Which of the following is a complementary approach to function-oriented approach?

(i) Object-oriented analysis (ii) Object-oriented design (iii) Structured approach (iv) Both object-oriented analysis and design

Requirement analysis’s primary goal is to understand and document stakeholder and user needs, creating a clear specification that drives design, coding, and testing.

• Defined as “identifying, refining, and documenting what a system must do,” it yields an SRS, user stories, or use cases.
• Core steps: elicit needs, analyze/refine, document, validate, and baseline for downstream work ($\text{Requirement Analysis}\rightarrow\text{Clear Requirements}\rightarrow\text{Better Design, Coding, and Testing}$).
• It answers “What does the user need?” unlike design (“How will it be built?”) ($\text{Analysis asks } "What\ is\ needed?" \neq \text{Design asks } "How\ will\ it\ be\ built?"$).
• Coding, architecture, and testing are downstream activities; the exam answer is option (ii) – understanding and documenting user needs.

In compiler design, the lexical analyzer’s sole output is a stream of tokens derived from the source code character stream.

• It scans characters left‑to‑right, grouping them into lexemes that match language patterns.
• Each lexeme is classified into a token category (e.g., ID, NUM, PLUS) possibly with attributes.
• The token stream is handed to the parser, which builds the parse tree or AST.
• Machine code, intermediate code, and parse trees are produced in later compilation phases, not by the lexer.

Algorithms are finite, well‑defined procedures that transform inputs into outputs, and their study emphasizes correctness, efficiency, and scalability.

• Good algorithms exhibit finiteness, definiteness, clear I/O, effectiveness, and reasonable time/space usage.
• Asymptotic analysis uses $O$, $\Theta$, $\Omega$; e.g., merge sort $T(n)=2T(n/2)+O(n)$ gives $O(n\log n)$, binary search yields $O(\log n)$.
• Design paradigms—divide‑and‑conquer, greedy, dynamic programming, backtracking, branch‑and‑bound—fit different problem structures.
• Standard analysis steps: define input size $n$, count dominant operations, derive growth, examine best/average/worst cases, and assess space.
• Core algorithm families include searching (linear, binary), sorting (merge sort), graph traversal (BFS/DFS), and shortest‑path (Dijkstra).