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• W4256350760 abstract "This issue marks the first real column in the Semantics series. I am pleased that the guest author, Achim Jung, agreed to write this column. Achim is renowned for his research in denotational semantics, and in particular in domain theory, and he also established himself as a leader in the UK computer science academic community during his two terms as Head of Department at the University of Birmingham. Achim has chosen to focus on pedagogy with a column entitled, Teaching Denotational Semantics. Achim played a pivotal role in establishing the Midlands Graduate School in the Foundations of Computer Science, which runs an annual series of summer schools and other events. He was instrumental in obtaining initial funding for the series, assuring its success. Achim uses the course he teaches at the MGS summer school as a guide for what to include in a denotational semantics course, providing both a great template from which to work, as well as a clear rationale for why a short course on denotational semantics should be taught in the way he outlines. It's an excellent overview that offers guidance for those who are just starting to teach such a course, as well as a source of new ideas for those who have an established course already in hand. Above and beyond the outline Achim gives us, there is an equally important question that his column answers: Why should we teach denotational semantics? Denotational semantics courses are fairly well represented in Europe, where the area has its origins. But on my side of the Atlantic, semantics is relegated to a day, or at best a week, in programming language courses. Achim's outline provides a laundry list of reasons why denotational semantics deserves a full course, offering a number of lessons that are applicable across the whole range of computer science. For instance, such a course demonstrates: ---Abstraction: abstracting away from low-level details allows one to treat a problem on a more abstract level, where it can be understood better and more easily solved. This teaches students to avoid irrelevant details, and to focus on the issues at the heart of the problem. ---Modularity: breaking a problem down into subproblems that are easier to solve, and then using solutions to the subproblems to build a solution to the main problem. This is one of the great lessons of abstract mathematics that comes to the fore in denotational semantics. ---Proof techniques: the stock and trade of denotational semantics is proving properties of programs and it provides numerous proof tools for this purpose. Achim points out several techniques that are standard components of the approach: structural induction, term model construction, logical relations and domain theory. ---Mathematical thinking: using mathematics as both a language in which to phrase problems precisely, and as a tool kit for solving those problems. These are some of the benefits of a semantics course for computer science students. As for mathematics students, Achim argues that they are not interested in such a course. That may be true, but mathematics students also have a lot to learn from a course like Achim's: it demonstrates how mathematics can be used effectively to solve hard problems in a related discipline. Denotational semantics also offers a great middle ground between the abstract definition-theorem-proof world of abstract mathematics, and the reliance on combinatorics and calculations prevalent in complexity theory and algorithmic analysis. This latter point applies as well for computer science students, who should find in a semantics course a chance to experience abstract reasoning as a means for gaining a broader perspective about their discipline, as well as a new suite of tools to use in solving its problems." @default.
• W4256350760 created "2022-05-12" @default.
• W4256350760 date "2014-10-14" @default.
• W4256350760 modified "2023-09-30" @default.
• W4256350760 title "Session details: Semantics" @default.
• W4256350760 doi "https://doi.org/10.1145/3262517" @default.
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