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Abduction by Non-Experts

15 pagesPublished: June 4, 2017

Abstract

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 find abductive inferences for Horn clauses automatically, 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.

Keyphrases: abduction, Horn solving, Crowdsourcing

In: Thomas Eiter, David Sands, Geoff Sutcliffe and Andrei Voronkov (editors). IWIL Workshop and LPAR Short Presentations, vol 1, pages 58--72

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