Future Developments-Reference-Cited by-同舟云学术

Future Developments

Published:2013 Issue: Volume: Page:365-374
ISSN:1611-2482
Container-title:Cognitive Technologies
language:
Short-container-title:

Author:

Cervesato Iliano

Publisher

Springer Berlin Heidelberg

Link

http://link.springer.com/content/pdf/10.1007/978-3-642-37747-1_11

Reference18 articles.

1. Agustí, J., Puigsegur, J., Robertson, D., & Schorlemmer, M. (1996). Visual logic programming through set inclusion and chaining. In CADE-13 workshop on visual reasoning, New Brunswick. This paper presents the design of a visual logic programming language that supports visual representation and visual reasoning in a declarative way.

2. Blackwell, A. (2002). First steps in programming: A rationale for attention investment models. In Conference on human-centric computing languages and environments, Arlington (pp. 2–10). IEEE Computer Society. This is the original paper on the attention investment model. It focuses on the initial attitude of non-professional end-users when given tasks that have a programming component (e.g., writing spreadsheet formulas or programming a VCR). In particular, the attention investment model examines the first steps these users take and tries to understand their actions based on task and system at hand.

3. Cervesato, I. (2012). An improved proof-theoretic compilation of logic programs. In A. Dovier & V. Santos Costa (Eds.), 28th international conference on logic programming – ICLP’12, Budapest (Theory and practice of logic programming). Cambridge University Press. This paper describes a general, logic-based, methodology to compile a logic program into an intermediate logical language that can be executed more efficiently. This is in contrast to traditional approaches to compiling logic programs, which took a purely operational view.

4. Ceri, S., Gottlob, G., & Tanca, L. (1990). Logic programming and databases. Berlin/New York: Springer. This expanded version of [CGT89] is an excellent survey with some in-depth analysis of important concepts, in particular semantics, optimizations and the interface with actual databases. It covers the experimental deductive database system of the time at length.

5. Erwig, M., & Burnett, M. (2002). Adding apples and oranges. In Practical aspects of declarative languages, 4th international symposium – PADL’02, Portland (Lecture notes in computer science, Vol. 2257, pp. 173–191). Springer. This paper attempts to rein in the high error rate found in spreadsheets by relying on “units” implicitly inferred from a spreadsheet rather than a rigid system of types. Such units are classified and correlated into dependent units, multiplicities and generalizations, with the aim to capture the user’s intention and fend off mistakes.