CS 394P: Automatic Programming: Lecture Notes

CS 394P: Automatic Programming: Lecture Notes

Copyright © 2005 by Gordon S. Novak Jr.

Permission is granted for individuals to make copies of these notes for personal use, or for instructors to make copies for classroom use.

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2. Automatic Programming

3. Need for Automatic Programming

4. Strategies for AI

5. Problems with Programming Languages

6. Goals of the Course

8. People in Austin

10. Abstract Syntax Tree

11. Substitution and Pattern Matching

12. Binding Lists

13. Substitution

14. Copying and Substitution Functions

15. Program Transformation

16. Rewriting: Program vs. Pattern Matching

17. Transformation Process

18. Pattern Matching

19. Rules for Pattern Matching

20. Equality vs. Matching

21. Equality vs. Matching

22. Matching and Substitution

23. Dot Matching

24. More Complex Rules

25. Transformation

26. Building on Transformation

27. Pattern Matching

30. Correctness of Transformations

31. Top-Down Context

32. Side Effects

33. Uses of Transformations

34. Optimization by Transformation

35. Specialization by Transformation

36. Loop Expansion

37. Advantages of Expansion

38. Language Translation by Transformation

39. Example of Language Translation

40. Knuth-Bendix Algorithm

41. Pattern Optimization Examples

42. Examples ...

43. Examples ...

44. Examples ...

49. Optimization

50. Correctness of Optimization

51. Local and Global Optimization

52. Optimization and Automatic Programming

53. Some Optimization Techniques

54. Program Analysis

55. Basic Block

56. Finding Basic Blocks

57. Relations and Graphs

58. Graph Notations

59. Bit Vector Representations

60. Boolean Matrix Representation of Graph

63. Intervals and Derived Graphs

64. Definition and Reference of Variables

65. Data Flow Analysis for a Block

66. Availability of Expressions

67. Data Flow Analysis for an Interval

68. Dual Assumptions

69. Solving Equations for Derived Graph

70. Busy Variables

71. Variable Uses and Register Assignment

72. Register Allocation by Graph Coloring

73. Overview of Global Optimization

74. Global Optimization and Automatic Programming

75. Loop Transformations

76. Strip Mining

77. Induction Variable Transformation

78. Finite Differencing

79. Example: Computing Squares

80. General Case

81. Finite Differencing for Set Operations

82. Memoization

83. Code Expansion

85. Loop Unrolling

86. Loop Unrolling in Lisp

87. Function Inlining

88. Partial Evaluation

89. Interpretation

90. Partial Evaluation

92. Simple Partial Evaluator

93. Simple Partial Evaluator...

96. Binding-Time Analysis

97. Futamura Projections

98. Generating Extension

99. Parameterized Programs

100. Representation Independence

101. Improvements of Partial Evaluation

102. Improvements ...

103. Partial Evaluation: Matrix

104. Code Expansion with Partial Evaluation

105. Partial Evaluation: Interpreter

106. Specialization

107. Partial Evaluation in OOP

108. Partial Evaluation in Automatic Programming

109. Object-oriented Programming

110. Type Checking

111. Static Type Checking

112. Dynamic Type Checking

113. Generic Functions

114. Object-oriented Programming

115. Access to Objects

116. Internal Implementation is Hidden

117. Encapsulation with OOP

118. Object-oriented Programming Terminology

119. Terminology ...

120. Message Sending

121. Method Lookup

122. Invoking Evaluation Explicitly

123. APPLY and FUNCALL

124. When to Use EVAL, APPLY, FUNCALL

125. FUNCALL Can Save CONSes

126. LAMBDA Expressions

127. Property List Representation

128. Property Lists

129. CLOS Example: ship

130. A Simple OOP System

131. Defining a Class

132. Class Implementation

133. Instance Implementation

134. Creating an Instance

135. Creation of an Instance

136. Getting and Storing Data

137. Defining Methods

138. Implementing Method Definition

139. Associating Selector and Method

140. Sending Messages

141. Implementing Message Sending

142. Extending the Class System

143. {\tt oops} System

144. Making Instances

145. Slot Values

146. Defining Methods

147. Sending Messages

150. ThingLab Examples

151. OOP and Automatic Programming

152. Good Features of OOP

153. Unfortunate Features of OOP

154. Improving OOP Efficiency

155. Why OOP Is Not Enough

156. Top Ten Lies About OOP

157. Aspect-Oriented Programming

158. Aspect Weaving

160. Data Structure Descriptions

161. Reference to Substructures

162. glispobjects

163. Message List

164. Language Features

166. Inheritance

167. Operator Overloading

168. Recursive Expansion

169. Writing Generic Procedures

170. Generics and Views

173. Views as Isomorphisms

174. Requirements of Views

175. Specifying a View

179. Notes on Pipe Example

180. Making Views

181. Data Structure Views: VIEWAS

184. Mathematical Views: MKV

185. Line Segment

186. Example of Line Segment View

187. Line Segment Data Conversion

188. Advantages of Graphical Correspondences

189. MKV: Incremental Equation Solving

190. Basis Variables and Equations

191. Equation Solving

192. Basis Variable and Equations

193. Variable Dependency Graph

194. Reuse through View

195. Storing Basis Variables

196. Data Translation through Views

197. VIP: Programming by Graphical Connections

198. Calculation of the Mass of the Sun

199. Aircraft Position from Radar Data

200. Aircraft Position Program

201. Aircraft Position Program in C

202. Language Translation

203. Automatic Programming Server

204. Automatic Programming Server

205. APS: Example

206. GPS: Component Programming

207. A Simple Program

208. Program Components

209. Substitution Test

210. Generic Software Components

211. Generic Component: Views

212. Generic Component: Views ...

213. Program Representation

214. Component Specification

215. Inference and Propagation

216. Type Propagation Example

217. Modifying Properties

218. Partial Evaluation

219. Updating a {\tt sum}

220. Generic Iterate-Accumulate

222. Software Reuse

223. Krueger's Survey of Software Reuse

224. Software Reuse

225. Evaluation of Reuse Approaches

226. Abstraction

227. Minimizing Cognitive Distance

228. High-level Languages

229. Design and Code Scavenging

230. Source Code Components

231. Software Schemas

232. Application Generators

233. Very-high-level Languages

234. Transformational Systems

235. Software Architectures

236. Krueger's Truisms of Software Reuse

237. V and Refine

238. Form of Rules

239. Refinements: Logic to Code

241. KIDS Specifications

242. Example: $n$ Queens

243. Global Search Theory

244. Goguen: Theory

245. `View' as used by Goguen

246. Deductive Composition of Astronomical

247. Difficulty of Programming

248. SNARK Theorem Prover

249. Astronomical Domain

250. Problem Difficulty

251. Where is the shadow of Io on Jupiter?

252. Shadow of Io Theorem

253. Shadow of Io Program

254. Theorem Proving

255. Result of Ordering

256. Set-of-Support

257. Performance

258. Automated Software Synthesis:

259. Degrees of Freedom

262. Skeletal Plan Fragment Generation

264. Example ...

265. Plan Fragment Elaboration