Definition
A database is a collection of data items operated on concurrently by several programs. A set of values for the data items is called a database state. It is consistent if the values satisfy the integrity constraints specified for the database. Arbitrary interleaving of the executions of the programs may affect the consistency of the database. The executions that preserve the consistency are called correct executions. The notion of serializability helps to identify correct executions. It is based on the transaction concept: a transactionis a partially ordered set of atomic steps that constitute an execution of a program, with the property that, when executed alone, it transforms a consistent database state into another consistent one. Examples of atomic steps are read and write of a data item, increment and decrement on a counter object, enqueue and dequeue on a queue object, etc. The sequence of steps in an execution...
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Recommended Reading
Bernstein P.A., Shipman D.W., and Wong W.S. Formal aspects of serializability in database concurrency control. IEEE Trans. Software Eng., SE-5:203–215, 1979.
Eswaran K.P., Gray J.N., Lorie R.A., and Traiger I.L. The notion of consistency and predicate locks in a database system. Commun. ACM, 19:624–633, 1976.
Farrag A.A. and Özsu M.T. Using semantic knowledge of transactions to increase concurrency. ACM Trans. Database Syst., 14(4):503–525, 1989.
Garcia-Molina H. Using semantic knowledge for transactions processing in a distributed database. ACM Trans. Database Syst., 8(2):186–213, 1983.
Garcia-Molina H. and Salem K. Sagas. In Proc. ACM SIGMOD Int. Conf. on Management of Data, 1987, pp. 249–259.
Ibaraki T., Kameda T., and Minoura T. Serializability with constraints. ACM Trans. Database Syst., 12(3):429–452, 1987.
Lynch N.A. Multilevel atomicity – a new correctness criterion for database concurrency control. ACM Trans. Database Syst., 8(4):485–502, 1983.
Moss T.E.B. 1981.Nested Transactions: An Approach to Reliable Distributed Computing. MIT Laboratory for Computer Science, Cambridge, Massachusetts, Ph.D. Thesis, Technical Report MIT/LCS/TR-260,
Papadimitriou C.H. The serializability of concurrent database updates. J. ACM, 26:631–653, 1979.
Papadimitriou C.H. and Kanellakis P. On concurrency control by multiple versions. ACM Trans. Database Syst., 9:(1):89–99, 1984.
Vidyasankar K. Generalized theory of serializability. Acta Inf., 24:105–119, 1987.
Vidyasankar K. Unified theory of database serializability. Fundamenta Inf., 14(2):147–183, 1991.
Vidyasankar K. Generalized relative serializability. In Proc. of 9th Int. Conf. on Management of Data, 1998, pp. 313–327.
Vidyasankar K. and Dampney C.N.G. Version consistency and serializability in design databases. In Proc. 2nd Int. Conf. on Database Theory, 1988, pp. 368–382.
Weikum G. and Vossen G. Transactional information systems – theory, algorithms, and the practice of concurrency control and recovery. Morgan Kaufmann, 2002.
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Vidyasankar, K. (2009). Serializability. In: LIU, L., ÖZSU, M.T. (eds) Encyclopedia of Database Systems. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-39940-9_344
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DOI: https://doi.org/10.1007/978-0-387-39940-9_344
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