Modular average case analysis: Language implementation and extension

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dc.contributor.advisor Schellekens, Michel P. en
dc.contributor.author Gao, Ang
dc.date.accessioned 2013-04-27T14:28:41Z
dc.date.available 2013-04-27T14:28:41Z
dc.date.issued 2013
dc.date.submitted 2013
dc.identifier.citation Gao, A. 2013. Modular average case analysis: Language implementation and extension. PhD Thesis, University College Cork. en
dc.identifier.endpage 240
dc.identifier.uri http://hdl.handle.net/10468/1089
dc.description.abstract Motivated by accurate average-case analysis, MOdular Quantitative Analysis (MOQA) is developed at the Centre for Efficiency Oriented Languages (CEOL). In essence, MOQA allows the programmer to determine the average running time of a broad class of programmes directly from the code in a (semi-)automated way. The MOQA approach has the property of randomness preservation which means that applying any operation to a random structure, results in an output isomorphic to one or more random structures, which is key to systematic timing. Based on original MOQA research, we discuss the design and implementation of a new domain specific scripting language based on randomness preserving operations and random structures. It is designed to facilitate compositional timing by systematically tracking the distributions of inputs and outputs. The notion of a labelled partial order (LPO) is the basic data type in the language. The programmer uses built-in MOQA operations together with restricted control flow statements to design MOQA programs. This MOQA language is formally specified both syntactically and semantically in this thesis. A practical language interpreter implementation is provided and discussed. By analysing new algorithms and data restructuring operations, we demonstrate the wide applicability of the MOQA approach. Also we extend MOQA theory to a number of other domains besides average-case analysis. We show the strong connection between MOQA and parallel computing, reversible computing and data entropy analysis. en
dc.description.sponsorship Science Foundation Ireland (07/IN.1/I977) en
dc.format.mimetype application/pdf en
dc.language.iso en en
dc.publisher University College Cork en
dc.rights © 2013, Ang Gao en
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/3.0/ en
dc.subject Module average case analysis en
dc.subject Randomness preservation en
dc.subject Language design en
dc.subject Data structures and algorithm analysis en
dc.subject Parallel computing en
dc.subject.lcsh Parallel processing (Electronic computers) en
dc.subject.lcsh Software engineering. en
dc.title Modular average case analysis: Language implementation and extension en
dc.type Doctoral thesis en
dc.type.qualificationlevel Doctoral en
dc.type.qualificationname PhD (Science) en
dc.internal.availability Full text available en
dc.check.info No embargo required en
dc.description.version Accepted Version
dc.contributor.funder Science Foundation Ireland en
dc.description.status Not peer reviewed en
dc.internal.school Computer Science en
dc.check.type No Embargo Required
dc.check.reason No embargo required en
dc.check.opt-out Not applicable en
dc.thesis.opt-out FALSE *
dc.check.embargoformat Not applicable en
ucc.workflow.supervisor m.schellekens@cs.ucc.ie *
ucc.workflow.supervisor m.schellekens@cs.ucc.ie *


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