Objective
One of the long-lasting dreams in science fiction is the ability to arrest criminals before they even commit crimes. Software testing researchers have a similar dream: when the context for a bug manifestation occurs in the field, the goal is to discover and fix the bug before it causes any in-field failure. In fact, current practice of pre-release testing is severely limited when dealing with autonomous AI (Artificial Intelligence) systems (such as self-driving cars, robots, automated traders, virtual doctors and customer service chatbots), running in complex, rapidly changing environments, which cause their run-time adaptation, learning and knowledge acquisition, because pre-release testing cannot exhaustively explore all different contexts and states in which the software will be running.
The PRECRIME project introduces a new, disruptive view on testing, called anticipatory testing and aimed at fixing bugs before they even manifest themselves in the field. Anticipatory testing is activated at run-time by a new type of oracles, called self-assessment oracles, which observe and report unexpected execution contexts. A self-assessment oracle is an estimator of the system’s confidence in being able to handle a new execution context correctly. The goal of anticipatory testing is to anticipate any failure that might occur in the field due to unexpected execution contexts. Whenever an execution context monitored at runtime by self-assessment oracles is estimated as a low confidence context for the system, anticipatory testing exercises the software automatically and extensively in similar contexts. Timely activation of anticipatory testing by runtime observations results in early, anticipatory fault detection. Combined with automated patch synthesis, anticipatory testing leads to the release of a patch for the fault before any software failure occurs in the field.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- natural sciences computer and information sciences artificial intelligence
- engineering and technology mechanical engineering vehicle engineering automotive engineering autonomous vehicles
- natural sciences computer and information sciences software
- social sciences law criminology
- humanities languages and literature literature studies literary genres essays science fiction
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Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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H2020-EU.1.1. - EXCELLENT SCIENCE - European Research Council (ERC)
MAIN PROGRAMME
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Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
ERC-ADG - Advanced Grant
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) ERC-2017-ADG
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
6900 LUGANO
Switzerland
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.