Abduction by Non-Experts
Author(s) -
Nikolaj Bjørner,
Dejan Jovanović,
Tancrède Lepoint,
Philipp Rümmer,
Martin Schäf
Publication year - 2018
Publication title -
kalpa publications in computing
Language(s) - English
Resource type - Conference proceedings
ISSN - 2515-1762
DOI - 10.29007/pz3t
Subject(s) - crowdsourcing , computer science , task (project management) , inference , horn clause , artificial intelligence , process (computing) , crowdsourcing software development , software , natural language processing , automation , software engineering , machine learning , programming language , logic programming , software development , software development process , world wide web , economics , mechanical engineering , management , engineering
Crowdsourcing promises to quasi-automate tasks that cannot be automated otherwise. Success stories like natural language translation or recognition of cats in images show that carefully crafted crowdsourcing tasks solve large problem instances which could not be solved otherwise. To utilize crowdsourcing, one has to define the problem in a way that is easy to split into small tasks, that the tasks are easy to solve for humans and hard to solve for a machine, and that the machine can efficiently check if the solution is correct. In this paper we discuss a novel approach of using crowdsourcing to assist software verification. We argue that Horn clauses form a good base for crowdsourcing since they are easy to subdivide, and that logic abduction is a suitable task since it is hard to automatically find abductive inferences for Horn clauses, but it is easy to check if an inference makes a Horn clause valid. We describe a prototype implementation, we show how crowdsourcing integrates in the verification process, and present preliminary results.
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