---
OA_place: publisher
OA_type: hybrid
_id: '18169'
abstract:
- lang: eng
  text: "As the complexity and criticality of software increase every year, so does
    the importance of runtime monitoring. Third-party and best-effort monitoring are
    especially valuable, yet under-explored areas of runtime monitoring. In this context,
    third-party monitoring means monitoring with a limited knowledge of the monitored
    software (as it has been developed by a third party). Best-effort monitoring keeps
    pace with the monitored software at the cost of possibly imprecise verdicts when
    keeping up with the monitored software would not be feasible. Most existing monitoring
    frameworks do not support the combination of third-party and best-effort monitoring
    because they either require the full access to the monitored code or the ability
    to process all observable events, or both.\r\nWe present a middleware framework,
    Vamos, for the runtime monitoring of software. Vamos is explicitly designed to
    support third-party and best-effort scenarios. The design goals of Vamos are (i)
    efficiency (tracing events with low overhead), (ii) flexibility (the ability to
    monitor a variety of different event channels, and to connect to a wide range
    of monitors), and (iii) ease-of-use. To achieve its goals, Vamos combines aspects
    of event broker and event recognition systems with aspects of stream processing
    systems.\r\nWe implemented a prototype toolchain for Vamos and conducted a set
    of experiments demonstrating the usability of the scheme. The results indicate
    that Vamos enables writing useful yet efficient monitors, and simplifies key aspects
    of setting up a monitoring system from scratch."
acknowledgement: This work was supported in part by the ERC-2020-AdG 101020093. The
  authors would like to thank the STTT reviewers for their valuable feedback and suggestions.
article_number: '103212'
article_processing_charge: Yes (via OA deal)
article_type: original
author:
- first_name: Marek
  full_name: Chalupa, Marek
  id: 87e34708-d6c6-11ec-9f5b-9391e7be2463
  last_name: Chalupa
- first_name: Fabian
  full_name: Mühlböck, Fabian
  id: 6395C5F6-89DF-11E9-9C97-6BDFE5697425
  last_name: Mühlböck
  orcid: 0000-0003-1548-0177
- first_name: Stefanie
  full_name: Muroya Lei, Stefanie
  id: a376de31-8972-11ed-ae7b-d0251c13c8ff
  last_name: Muroya Lei
- first_name: Thomas A
  full_name: Henzinger, Thomas A
  id: 40876CD8-F248-11E8-B48F-1D18A9856A87
  last_name: Henzinger
  orcid: 0000-0002-2985-7724
citation:
  ama: 'Chalupa M, Mühlböck F, Muroya Lei S, Henzinger TA. VAMOS: Middleware for best-effort
    third-party monitoring. <i>Science of Computer Programming</i>. 2025;240(2). doi:<a
    href="https://doi.org/10.1016/j.scico.2024.103212">10.1016/j.scico.2024.103212</a>'
  apa: 'Chalupa, M., Mühlböck, F., Muroya Lei, S., &#38; Henzinger, T. A. (2025).
    VAMOS: Middleware for best-effort third-party monitoring. <i>Science of Computer
    Programming</i>. Elsevier. <a href="https://doi.org/10.1016/j.scico.2024.103212">https://doi.org/10.1016/j.scico.2024.103212</a>'
  chicago: 'Chalupa, Marek, Fabian Mühlböck, Stefanie Muroya Lei, and Thomas A Henzinger.
    “VAMOS: Middleware for Best-Effort Third-Party Monitoring.” <i>Science of Computer
    Programming</i>. Elsevier, 2025. <a href="https://doi.org/10.1016/j.scico.2024.103212">https://doi.org/10.1016/j.scico.2024.103212</a>.'
  ieee: 'M. Chalupa, F. Mühlböck, S. Muroya Lei, and T. A. Henzinger, “VAMOS: Middleware
    for best-effort third-party monitoring,” <i>Science of Computer Programming</i>,
    vol. 240, no. 2. Elsevier, 2025.'
  ista: 'Chalupa M, Mühlböck F, Muroya Lei S, Henzinger TA. 2025. VAMOS: Middleware
    for best-effort third-party monitoring. Science of Computer Programming. 240(2),
    103212.'
  mla: 'Chalupa, Marek, et al. “VAMOS: Middleware for Best-Effort Third-Party Monitoring.”
    <i>Science of Computer Programming</i>, vol. 240, no. 2, 103212, Elsevier, 2025,
    doi:<a href="https://doi.org/10.1016/j.scico.2024.103212">10.1016/j.scico.2024.103212</a>.'
  short: M. Chalupa, F. Mühlböck, S. Muroya Lei, T.A. Henzinger, Science of Computer
    Programming 240 (2025).
corr_author: '1'
date_created: 2024-10-06T22:01:10Z
date_published: 2025-02-01T00:00:00Z
date_updated: 2025-09-09T12:25:29Z
day: '01'
ddc:
- '000'
department:
- _id: ToHe
doi: 10.1016/j.scico.2024.103212
ec_funded: 1
external_id:
  isi:
  - '001327852600001'
file:
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  creator: dernst
  date_created: 2025-01-13T09:02:47Z
  date_updated: 2025-01-13T09:02:47Z
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file_date_updated: 2025-01-13T09:02:47Z
has_accepted_license: '1'
intvolume: '       240'
isi: 1
issue: '2'
language:
- iso: eng
license: https://creativecommons.org/licenses/by/4.0/
month: '02'
oa: 1
oa_version: Published Version
project:
- _id: 62781420-2b32-11ec-9570-8d9b63373d4d
  call_identifier: H2020
  grant_number: '101020093'
  name: Vigilant Algorithmic Monitoring of Software
publication: Science of Computer Programming
publication_identifier:
  issn:
  - 0167-6423
publication_status: published
publisher: Elsevier
quality_controlled: '1'
related_material:
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    relation: earlier_version
    status: public
scopus_import: '1'
status: public
title: 'VAMOS: Middleware for best-effort third-party monitoring'
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  image: /images/cc_by.png
  legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
  name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
  short: CC BY (4.0)
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 240
year: '2025'
...