Course information
Lecture:  Monday, Wednesday 9:0010:15am in Braker 001. Lecture notes. 
Recitations:  Recitations start September 8. Logistics Recitation notes. 
Homework:  Assignments and solutions 
Syllabus:  By topic By day By calendar 
Essentials:  Important information about the course that every student must know:

Book(s): 
Programming Languages: Build, Prove, and Compare by
Norman Ramsey (with Samuel L. Kamin). Required. Elements of ML Programming (ML97 edition) by Jeffrey D. Ullman. Recommended. Both books are available at the Tufts Bookstore. 
Readings:  Lots of helpful reference material 
Discussion:  We will use Piazza for questions and discussions: piazza.com/tufts/fall2016/comp105/home. 
Course staff:  Names and photos and office hours 
Grading:  How your grades will be determined. 
Statistics:  Data on how the class is doing. 
Topics
In rough chronological order:
 Abstract syntax and operational semantics
 Functional programming with lists and recursion
 Firstclass and higherorder functions; continuations
 Functional programming with algebraic data types and static types (in ML)
 Type systems and parametric polymorphism
 ML type inference
 Objectorientation and inheritance
 ML Module System
 Lambda calculus; smallstep semantics
Description
COMP105 is a course about the principles of programming languages and their application. The emphasis is on ideas and techniques relevant to practitioners, but includes theoretical foundations crucial for deeper understanding: abstract syntax, formal semantics, type systems, and lambda calculus. Work in the course involves exploring programming languages and features both as a user (by writing programs in those languages), as a language designer (by implementing interpreters for those languages), and as a scholar (by proving mathematical properties of them).
COMP105 is a survey course in programming languages. To succeed in this field, you will combine code and math. The goal of the course is to give you intellectual tools that will help you use, evaluate, choose, and design programming languages. You will learn to ask questions about language safety and classification of errors, type systems, formal semantics, and abstraction mechanisms for both functions and data.
COMP105 provides an introduction to the study of programming languages as an intellectual discipline. The elements of this discipline include specifications based on abstract syntax, lambda calculus, type systems, and dynamic semantics. You must be comfortable with recursion and with basic mathematical ideas and notations for sets, functions, etc.
COMP105 uses the casestudy method to give you experience with languages that go beyond the simple imperative paradigm. Case studies will cover languages from the imperative, functional, and objectoriented families. Example languages may include Standard ML, Smalltalk, and Scheme.
Case studies are reinforced by suitable programming exercises. COMP105 assumes previous experience programming in imperative languages like C, C++, or Java. Good programming skills are essential, and we assume some knowledge of C. Plan to complete ten or twelve programming assignments over the course of the term. The more interesting or amusing assignments include HindleyMilner type inference, arbitraryprecision arithmetic, and some gameplaying programs.
COMP105 is recommended for graduate students, especially those whose primary research interests lie in related fields such as compilers, software systems, or artificial intelligence. Graduate students whose primary interests lie in programming languages may find that COMP105 overemphasizes programming practice and underemphasizes foundations.
Note: COMP105 does not cover implementation of conventional, imperative programming languages, which are covered in COMP 181 (Compilers).