Details
| Originalsprache | Englisch |
|---|---|
| Titel des Sammelwerks | 28th ACM International Systems and Software Product Line Conference, Proceedings |
| Untertitel | SPLC 2024 |
| Herausgeber/-innen | Maxime Cordy, Daniel Struber, Daniel Struber, Monica Pinto, Iris Groher, Deepak Dhungana, Jacob Kruger, Juliana Alves Pereira, Mathieu Acher, Thomas Thum, Thomas Thum, Maurice H. ter Beek, Jessie Galasso-Carbonnel, Paolo Arcaini, Mohammad Reza Mousavi, Xhevahire Ternava, Jose A. Galindo, Tao Yue, Lidia Fuentes, Jose Miguel Horcas |
| Seiten | 12-23 |
| Seitenumfang | 12 |
| ISBN (elektronisch) | 9798400705939 |
| Publikationsstatus | Veröffentlicht - 2 Sept. 2024 |
| Veranstaltung | 28th ACM International Systems and Software Product Line Conference, SPLC 2024 - Dommeldange, Luxemburg Dauer: 2 Sept. 2024 → 6 Sept. 2024 |
Publikationsreihe
| Name | ACM International Conference Proceeding Series |
|---|
Abstract
In the face of critical security vulnerabilities, patch and update management are a crucial and challenging part of the software life cycle. In software product families, patching becomes even more challenging as we have to support different variants, which are not equally affected by critical patches. While the naive “better-patched-than-sorry” approach will apply all necessary updates, it provokes avoidable costs for developers and customers. In this paper we introduce SiB (Should I Bother?), a heuristic patch-filtering method for statically-configurable software that efficiently identifies irrelevant patches for specific variants. To solve the variability-aware patch-filtering problem, SiB compares modified line ranges from patches with those source-code ranges included in variants currently deployed. We apply our prototype for CPP-managed variability to four open-source projects (Linux, OpenSSL, SQLite, Bochs), demonstrating that SiB is both effective and efficient in reducing the number of to-be-considered patches for unaffected software variants. It correctly classifies up to 68 percent of variants as unaffected, with a recall of 100 percent, thus reducing deployments significantly, without missing any relevant patches.
ASJC Scopus Sachgebiete
- Informatik (insg.)
- Mensch-Maschine-Interaktion
- Informatik (insg.)
- Computernetzwerke und -kommunikation
- Informatik (insg.)
- Maschinelles Sehen und Mustererkennung
- Informatik (insg.)
- Software
Zitieren
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- Harvard
- Apa
- Vancouver
- BibTex
- RIS
28th ACM International Systems and Software Product Line Conference, Proceedings: SPLC 2024. Hrsg. / Maxime Cordy; Daniel Struber; Daniel Struber; Monica Pinto; Iris Groher; Deepak Dhungana; Jacob Kruger; Juliana Alves Pereira; Mathieu Acher; Thomas Thum; Thomas Thum; Maurice H. ter Beek; Jessie Galasso-Carbonnel; Paolo Arcaini; Mohammad Reza Mousavi; Xhevahire Ternava; Jose A. Galindo; Tao Yue; Lidia Fuentes; Jose Miguel Horcas. 2024. S. 12-23 (ACM International Conference Proceeding Series).
Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review
}
TY - GEN
T1 - Should I Bother?
T2 - 28th ACM International Systems and Software Product Line Conference, SPLC 2024
AU - Landsberg, Tobias
AU - Dietrich, Christian
AU - Lohmann, Daniel
N1 - Publisher Copyright: © 2024 Copyright held by the owner/author(s).
PY - 2024/9/2
Y1 - 2024/9/2
N2 - In the face of critical security vulnerabilities, patch and update management are a crucial and challenging part of the software life cycle. In software product families, patching becomes even more challenging as we have to support different variants, which are not equally affected by critical patches. While the naive “better-patched-than-sorry” approach will apply all necessary updates, it provokes avoidable costs for developers and customers. In this paper we introduce SiB (Should I Bother?), a heuristic patch-filtering method for statically-configurable software that efficiently identifies irrelevant patches for specific variants. To solve the variability-aware patch-filtering problem, SiB compares modified line ranges from patches with those source-code ranges included in variants currently deployed. We apply our prototype for CPP-managed variability to four open-source projects (Linux, OpenSSL, SQLite, Bochs), demonstrating that SiB is both effective and efficient in reducing the number of to-be-considered patches for unaffected software variants. It correctly classifies up to 68 percent of variants as unaffected, with a recall of 100 percent, thus reducing deployments significantly, without missing any relevant patches.
AB - In the face of critical security vulnerabilities, patch and update management are a crucial and challenging part of the software life cycle. In software product families, patching becomes even more challenging as we have to support different variants, which are not equally affected by critical patches. While the naive “better-patched-than-sorry” approach will apply all necessary updates, it provokes avoidable costs for developers and customers. In this paper we introduce SiB (Should I Bother?), a heuristic patch-filtering method for statically-configurable software that efficiently identifies irrelevant patches for specific variants. To solve the variability-aware patch-filtering problem, SiB compares modified line ranges from patches with those source-code ranges included in variants currently deployed. We apply our prototype for CPP-managed variability to four open-source projects (Linux, OpenSSL, SQLite, Bochs), demonstrating that SiB is both effective and efficient in reducing the number of to-be-considered patches for unaffected software variants. It correctly classifies up to 68 percent of variants as unaffected, with a recall of 100 percent, thus reducing deployments significantly, without missing any relevant patches.
KW - Patch Filtering
KW - Software Evolution
KW - Software Product Lines
UR - http://www.scopus.com/inward/record.url?scp=85203839201&partnerID=8YFLogxK
U2 - 10.1145/3646548.3672585
DO - 10.1145/3646548.3672585
M3 - Conference contribution
AN - SCOPUS:85203839201
T3 - ACM International Conference Proceeding Series
SP - 12
EP - 23
BT - 28th ACM International Systems and Software Product Line Conference, Proceedings
A2 - Cordy, Maxime
A2 - Struber, Daniel
A2 - Struber, Daniel
A2 - Pinto, Monica
A2 - Groher, Iris
A2 - Dhungana, Deepak
A2 - Kruger, Jacob
A2 - Alves Pereira, Juliana
A2 - Acher, Mathieu
A2 - Thum, Thomas
A2 - Thum, Thomas
A2 - ter Beek, Maurice H.
A2 - Galasso-Carbonnel, Jessie
A2 - Arcaini, Paolo
A2 - Mousavi, Mohammad Reza
A2 - Ternava, Xhevahire
A2 - Galindo, Jose A.
A2 - Yue, Tao
A2 - Fuentes, Lidia
A2 - Horcas, Jose Miguel
Y2 - 2 September 2024 through 6 September 2024
ER -