CSS Computer Science Databases, Image Processing & Web Technologies Syllabus

Databases, Image Processing & Web Technologies syllabus — full chapter and topic list

Expand any chapter to see its topics and sub-topics. This is the whole examinable outline for Databases, Image Processing & Web Technologies in CSS Computer Science, not a summary of it.

1. 1

   Relational Database Systems

   5 topics

   • Relational Model & Constraints
   • Entity-Relationship Modeling
   • Relational Algebra & Calculus
   • SQL
   • PL/SQL Procedures & Triggers
2. 2

   Database Design & Processing

   5 topics

   • Functional Dependencies
   • Normalization
   • Storage & Indexing Structures
   • Query Processing & Optimization
   • Transaction Processing & Concurrency
3. 3

   Advanced Databases

   4 topics

   • Distributed Databases
   • Object-Oriented Databases
   • XML & Web Services
   • Database Security & Access Control
4. 4

   Digital Image Processing

   6 topics

   • Image Sensing & Acquisition
   • Sampling & Quantization
   • Geometric Transformations
   • Image Enhancement
   • Color Models & Restoration
   • Morphological Operations & Segmentation
5. 5

   Web Engineering & Technologies

   5 topics

   • Web Application Modeling & Requirements
   • Web Software Architecture
   • Client-Side Programming
   • Server-Side Programming (PHP)
   • Deployment, Testing & Security

Databases, Image Processing & Web Technologies flashcards for CSS Computer Science

19 of 57 cards from the Databases, Image Processing & Web Technologies deck — real questions with worked answers.

1. In the relational model, what is a relation?

   A relation is a set of tuples sharing the same attributes, represented as a two-dimensional table with rows (tuples) and columns (attributes); it has a schema (name + attributes) and an instance (the set of current tuples).

2. Define the degree and cardinality of a relation.

   Degree (arity) is the number of attributes (columns) in the relation; cardinality is the number of tuples (rows) currently in the relation instance.

3. What is a candidate key, and how does it relate to a superkey and a primary key?

   A superkey is any set of attributes that uniquely identifies a tuple. A candidate key is a minimal superkey (no proper subset is a superkey). The primary key is the candidate key chosen to identify tuples; remaining candidate keys are alternate keys.

4. State the entity integrity constraint.

   Entity integrity requires that no attribute of a primary key may have a NULL value, ensuring every tuple is uniquely identifiable.

5. State the referential integrity constraint.

   Referential integrity requires that a foreign key value either match an existing primary/candidate key value in the referenced relation or be wholly NULL; it forbids dangling references.

6. What is a foreign key?

   A foreign key is an attribute (or set) in one relation that references the primary (or candidate) key of another (or the same) relation, establishing a link between the two relations.

7. What is the difference between a domain constraint and a key constraint?

   A domain constraint restricts the set of permitted atomic values for an attribute (its data type/range). A key constraint requires that the values of a key attribute set be unique across all tuples.

8. In ER modeling, distinguish an entity, an entity type, and an entity set.

   An entity is a real-world object; an entity type is the schema/definition (name + attributes) describing a class of such objects; an entity set is the collection of all entities of that type at a given time.

9. What is a weak entity type and how is it identified?

   A weak entity type has no key attributes of its own; it depends on an owner (identifying) entity type and is identified by combining its partial key (discriminator) with the owner's primary key, via an identifying relationship.

10. Define the cardinality ratios of binary relationships in ER modeling.

    They specify how many entities can participate: 1:1 (one-to-one), 1:N (one-to-many), and M:N (many-to-many), constraining how instances of one entity type associate with the other.

11. What is the difference between total and partial participation in an ER relationship?

    Total (mandatory) participation means every entity of the set must take part in the relationship (shown by a double line); partial (optional) participation means some entities may not participate.

12. What is a multivalued attribute in ER modeling, and how is it mapped to relations?

    A multivalued attribute can hold multiple values for one entity (e.g., phone numbers). It is mapped to a separate relation containing the entity's primary key plus the attribute, with both forming the new key.

13. List the fundamental (primitive) operations of relational algebra.

    Selection (σ), Projection (π), Cartesian product (×), Union (∪), Set difference (−), and Rename (ρ). All other operations (join, intersection, division) can be derived from these.

14. What does the selection operator σ do versus the projection operator π?

    Selection σ picks rows (tuples) that satisfy a predicate (horizontal subset). Projection π picks specified columns (attributes) and removes duplicates (vertical subset).

15. Define a natural join in relational algebra.

    A natural join (⋈) combines tuples from two relations that have equal values on all commonly named attributes, automatically eliminating the duplicate join columns from the result.

16. What is the difference between an equi-join and a theta-join?

    A theta-join joins tuples satisfying an arbitrary comparison condition (θ ∈ {<,≤,=,≠,>,≥}). An equi-join is the special case where the condition uses only equality (=); it keeps both join columns (unlike natural join).

17. What does the relational division operation compute?

    Division (R ÷ S) returns the tuples of R that are associated with every tuple of S; it answers 'for all' queries, e.g., 'find suppliers who supply all parts.'

18. What is the difference between tuple relational calculus and domain relational calculus?

    Both are nonprocedural. Tuple relational calculus uses variables ranging over tuples ({t | P(t)}); domain relational calculus uses variables ranging over individual attribute domain values ({<x1,...,xn> | P(x1,...,xn)}).

19. What does it mean for relational algebra and relational calculus to be 'relationally complete'?

    A query language is relationally complete if it can express every query expressible in relational algebra. Codd showed safe relational calculus and relational algebra are equivalent in expressive power.

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