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Self-Adaptation in Industry: A Survey

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F23%3A10474038" target="_blank" >RIV/00216208:11320/23:10474038 - isvavai.cz</a>

  • Alternative codes found

    RIV/49777513:23520/23:43969156

  • Result on the web

    <a href="https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=~6LaQ1mzXa" target="_blank" >https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=~6LaQ1mzXa</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1145/3589227" target="_blank" >10.1145/3589227</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Self-Adaptation in Industry: A Survey

  • Original language description

    Computing systems form the backbone of many areas in our society, from manufacturing to traffic control, healthcare, and financial systems. When software plays a vital role in the design, construction, and operation, these systems are referred to as software-intensive systems. Self-adaptation equips a software-intensive system with a feedback loop that either automates tasks that otherwise need to be performed by human operators or deals with uncertain conditions. Such feedback loops have found their way to a variety of practical applications; typical examples are an elastic cloud to adapt computing resources and automated server management to respond quickly to business needs. To gain insight into the motivations for applying self-adaptation in practice, the problems solved using self-adaptation and how these problems are solved, and the difficulties and risks that industry faces in adopting self-adaptation, we performed a large-scale survey. We received 184 valid responses from practitioners spread over 21 countries. Based on the analysis of the survey data, we provide an empirically grounded overview the of state of the practice in the application of self-adaptation. From that, we derive insights for researchers to check their current research with industrial needs, and for practitioners to compare their current practice in applying self-adaptation. These insights also provide opportunities for applying self-adaptation in practice and pave the way for future industry-research collaborations.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

  • Continuities

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2023

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    ACM Transactions on Autonomous and Adaptive Systems

  • ISSN

    1556-4665

  • e-ISSN

    1556-4703

  • Volume of the periodical

    18

  • Issue of the periodical within the volume

    2

  • Country of publishing house

    US - UNITED STATES

  • Number of pages

    44

  • Pages from-to

    5

  • UT code for WoS article

    001018507200002

  • EID of the result in the Scopus database

    2-s2.0-85177864146