---
_id: '13234'
abstract:
- lang: eng
  text: Neural-network classifiers achieve high accuracy when predicting the class
    of an input that they were trained to identify. Maintaining this accuracy in dynamic
    environments, where inputs frequently fall outside the fixed set of initially
    known classes, remains a challenge. We consider the problem of monitoring the
    classification decisions of neural networks in the presence of novel classes.
    For this purpose, we generalize our recently proposed abstraction-based monitor
    from binary output to real-valued quantitative output. This quantitative output
    enables new applications, two of which we investigate in the paper. As our first
    application, we introduce an algorithmic framework for active monitoring of a
    neural network, which allows us to learn new classes dynamically and yet maintain
    high monitoring performance. As our second application, we present an offline
    procedure to retrain the neural network to improve the monitor’s detection performance
    without deteriorating the network’s classification accuracy. Our experimental
    evaluation demonstrates both the benefits of our active monitoring framework in
    dynamic scenarios and the effectiveness of the retraining procedure.
acknowledgement: This work was supported in part by the ERC-2020-AdG 101020093, by
  DIREC - Digital Research Centre Denmark, and by the Villum Investigator Grant S4OS.
article_processing_charge: Yes (in subscription journal)
article_type: original
arxiv: 1
author:
- first_name: Konstantin
  full_name: Kueffner, Konstantin
  id: 8121a2d0-dc85-11ea-9058-af578f3b4515
  last_name: Kueffner
  orcid: 0000-0001-8974-2542
- first_name: Anna
  full_name: Lukina, Anna
  id: CBA4D1A8-0FE8-11E9-BDE6-07BFE5697425
  last_name: Lukina
- first_name: Christian
  full_name: Schilling, Christian
  id: 3A2F4DCE-F248-11E8-B48F-1D18A9856A87
  last_name: Schilling
  orcid: 0000-0003-3658-1065
- 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: 'Kueffner K, Lukina A, Schilling C, Henzinger TA. Into the unknown: Active
    monitoring of neural networks (extended version). <i>International Journal on
    Software Tools for Technology Transfer</i>. 2023;25:575-592. doi:<a href="https://doi.org/10.1007/s10009-023-00711-4">10.1007/s10009-023-00711-4</a>'
  apa: 'Kueffner, K., Lukina, A., Schilling, C., &#38; Henzinger, T. A. (2023). Into
    the unknown: Active monitoring of neural networks (extended version). <i>International
    Journal on Software Tools for Technology Transfer</i>. Springer Nature. <a href="https://doi.org/10.1007/s10009-023-00711-4">https://doi.org/10.1007/s10009-023-00711-4</a>'
  chicago: 'Kueffner, Konstantin, Anna Lukina, Christian Schilling, and Thomas A Henzinger.
    “Into the Unknown: Active Monitoring of Neural Networks (Extended Version).” <i>International
    Journal on Software Tools for Technology Transfer</i>. Springer Nature, 2023.
    <a href="https://doi.org/10.1007/s10009-023-00711-4">https://doi.org/10.1007/s10009-023-00711-4</a>.'
  ieee: 'K. Kueffner, A. Lukina, C. Schilling, and T. A. Henzinger, “Into the unknown:
    Active monitoring of neural networks (extended version),” <i>International Journal
    on Software Tools for Technology Transfer</i>, vol. 25. Springer Nature, pp. 575–592,
    2023.'
  ista: 'Kueffner K, Lukina A, Schilling C, Henzinger TA. 2023. Into the unknown:
    Active monitoring of neural networks (extended version). International Journal
    on Software Tools for Technology Transfer. 25, 575–592.'
  mla: 'Kueffner, Konstantin, et al. “Into the Unknown: Active Monitoring of Neural
    Networks (Extended Version).” <i>International Journal on Software Tools for Technology
    Transfer</i>, vol. 25, Springer Nature, 2023, pp. 575–92, doi:<a href="https://doi.org/10.1007/s10009-023-00711-4">10.1007/s10009-023-00711-4</a>.'
  short: K. Kueffner, A. Lukina, C. Schilling, T.A. Henzinger, International Journal
    on Software Tools for Technology Transfer 25 (2023) 575–592.
date_created: 2023-07-16T22:01:11Z
date_published: 2023-08-01T00:00:00Z
date_updated: 2024-01-30T12:06:57Z
day: '01'
ddc:
- '000'
department:
- _id: ToHe
doi: 10.1007/s10009-023-00711-4
ec_funded: 1
external_id:
  arxiv:
  - '2009.06429'
  isi:
  - '001020160000001'
file:
- access_level: open_access
  checksum: 3c4b347f39412a76872f9a6f30101f94
  content_type: application/pdf
  creator: dernst
  date_created: 2024-01-30T12:06:07Z
  date_updated: 2024-01-30T12:06:07Z
  file_id: '14903'
  file_name: 2023_JourSoftwareTools_Kueffner.pdf
  file_size: 13387667
  relation: main_file
  success: 1
file_date_updated: 2024-01-30T12:06:07Z
has_accepted_license: '1'
intvolume: '        25'
isi: 1
language:
- iso: eng
month: '08'
oa: 1
oa_version: Published Version
page: 575-592
project:
- _id: 62781420-2b32-11ec-9570-8d9b63373d4d
  call_identifier: H2020
  grant_number: '101020093'
  name: Vigilant Algorithmic Monitoring of Software
publication: International Journal on Software Tools for Technology Transfer
publication_identifier:
  eissn:
  - 1433-2787
  issn:
  - 1433-2779
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
related_material:
  record:
  - id: '10206'
    relation: shorter_version
    status: public
scopus_import: '1'
status: public
title: 'Into the unknown: Active monitoring of neural networks (extended version)'
tmp:
  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: 25
year: '2023'
...
---
_id: '10861'
abstract:
- lang: eng
  text: We introduce in this paper AMT2.0, a tool for qualitative and quantitative
    analysis of hybrid continuous and Boolean signals that combine numerical values
    and discrete events. The evaluation of the signals is based on rich temporal specifications
    expressed in extended signal temporal logic, which integrates timed regular expressions
    within signal temporal logic. The tool features qualitative monitoring (property
    satisfaction checking), trace diagnostics for explaining and justifying property
    violations and specification-driven measurement of quantitative features of the
    signal. We demonstrate the tool functionality on several running examples and
    case studies, and evaluate its performance.
article_processing_charge: No
article_type: original
author:
- first_name: Dejan
  full_name: Nickovic, Dejan
  id: 41BCEE5C-F248-11E8-B48F-1D18A9856A87
  last_name: Nickovic
- first_name: Olivier
  full_name: Lebeltel, Olivier
  last_name: Lebeltel
- first_name: Oded
  full_name: Maler, Oded
  last_name: Maler
- first_name: Thomas
  full_name: Ferrere, Thomas
  id: 40960E6E-F248-11E8-B48F-1D18A9856A87
  last_name: Ferrere
  orcid: 0000-0001-5199-3143
- first_name: Dogan
  full_name: Ulus, Dogan
  last_name: Ulus
citation:
  ama: 'Nickovic D, Lebeltel O, Maler O, Ferrere T, Ulus D. AMT 2.0: Qualitative and
    quantitative trace analysis with extended signal temporal logic. <i>International
    Journal on Software Tools for Technology Transfer</i>. 2020;22(6):741-758. doi:<a
    href="https://doi.org/10.1007/s10009-020-00582-z">10.1007/s10009-020-00582-z</a>'
  apa: 'Nickovic, D., Lebeltel, O., Maler, O., Ferrere, T., &#38; Ulus, D. (2020).
    AMT 2.0: Qualitative and quantitative trace analysis with extended signal temporal
    logic. <i>International Journal on Software Tools for Technology Transfer</i>.
    Springer Nature. <a href="https://doi.org/10.1007/s10009-020-00582-z">https://doi.org/10.1007/s10009-020-00582-z</a>'
  chicago: 'Nickovic, Dejan, Olivier Lebeltel, Oded Maler, Thomas Ferrere, and Dogan
    Ulus. “AMT 2.0: Qualitative and Quantitative Trace Analysis with Extended Signal
    Temporal Logic.” <i>International Journal on Software Tools for Technology Transfer</i>.
    Springer Nature, 2020. <a href="https://doi.org/10.1007/s10009-020-00582-z">https://doi.org/10.1007/s10009-020-00582-z</a>.'
  ieee: 'D. Nickovic, O. Lebeltel, O. Maler, T. Ferrere, and D. Ulus, “AMT 2.0: Qualitative
    and quantitative trace analysis with extended signal temporal logic,” <i>International
    Journal on Software Tools for Technology Transfer</i>, vol. 22, no. 6. Springer
    Nature, pp. 741–758, 2020.'
  ista: 'Nickovic D, Lebeltel O, Maler O, Ferrere T, Ulus D. 2020. AMT 2.0: Qualitative
    and quantitative trace analysis with extended signal temporal logic. International
    Journal on Software Tools for Technology Transfer. 22(6), 741–758.'
  mla: 'Nickovic, Dejan, et al. “AMT 2.0: Qualitative and Quantitative Trace Analysis
    with Extended Signal Temporal Logic.” <i>International Journal on Software Tools
    for Technology Transfer</i>, vol. 22, no. 6, Springer Nature, 2020, pp. 741–58,
    doi:<a href="https://doi.org/10.1007/s10009-020-00582-z">10.1007/s10009-020-00582-z</a>.'
  short: D. Nickovic, O. Lebeltel, O. Maler, T. Ferrere, D. Ulus, International Journal
    on Software Tools for Technology Transfer 22 (2020) 741–758.
date_created: 2022-03-18T10:10:53Z
date_published: 2020-08-03T00:00:00Z
date_updated: 2023-09-08T11:52:02Z
day: '03'
department:
- _id: ToHe
doi: 10.1007/s10009-020-00582-z
external_id:
  isi:
  - '000555398600001'
intvolume: '        22'
isi: 1
issue: '6'
keyword:
- Information Systems
- Software
language:
- iso: eng
month: '08'
oa_version: None
page: 741-758
publication: International Journal on Software Tools for Technology Transfer
publication_identifier:
  eissn:
  - 1433-2787
  issn:
  - 1433-2779
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
related_material:
  record:
  - id: '299'
    relation: earlier_version
    status: public
scopus_import: '1'
status: public
title: 'AMT 2.0: Qualitative and quantitative trace analysis with extended signal
  temporal logic'
type: journal_article
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
volume: 22
year: '2020'
...