Language Processors (CMPE424) Course Detail

Course Name Course Code Season Lecture Hours Application Hours Lab Hours Credit ECTS
Language Processors CMPE424 3 0 0 3 5
Pre-requisite Course(s)
N/A
Course Language English
Course Type N/A
Course Level Bachelor’s Degree (First Cycle)
Mode of Delivery Face To Face
Learning and Teaching Strategies Lecture.
Course Coordinator
Course Lecturer(s)
Course Assistants
Course Objectives The objective of this course is to provide necessary skills in developing a language processor as applied to compiler generation.
Course Learning Outcomes The students who succeeded in this course;
  • Use syntactic analyzers in the context of compiler construction
  • Appraise higher level programming languages concepts
  • Design a scanner and a parser as a part of a compiler
Course Content Fundamental concepts of compilation and interpretation; single-pass and multiple-pass language translators; lexical analyzer; top-down parsing, and LL(1) grammars; recursive descent method; bottom-up parsing; shift reduce technique; operator precedence grammar, LR(0) and SLR(1) grammars; syntax directed translation; error processing and recovery; s

Weekly Subjects and Releated Preparation Studies

Week Subjects Preparation
1 Introduction to Compiling Chapter 1 (main text)
2 A Simple One-Pass Compiler Chapter 2
3 Lexical Analysis Chapter 3
4 Syntax Analysis Chapter 4
5 Syntax Directed Translation Chapter 5
6 Syntax Directed Translation Chapter 5
7 Type Checking Chapter 6
8 Run-time Environments Chapter 7
9 Run-time Environments Chapter 7
10 Run-time Environments Chapter 7
11 Intermediate Code Generation Chapter 8
12 Code Generation Chapter 9
13 Code Generation Chapter 9
14 Code Optimization Chapter 10

Sources

Course Book 1. Alfred V. Aho, Monica S. Lam, Ravi Sethi, Jeffrey D. Ullman, Compilers: Principles, Techniques, and Tools (2nd Edition), 2006, ISBN: 0321486811. (Dragon Book)
Other Sources 2. 1. Steven Muchnick, Advanced Compiler Design and Implementation, 1997, Morgan Kaufmann Publishers, ISBN:1-55860-320-4.
3. 2. Doug Brown, John Levine, Tony Mason, UNIX Programming Tools: Lex & Yacc, O’Reilly, 1992.
4. 3. Dick Grune, Henri E. Bal, Ceriel J.H. Jacobs, and Koen Langendoen VU University Amsterdam, Amsterdam, The Netherlands. John Wiley & Sons, Ltd., pp. 736 + xviii; ISBN 0471976970, 2000.
5. 4. http://dinosaur.compilertools.net/yacc/.
6. 5. Andrew W. Appel, Jens Palsberg, “Modern Compiler Implementation in Java (2nd edition)”, Cambridge Univ. Press, ISBN-13: 9780521820608, 2002.

Evaluation System

Requirements Number Percentage of Grade
Attendance/Participation - -
Laboratory - -
Application - -
Field Work - -
Special Course Internship - -
Quizzes/Studio Critics - -
Homework Assignments 2 15
Presentation - -
Project 1 30
Report - -
Seminar - -
Midterms Exams/Midterms Jury 1 25
Final Exam/Final Jury 1 30
Toplam 5 100
Percentage of Semester Work 70
Percentage of Final Work 30
Total 100

Course Category

Core Courses
Major Area Courses X
Supportive Courses
Media and Managment Skills Courses
Transferable Skill Courses

The Relation Between Course Learning Competencies and Program Qualifications

# Program Qualifications / Competencies Level of Contribution
1 2 3 4 5
1 Adequate knowledge in mathematics, science and subjects specific to the computer engineering discipline; the ability to apply theoretical and practical knowledge of these areas to complex engineering problems. X
2 The ability to identify, define, formulate and solve complex engineering problems; selecting and applying proper analysis and modeling techniques for this purpose. X
3 The ability to design a complex system, process, device or product under realistic constraints and conditions to meet specific requirements; the ability to apply modern design methods for this purpose. X
4 The ability to develop, select and utilize modern techniques and tools essential for the analysis and determination of complex problems in computer engineering applications; the ability to utilize information technologies effectively. X
5 The ability to design experiments, conduct experiments, gather data, analyze and interpret results for the investigation of complex engineering problems or research topics specific to the computer engineering discipline.
6 The ability to work effectively in inter/inner disciplinary teams; ability to work individually X
7 Effective oral and writen communication skills in Turkish; the ability to write effective reports and comprehend written reports, to prepare design and production reports, to make effective presentations, to give and to receive clear and understandable instructions.
8 The knowledge of at least one foreign language; the ability to write effective reports and comprehend written reports, to prepare design and production reports, to make effective presentations, to give and to receive clear and understandable instructions.
9 Recognition of the need for lifelong learning; the ability to access information, to follow recent developments in science and technology.
10 The ability to behave according to ethical principles, awareness of professional and ethical responsibility;
11 Knowledge of the standards utilized in software engineering applications
12 Knowledge on business practices such as project management, risk management and change management;
13 Awareness about entrepreneurship, innovation
14 Knowledge on sustainable development
15 Knowledge on the effects of computer engineering applications on the universal and social dimensions of health, environment and safety;
16 Awareness of the legal consequences of engineering solutions
17 An ability to describe, analyze and design digital computing and representation systems.
18 An ability to use appropriate computer engineering concepts and programming languages in solving computing problems. X

ECTS/Workload Table

Activities Number Duration (Hours) Total Workload
Course Hours (Including Exam Week: 16 x Total Hours) 16 3 48
Laboratory
Application
Special Course Internship
Field Work
Study Hours Out of Class 16 2 32
Presentation/Seminar Prepration
Project 1 15 15
Report
Homework Assignments 2 5 10
Quizzes/Studio Critics
Prepration of Midterm Exams/Midterm Jury 1 10 10
Prepration of Final Exams/Final Jury 1 15 15
Total Workload 130