16/09/2022

Interaction specification mining with adversarial examples

This job offer has expired


  • ORGANISATION/COMPANY
    CEA LIST
  • RESEARCH FIELD
    Computer scienceInformatics
  • RESEARCHER PROFILE
    First Stage Researcher (R1)
    Recognised Researcher (R2)
    Established Researcher (R3)
    Leading Researcher (R4)
  • APPLICATION DEADLINE
    14/12/2022 00:00 - Europe/Athens
  • LOCATION
    France › Palaiseau
  • TYPE OF CONTRACT
    Temporary
  • JOB STATUS
    Full-time

OFFER DESCRIPTION

A 3-year long full-time PhD student in Softtware Engineering on the following subject:

 

Interaction specification mining with adversarial examples

 

Software systems are often developed in a modular way by (re)using components that cooperate in providing a more global service. We will consider component-intensive software systems, particularly those composed of communicating components via message passing and communication primitives. Examples of such systems are client/server systems, transportation control systems, Internet of Things, connected autonomous vehicles, etc. In practice, the assembly of these components follows poorly documented ad-hoc procedures. Therefore, discovering their formal specifications, i.e., specification mining is of great interest for many software Verification and Validation activities (V&V). In our context, mining will exploit the information contained in the execution logs of the communicating components. These logs are often collected via code instrumentation or sniffing or via a testing architecture. The objective of the doctoral work is to develop new methods for mining interaction specifications, such as models of UML Sequence diagrams or Message Sequence Charts (MSC). The foreseen mining framework will be grounded by recent theoretical work and supporting tooling on operational rewriting semantics of interaction developed conjointly between CEA LIST and CentraleSupélec. It will encompass test generation, guided by key reachability properties or, more generally, LTL (Linear Temporal Logic) properties that adversely exercise the components against uncommon test inputs and thus ensuring diversity in their executions for more efficient mining.

The doctoral work will be conducted in the frame of the HORIZON Europe project SELFY. N.B., SELFY stands for SELF assessment, protection & healing tools for a trustworthY and resilient CCAM, CCAM stands for Cooperative, Connected and Automated Mobility. The project SELFY aims to increase the CCAM ecosystem’s safety, security, robustness, and resilience by researching and developing a toolbox made of collaborative tools, including a V&V tool based on interaction specification mining. The PhD student will be involved in research collaboration with Okayama University (Japan), an international associate partner linked to CEA in the project.

 

Detailed proposition. https://drive.google.com/file/d/1dKcIEeucEAP03opm_XLS6vmQI5vmCPYk/view?usp=sharing



Funding category: Contrat doctoral



PHD Country: France

More Information

Offer Requirements

Specific Requirements

The applicant must have a master's degree in computer science or a specialization in computer science in an engineering school.

Work location(s)
1 position(s) available at
CEA LIST
France
Palaiseau

EURAXESS offer ID: 837414
Posting organisation offer ID: 107534

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