• Generative Programming — programs are synthesized by other programs
• Compositional Programming — programs are assembled by composing prefabricated parts
• Domain-Specific Languages (DSL) — domain-specific notations that simplify program specification
• Model Driven Engineering  (MDE) -- programs are specified as and synthesized from models
• Automatic Programming — efficient programs are synthesized from declarative specifications
• Program Analysis — tools that evaluate properties of programs

The integration of the above seems daunting. Yet a spectacular example of their integration was realized thirty years ago: relational query optimization (RQO). A relational query is specified in SQL, a parser maps it to an inefficient relational algebra expression, a query optimizer optimizes the expression automatically, and an efficient query evaluation program is generated from the optimized expression. SQL is a prototypical declarative DSL. Query evaluation programs are specified as compositions of relational algebra operations; relational algebra is a prototype for compositional programming. Query optimizers achieve automatic programming by rewriting an inefficient expression/program to a semantically equivalent but more efficient expression/program. The cost models that drive expression optimization are examples of program analysis. Mapping a relational algebra expression to an efficient program is generative programming and is an elementary example of model driven engineering.

A "holy grail" of Software Engineering is to replicate the success of RQO in other domains. Feature Oriented Software Development is a generalization, and its ideas are at the confluence next-generation research topics in software modularity, program design and program synthesis: OO design, product-lines, program refactoring, model driven engineering, program evolution, and program transformations.

Prior offerings of this course lead to student publications and research degrees (M.Sc. and Ph.D), some -- not all -- are listed below:

• Java.  All assignments and lecture examples are in Java or Java dialects.
• Compilers and Grammars. Basic familiarity with grammars is assumed.
• Object-Orientation.  Basic familiarity with OO concepts, OO refactoring, UML models are assumed.
• An Open Mind.

Lecture notes will be presented online (after the lecture) as downloadable PPTX files.  A special font is used in the titles of lecture slides -- you can download it here. Links to the lectures are given below in the Course Outline. There is an optional text for this course:

• B. Pierce, Category Theory for Computer Scientists

We will use prototype Java-based tools that may be updated periodically during the course.  Some of the tools that we will use are posted below.  Note that you'll need about 500MB+ for this software.

• ATS (AHEAD Tool Suite) is a command-line set of tools that runs on both Windows (preferred) and Linux, and requires tool support from several vendors.
• FeatureIDE -- An Eclipse plug-in for Feature-Oriented Software Development that uses AHEAD, among other tools.
• CIDE -- an Eclipse plug-in for FOSD that illustrates virtual separation of concerns.  Note: do not install CIDE and FeatureIDE on the same instance of Eclipse.
• FeatureMapper -- a tool that integrates software product line and model driven engineering.

• YUML -- this is a neat, free, web-based tool for drawing UML diagrams.

• More may be added.

• 10% class participation, quizzes
• 30% homework
• 40% project and presentation (if final exam is given, 60% otherwise)
• 20% final exam

Each student (or group of students) will complete an approved project by the end of the class.  A classroom presentation on every project is expected.  Details on the projects will be announced later.

• Submitting homework: create a zip file <yourname>.zip, and run on a linux box:
  
  > turnin -- submit dsb cs392F <yourname>.zip
  
• Mandatory instructions on submissions is listed here.

This year, group projects will be assigned at the beginning of the semester, where the first few lectures (past the introductory lecture) will be on various projects that could be worked on in groups.  I will entertain singleton projects (meaning specific projects that an individual student will propose) that are outside the group projects I present in class.