Isra University Hyderabad Campus
A hallmark of the future
The university is owned by Isra Islamic Foundation, a non-profit organization, certified by Pakistan Centre for Philanthropy (PCP). The University is highly ranked by HEC. The easily accessible and beautiful campuses provide services that create an academic environment of learning and intellectual growth.
The course focuses generally on the advanced concepts prevail in databases. This course covers files storage and structures; query processing component of a relational database system; fundamental knowledge of concurrency control and database recovery; transaction Processing Concepts and Theory; concurrency control techniques; database recovery techniques; relational algebra; physical storage; indexing and hashing; query processing and optimization; object oriented databases and distributed databases.
Quality Assurance Beyond Testing: Defect Prevention and Process
Improvement, Software Inspection, Formal Verification, Fault Tolerance and
Failure Containment, Comparing Quality Assurance Techniques and
Quantifiable Quality Improvement: Feedback Loop and Activities for
Quantifiable Quality Improvement, Quality Models and Measurements, Defect
Classification and Analysis.
Risk Identification for Quantifiable Quality Improvement, Software Reliability
calculus; negation disjunction and conjunction; implication and equivalence;
truth tables; predicates; quantifiers; natural deduction; rules of Inference;
methods of proofs; use in program proving; resolution principle; Set theory:
Paradoxes in set theory; inductive definition of sets and proof by induction;
Relations, representation of relations by graphs; properties of relations,
equivalence relations and partitions; Partial orderings; Linear and well- ordered sets; Functions: mappings, injection and surjection, composition of
functions; inverse functions; special functions; Peano postulates; Recursive
function theory; Elementary combinatorics; counting techniques; recurrence
relation; generating functions.
Graph Theory: elements of graph theory, Planar Graphs, Graph Colouring,
Euler graph, Hamiltonian path, trees and their applications.
Graphical representation of Data Stem-and Lead plot, Box-Cox plots, measures of central tendencies and dispersion, moments of frequency
distribution; Counting techniques, introduction to probability, sample space,
events, laws of probability, Conditional probability and Baye’s theorem with
application to random variable (Discrete and continuous) Binomial, Poisson,
Geometric, Negative Binomial Distributions; Exponential Gamma and Normal distributions; Regression and Correlation, Estimation and testing of
hypotheses, use of elementary statistical packages for explanatory Data