The advantages are expected to be numerous in terms of functional and non-functional properties, such as maintainability (lower complexity), security (smaller attack surface), reliability, and performance (smaller binaries).

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Section: How To Remove Variabilitymentioning

confidence: 99%

Section: How To Remove Variabilitymentioning

confidence: 99%

Section: How To Remove Variabilitymentioning

confidence: 99%

See 1 more Smart Citation

A Call for Removing Variability

Acher

Lesoil

Randrianaina

et al. 2023

Proceedings of the 17th International Working Conference on Variability Modelling of Software-Intensive Systems

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“…Study of code bloat in software with consequent debloating has received a lot of attention in the recent past. Xin et al [41] have analyzed the tradeoffs between code reduction and function generality in debloated software. Jiang et al [29], [30] have studied the issue of software bloat in real-world Android applications and have proposed static analysis based techniques to remove dead code.…”

Section: B Code-based Debloatingmentioning

confidence: 99%

IOSPReD: I/O Specialized Packaging of Reduced Datasets and Data-Intensive Applications for Efficient Reproducibility

et al. 2023

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The data generated by large scale scientific systems such as NASA's Earth Observing System Data and Information System is expected to increase substantially. Consequently, applications processing these huge volumes of data suffer from lack of storage space at the execution site. This poses a critical challenge while sharing data and reproducing application executions w.r.t. specific user inputs in dataintensive applications. To address this issue, we propose IOSPReD (I/O Specialized Packaging of Reduced Datasets), a data-based debloating framework, designed to automatically track and package only necessary chunks of data (along with the application) in a container. IOSPReD uses the specific inputs provided by the user to identify the necessary data chunks. To do so, the high level user inputs are mapped down to low level data file offsets. We evaluate IOSPReD on different realistic NASA datasets to assess (i) the amount of data reduction, (ii) the reproducibility of results across multiple application executions and also (iii) the impact on performance.

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“…Debloating [65], [66] offers a way to produce a reduced program that still works correctly for existing clients on a given set of inputs. Adaptoring, meanwhile, creates a new, reduced API, designed to improve learnability and reduce the risk of misuse by new clients.…”

Section: Related Workmentioning

confidence: 99%