The exercises in this book are intended to deepen your understanding of ml and improve your programming skills. But such exercises cannot turn you into a programmer, let alone a software engineer. A project is more than a large programming exercise; it involves more than programming. It demands careful preparation: background study, analysis of requirements, design. The finished program should be evaluated fairly but thoroughly.

Each suggestion is little better than a hint, but with a little effort, can be developed into a proper proposal. Follow the attached references and prepare a project description including a statement of objectives, a provisional timetable and a list of required resources. The next stage is to write a detailed requirements analysis, listing all functions in sufficient detail to allow someone else to carry out eventual testing. Then specify the basic design; ml functors and signatures can describe the main components and their interfaces.

The preparatory phases outlined above might be done by the instructor, a student or a team of students. This depends upon the course aims, which might be concerned purely with ml, with project management, or with demonstrating some methodology of software engineering. The final evaluation might similarly be done by the instructor, the implementor or another team of students.

The evaluation should consider to what extent the program meets its objectives.