. REVIEW .
April 2015, Vol. 58 041301:1041301:20
Key techniques for 5G wireless communications:
network architecture, physical layer,
and MAC layer perspectives
MA Zheng1 , ZHANG ZhengQuan1
CS1356-COMPILER DESIGN LAB
LIST OF EXPERIMENTS:
CYCLE-1 (5 WEEKS)
1. Implementation of token separation.
2. Implementation of symbol table.
3. Implementation of Lexical Analysis in C
4. Implementation of Lexical Analysis in LEX
An operating system abstraction representing an instance of a running computer
Consists of data, stack, register contents, and the state specific to the underlying
Can have one or more
A resource can be a logical, such as a shared file, or physical, such as a CPU (a node of
the distributed system). One of the functions of a distributed operating system is to assign
processes to the nodes
DISTRIBUTED FILE SYSTEMS
A file system is responsible for the organization, storage, retrieval, naming, sharing, and
protection of files. File systems provide directory services, which convert a file name
(possibly a hierarchica
Department of Computer Science and Engineering
Computer Science & Engineering
Compiler Design Lab Manual
BALAJI INSTITUTE OF TECHNOLOGY AND
Department of computer science & engineering
Approved & Reviewed
Case Study: The Andrew File System (AFS)
AFS differs markedly from NFS in its design and implementation. The differences are primarily
attributable to the identification of scalability as the most important design goal. AFS is designed
to perform well wit
1. Define the following terms: Compiler, Interpreter, Translator and differentiate
2. Differentiate between lexeme, token and pattern.
3. What are the issues in lexical analysis.
4. Explain in detail the process of compilation. Illustrate th
CSC7230 Homework 2
Each question contributes 10% of the total mark
Due date: 19/11/2002
Submission: Hand in on class or send email to [email protected] with
student name and student ID. Please name your file with your SID.
Is it conceivably usefu
Generate 4096 data samples from a chirp pattern. One may extend
sampling size from 4096 to million to mimic real big data.
Mimic Real Big Data:
Data sets that are too large and complex to manipulate or interrogate with standard
methods or tools.