3680 KB402 KB0 KB2022Črepinšek, MatejKovačević, ŽeljkoXXVI, 132 f., 30 cmCOBISSID:99642627URN:URN:NBN:SI:doc-RG5DOY9EenKovačević Ž.visokošolska delaatributne gramatikeattribute grammarsdisertacijedomain-specific languagesdomensko specifični jezikigenetic programminggenetsko programiranjegrammatical inferencememetic algorithmmemetski algoritmisemantic inferencesemantično sklepanjesklepanje o gramatikahAutomatic compiler/interpreter generation from programs for domain-specific languages using semantic inference| doktorska disertacija|Presented doctoral dissertation describes a research work on Semantic Inference, which can be regarded as an extension of Grammar Inference. The main task of Grammar Inference is to induce a grammatical structure from a set of positive samples (programs), which can sometimes also be accompanied by a set of negative samples. Successfully applying Grammar Inference can result only in identifying the correct syntax of a language. But, when valid syntactical structures are additionally constrained with context-sensitive information the Grammar Inference needs to be extended to the Semantic Inference. With the Semantic Inference a further step is realised, namely, towards inducing language semantics. In this doctoral dissertation it is shown that a complete compiler/interpreter for small Domain-Specific Languages (DSLs) can be generated automatically solely from given programs and their associated meanings using Semantic Inference. For the purpose of this research work the tool LISA.SI has been developed on the top of the compiler/interpreter generator tool LISA that uses Evolutionary Computations to explore and exploit the enormous search space that appears in Semantic Inference. A wide class of Attribute Grammars has been learned. Using Genetic Programming approach S-attributed and L-attributed have been inferred successfully, while inferring Absolutely Non-Circular Attribute Grammars (ANC-AG) with complex dependencies among attributes has been achieved by integrating a Memetic Algorithm (MA) into the LISA.SI toolDoktorska disertacija opisuje raziskovalno delo na področju semantičnega sklepanja, ki je razširitev sklepanja o gramatikah. Glavna naloga sklepanja o gramatikah je zapisati sintaktično strukturo (gramatiko) iz podanih pozitivnih primerov programa, katerim lahko dodamo še negativne primere. Vendar nas sklepanje o gramatikah privede le do ustrezne sintaktične strukture programskega jezika. Toda kadar imajo sintaktično pravilni programi še dodatne omejitve sklepanje o gramatiki ne zadošča in potrebna je razširitev - sklepanje o semantiki, ki nas popelje v semantiko programskega jezika. V doktorski nalogi pokažemo, da je s pomočjo semantičnega sklepanja možno avtomatsko generirati prevajalnik/interpreter za manjše domensko specifične jezike samo na podlagi podanih programov in njihovih pomenov. V ta namen smo razvili orodje LISA.SI kot nadgradnjo generatorja prevajalnikov/interpreterjev LISA z uporabo evolucijskega računanja, ki uspešno preišče ogromen preiskovalni prostor vseh možnih rešitev semantičnega sklepanja. Pri tem smo uspešno pridobili raznovrstne atributne gramatike. Z uporabo genetskega programiranja smo uspešno sklepali na atributne gramatike vrste S in L. Medtem ko je za sklepanje absolutno necikličnih atributnih gramatik (ANC-AG), ki imajo kompleksne odvisnosti med atributi, bila potrebna integracija memetskih algoritmov v orodje LISA.SITEXTvisokošolska delatheses and dissertationsSlovenian National E-content AggregatorNational and University Library of SloveniaUniverza v Mariboru, Fakulteta za elektrotehniko računalništvo in informatiko