Introduction

本課程將講授程式語言領域之入門理論與知識,希望培養學生以型式邏輯進行清晰思考的能力,了解邏輯與程式語言、型別系統的密切關係,以及型別系統在程式語言中扮演的角色,使學生能以遞迴/迭構方式理解並解決程式設計問題,能運用軟體工具輔助邏輯推理及證明程式正確性,並具備進一步探索程式語言相關領域的知識基礎。

Announcements

Special Lecture

Monad and Side Effects

函數程式雖然常被說成是沒有副作用的,但是其實藉由函數以及型別的抽象化,尤其是藉由著名的 Monad 概念,可以更精準、更廣泛地表達並駕馭各種副作用。我們先介紹 Monad 的原理,再說明幾種歷久彌新的應用,包括搜尋、句法分析、機率運算等。我們也會跟人工智慧扯上關係,因為不論是要用「自動微分」把機器學習普及化,還是要把清晰易懂的模型變成跑得動的程式,都免不了對副作用進行推理。

Important dates

  1. 03/10
    網站上線
  2. 07/17
    外地實習生報名截止
  3. 07/20
    外校學生修課報名截止
  4. 07/25
    臺大學生報名截止
  5. 07/27
    旁聽報名截止
  6. 08/01
    課程開始
  7. 08/08
    期中停修截止
  8. 08/12
    課程結束

Courses

Functional Programming

This course uses Haskell as a tool to provide an overview of some of the essential knowledge related to function programming in order to bridge the gap with other courses. Starting with structural induction, we will talk about data structures and the inductive definition of functions, and discover that the definition of a function can follow the definition of a data structure. If you want to prove the properties of a function, you can use induction, and the proof will follow the definition of the function. We then turn to the notion of fold, which we find can be regarded as an abstraction of structural induction. Finally, the red-black tree will be used as an example of programming and inductive proofs, in preparation for the subsequent course on dependent types.

Taught by

Shin-Cheng Mu
Institute of Information Science, Academia Sinica

Resources

Handouts & Slides
Source
Practicals & Solutions
Other

Logic

Mathematical proofs are built upon valid inference structures; in formal logic, we express these structures with precise and succinct symbols, and study their properties. This course module focuses on the natural deduction system of propositional intuitionistic logic, introduces the basic syntactic and semantic proof methods used in formal logic, and points out the intimate relationship between logic and computation, leading into the topic of dependently typed programming. By studying the inference structures formally, this course module also introduces the necessary proof techniques used in other modules.

Taught by

Josh Ko
Institute of Information Science, Academia Sinica

Resources

Slides

λ-Calculus

Nowadays many languages such as Haskell and Agda are based on variants of λ-calculus. In this course module, we will investigate λ-calculus and its notions and properties mathematically. For example, we will define computation and computational equivalence; after introducing types, we show how ‘a well-typed program does not go wrong’. Apart from theoretical interests, we also discuss a prevalent language feature —polymorphism— which has been applied to solve the code duplication problem in practice. Continuing into the dependently typed programming module, we will use Agda to implement λ-calculus and prove its properties.

Taught by

Liang-Ting Chen
Institute of Information Science, Academia Sinica

Resources

Slides

Dependently Typed Programming

The expressiveness of dependent types far exceeds that of type systems in mainstream languages, so that properties that would otherwise need to be proved additionally can be written directly as dependent types. As we provide more information to the type checker through the dependent type, the latter can in turn tell us what is known and what is yet to be satisfied, and write the correct program interactively. Mathematical theorems and proofs, when expressed in the language of the dependent type, not only ensure that the inference is correct, but also that it is computationally meaningful. Here mathematics, logic and computation become one, forming a solid basis for the design of a new generation of programming languages.

Taught by

Shin-Cheng Mu
Institute of Information Science, Academia Sinica
Josh Ko
Institute of Information Science, Academia Sinica
Liang-Ting Chen
Institute of Information Science, Academia Sinica

Resources

Agda Installation Guide
Source
Other

Special Topic: Monad and Side Effects

函數程式雖然常被說成是沒有副作用的,但是其實藉由函數以及型別的抽象化,尤其是藉由著名的 Monad 概念,可以更精準、更廣泛地表達並駕馭各種副作用。我們先介紹 Monad 的原理,再說明幾種歷久彌新的應用,包括搜尋、句法分析、機率運算等。我們也會跟人工智慧扯上關係,因為不論是要用「自動微分」把機器學習普及化,還是要把清晰易懂的模型變成跑得動的程式,都免不了對副作用進行推理。

Taught by

Chung‑Chieh Shan
Department of Computer Science, Indiana University

Resources

Slides
Practicals