SoK: Software Debloating Landscape and Future Directions

Mohannad Alhanahnah, Yazan Boshmaf, Ashish Gehani

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Software debloating seeks to mitigate security risks and improve performance by eliminating unnecessary code. In recent years, a plethora of debloating tools have been developed, creating a dense and varied landscape. Several studies have delved into the literature, focusing on comparative analysis of these tools. To build upon these efforts, this paper presents a comprehensive systematization of knowledge (SoK) of the software debloating landscape. We conceptualize the software debloating workflow, which serves as the basis for developing a multilevel taxonomy. This framework classifies debloating tools according to their input/output artifacts, debloating strategies, and evaluation criteria. Lastly, we apply the taxonomy to pinpoint open problems in the field, which, together with the SoK, provide a foundational reference for researchers aiming to improve software security and efficiency through debloating.

Original languageEnglish
Title of host publicationProceedings Of The 2024 Workshop On Forming An Ecosystem Around Software Transformation, Feast 2024
Subtitle of host publicationCCS 2024
PublisherAssociation for Computing Machinery, Inc
Pages11-18
Number of pages8
ISBN (Electronic)9798400712333
DOIs
Publication statusPublished - 19 Nov 2024
Event6th Workshop on Forming an Ecosystem Around Software Transformation, FEAST 2024 - Salt Lake City, United States
Duration: 14 Oct 202418 Oct 2024

Publication series

NameFEAST 2024 - Proceedings of the 2024 Workshop on Forming an Ecosystem Around Software Transformation, Co-Located with: CCS 2024

Conference

Conference6th Workshop on Forming an Ecosystem Around Software Transformation, FEAST 2024
Country/TerritoryUnited States
CitySalt Lake City
Period14/10/2418/10/24

Keywords

  • Sbom
  • Sdlc
  • Software Debloating
  • Software Security
  • Systematization of Knowledge
  • Taxonomy

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