An Editor for Helping Novices to Learn Standard ML

This paper describes a novel editor intended as an aid in the learning of the functional programming language Standard ML. A common technique used by novices is programming by analogy whereby students refer to similar programs that they have written before or have seen in the course literature and use these programs as a basis to write a new program. We present a novel editor for ML which supports programming by analogy by providing a collection of editing commands that transform old programs into new ones. Each command makes changes to an isolated part of the program. These changes are propagated to the rest of the program using analogical techniques. We observed a group of novice ML students to determine the most common programming errors in learning ML and restrict our editor such that it is impossible to commit these errors. In this way, students encounter fewer bugs and so their rate of learning increases. Our editor, C Y NTHIA, has been implemented and is due to be tested on st..

Generalised Logic Program Transformation Schemas

Schema-based logic program transformation has proven to be an effective technique for the optimisation of programs. This paper results from the research that began by investigating the suggestions in [11] to construct a more general database of transformation schemas for optimising logic programs at the declarative level. The proposed transformation schemas fully automate accumulator introduction (also known as descending computational generalisation), tupling generalisation (a special case of structural generalisation), and duality laws (which are extensions to relational programming of the first duality law of the fold operators in functional programming). The schemas are proven correct. A prototype schema-based transformation system is evaluated

Suojareleiden mittausketjun signaalinkäsittely

Since the early days of programming and automated reasoning, researchers have developed methods for systematically constructing programs from their specifications. Especially the last decade has seen a flurry of activities including the advent of specialized conferences, such as LOPSTR, covering the synthesis of programs in computational logic. In this paper we analyze and compare three state-of-the-art methods for synthesizing recursive programs in computational logic. The three approaches axe constructive/deductive synthesis, schema-guided synthesis, AA and inductive synthesis. Our comparison is carried out in a systematic way where, for each approach, we describe the key ideas and synthesize a common running example. In doing so, we explore the synergies between the approaches, which we believe are necessary in order to achieve progress over the next decade in this field