On the discovery of semantically meaningful sql constraints from armstrong samples foundations, implementation, and evaluation
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On the discovery of semantically meaningful sql constraints from armstrong samples foundations, implementation, and evaluation
On the Discovery of Semantically Meaningful SQL Constraints from Armstrong Samples: Foundations, Implementation, and EvaluationbyVan Tran Bao LeA thes On the discovery of semantically meaningful sql constraints from armstrong samples foundations, implementation, and evaluation sis submitted to the Victoria University of Wellington in fulfilment of the requirements for the degree of Doctor of Philosophy in Information Management.Victoria University of Wellington 2014AbstractA database is said to be C-ArmstronỊỊ for a finite set >: of data dependencies in a class c if the d On the discovery of semantically meaningful sql constraints from armstrong samples foundations, implementation, and evaluation atabase satisfies all data dependencies in >' and violates all data dependencies in c that are not implied by s. Therefore, Armstrong databases are coOn the discovery of semantically meaningful sql constraints from armstrong samples foundations, implementation, and evaluation
ncise, user-friendly representations of abstract data dependencies that can be used to judge, justify, convey, and test the understanding of database On the Discovery of Semantically Meaningful SQL Constraints from Armstrong Samples: Foundations, Implementation, and EvaluationbyVan Tran Bao LeA thes On the discovery of semantically meaningful sql constraints from armstrong samples foundations, implementation, and evaluation Structural and computational properties of Armstrong databases have been deeply investigated in Codd's Turing Award winning relational model of data. Armstrong databases have been incorporated in approaches towards relational database design. They have also been found useful for the elicitation of On the discovery of semantically meaningful sql constraints from armstrong samples foundations, implementation, and evaluation requirements, the semantic sampling of existing databases, and the specification of schema mappings.This research establishes a t(X)lbox of ArmstrongOn the discovery of semantically meaningful sql constraints from armstrong samples foundations, implementation, and evaluation
databases for SQL data. This is challenging as SQL data can contain null marker occurrences in columns declared NULL, and may contain duplicate rows. On the Discovery of Semantically Meaningful SQL Constraints from Armstrong Samples: Foundations, Implementation, and EvaluationbyVan Tran Bao LeA thes On the discovery of semantically meaningful sql constraints from armstrong samples foundations, implementation, and evaluation arid without duplicate rows. For the thesis, two popular interpretations of null markers are considered: the no information interpretation used in SQIand the exists but unknown interpretation by Codd. Furthermore, the study Ls limited to the popular class c of functional dependencies. However, the p On the discovery of semantically meaningful sql constraints from armstrong samples foundations, implementation, and evaluation resence of duplicate rows means that the class of uniqueness constraints is no longer subsumed by the class of functional dependencies, in contrast toOn the discovery of semantically meaningful sql constraints from armstrong samples foundations, implementation, and evaluation
the relational model of data. As a first contribution a provably-correct algorithmis developed that computes Armstrong databases for an arbitrarily gOn the Discovery of Semantically Meaningful SQL Constraints from Armstrong Samples: Foundations, Implementation, and EvaluationbyVan Tran Bao LeA thes On the discovery of semantically meaningful sql constraints from armstrong samples foundations, implementation, and evaluation ons of the associated implication problem that are also established in this thesis. While the problem to decide whether a given database is Armstrong for a given set of such constraints is precisely exponential, our algorithm computes an Armstrong database with a number of rows that is at most quadr On the discovery of semantically meaningful sql constraints from armstrong samples foundations, implementation, and evaluation atic in the number of rows of a minimum-sized Armstrong database. As a second contribution the algorithms are implemented in form of a design tool. UsOn the discovery of semantically meaningful sql constraints from armstrong samples foundations, implementation, and evaluation
ers of the t(X)l can therefore inspect Armstrong databases to analyze their current design choice E. Intuitively, Armstrong databases are useful for tOn the Discovery of Semantically Meaningful SQL Constraints from Armstrong Samples: Foundations, Implementation, and EvaluationbyVan Tran Bao LeA thes On the discovery of semantically meaningful sql constraints from armstrong samples foundations, implementation, and evaluation ived as meaningless before the inspection of an Armstrong database. As a final contribution, measures are introduced that formalize the term “useful" and it is shown by some detailed experiments that Armstrong tables, as computed by the tool, are indeed useful.In summary, this research establishes a On the discovery of semantically meaningful sql constraints from armstrong samples foundations, implementation, and evaluation toolbox of Armstrong databases that can be applied by database designers to concisely visualize constraints on SQL data. Such support can lead to datOn the discovery of semantically meaningful sql constraints from armstrong samples foundations, implementation, and evaluation
abase designs that guarantee efficient data management in practice.AcknowledgmentsMy first acknowledgement is to Sebastian I .ink. You not only guidedOn the Discovery of Semantically Meaningful SQL Constraints from Armstrong Samples: Foundations, Implementation, and EvaluationbyVan Tran Bao LeA thes On the discovery of semantically meaningful sql constraints from armstrong samples foundations, implementation, and evaluation hank you, Sebastian, for your patient guidance, enthusiastic encouragement, and excellent support that made it possible for me to complete this work. Your positive outlook and confidence in my capabilities inspired me, making the tough PhD journey become enjoyable. It has been an honour to be your P On the discovery of semantically meaningful sql constraints from armstrong samples foundations, implementation, and evaluation hD student, and 1 could not have imagined having a better supervisor for my PhD study.Thanks also to Flavio Ferrarotti. Despite your busy schedule, yoOn the discovery of semantically meaningful sql constraints from armstrong samples foundations, implementation, and evaluation
u always made yourself available to clarify my doubts. Your guidance and advice served me well, and I owe you my heartfelt appreciation. I also thank On the Discovery of Semantically Meaningful SQL Constraints from Armstrong Samples: Foundations, Implementation, and EvaluationbyVan Tran Bao LeA thes On the discovery of semantically meaningful sql constraints from armstrong samples foundations, implementation, and evaluation s are also extended to Dan Domer, Vai Hooper, and Pak Yoong. Your open doors and ready support were much appreciated. Thanks to Usha Varatharaju, Jean Grant, Nicole Green, and Tiso Ross. You helped me navigate bureaucratic pathways. My thanks also go to Dion Peszynski. Without you, the web applicati On the discovery of semantically meaningful sql constraints from armstrong samples foundations, implementation, and evaluation on developed for this work could not go live.Thanks to the many other helpful and generous people at Victoria University of Wellington and particularlOn the discovery of semantically meaningful sql constraints from armstrong samples foundations, implementation, and evaluation
y the academic, administrative, and technical staff of the School of Information Management: Jocelyn Granc-iiiivfield, Chem Li Liew, Gillian Oliver, LOn the Discovery of Semantically Meaningful SQL Constraints from Armstrong Samples: Foundations, Implementation, and EvaluationbyVan Tran Bao LeA thes On the discovery of semantically meaningful sql constraints from armstrong samples foundations, implementation, and evaluation the School of Information Management (SIM) at Victoria University of Wellington, and its members will always remain dear to me.I would especially like to acknowledge Palve Mogin and Hui Ma in the School of Engineering and Computer Science at Victoria University of Wellington, and Nguyen Thi Thanh Ta On the discovery of semantically meaningful sql constraints from armstrong samples foundations, implementation, and evaluation m in the Computer Science Department at Lotus University of Vietnam. You have been there to kindly assist me during the data gathering process. ThanksOn the discovery of semantically meaningful sql constraints from armstrong samples foundations, implementation, and evaluation
to all the computer science students for participating in my experiments. Without them, I simply could not have conducted empirical studies and complOn the Discovery of Semantically Meaningful SQL Constraints from Armstrong Samples: Foundations, Implementation, and EvaluationbyVan Tran Bao LeA thes On the discovery of semantically meaningful sql constraints from armstrong samples foundations, implementation, and evaluation the distance. Thanks to my husband, Nguyen Trong Due, for your unconditional support by being willing to share the ups and downs of the PhD process despite the massive challenges you confronted when making a big move to New Zealand to support me. Thanks also to my great friends in New Zealand and in On the discovery of semantically meaningful sql constraints from armstrong samples foundations, implementation, and evaluation Vietnam for your support and encouragement, for stepping in when things got tough, and making me take time out for a bit of fun every now and then.On the Discovery of Semantically Meaningful SQL Constraints from Armstrong Samples: Foundations, Implementation, and EvaluationbyVan Tran Bao LeA thesOn the Discovery of Semantically Meaningful SQL Constraints from Armstrong Samples: Foundations, Implementation, and EvaluationbyVan Tran Bao LeA thesGọi ngay
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