Analogy-Making as a Core Primitive in the Software Engineering Toolbox

An analogy is an identification of structural similarities and correspondences between two objects. Computational models of analogy making have been studied extensively in the field of cognitive science to better understand high-level human cognition. For instance, Melanie Mitchell and Douglas Hofstadter sought to better understand high-level perception by developing the Copycat algorithm for completing analogies between letter sequences. In this paper, we argue that analogy making should be seen as a core primitive in software engineering. We motivate this argument by showing how complex software engineering problems such as program understanding and source-code transformation learning can be reduced to an instance of the analogy-making problem. We demonstrate this idea using Sifter, a new analogy-making algorithm suitable for software engineering applications that adapts and extends ideas from Copycat. In particular, Sifter reduces analogy-making to searching for a sequence of update rule applications. Sifter uses a novel representation for mathematical structures capable of effectively representing the wide variety of information embedded in software. We conclude by listing major areas of future work for Sifter and analogy-making in software engineering.Comment: Conference paper at SPLASH 'Onward!' 2020. Code is available at https://github.com/95616ARG/sifte

AUTOMATED THEORY FORMATION IN MATHEMATICS 1

A program called "AM " is described which cairies on simple mathematics research: defining, and studying new concepts under the guidance of a large body of heuiistic rules. The 250 heurKtus communicate via an agenda mechanism, a global priority queue of small bisk', for the program to pei foim and teasons why each task is plausible (e.g., "Find PENCRAHZTION. of 'prnes', because turued out to be so useful a Conccpi"). Fach concept is an active, structured knowledge module. One bundled vei y incomplete modules are initially supplied, each one corresponding to an elementary set theoretic concept (e.g., union). This provides a definite but immense space which AM begins to explore. In one boor, AM rediscovers hundreds of common concepts (including singleton sets, natural numbers, arithmetic) and theorems (e.g., unique factorization)

Knowledge-based systems in artificial intelligence

xxi 490 p

Inside {Quasimodo}: {E}xploring Construction and Usage of Commonsense Knowledge

Structured world knowledge is at the foundation of knowledge-centric AI applications. Despite considerable research on knowledge base construction, beyond mere statement counts, little is known about the progress of KBs, in particular concerning their coverage, and one may wonder whether there is constant progress, or diminishing returns. In this paper we employ question answering and entity summarization as extrinsic use cases for a longitudinal study of the progress of KB coverage. Our analysis shows a near-continuous improvement of two popular KBs, DBpedia and Wikidata, over the last 19 years, with little signs of flattening out or leveling off

Designing a rule system that searches for scientific discoveries

Computer Science Departmen