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Michael Spenke

dblp:30/1097 · DBLP profile ↗
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5ranked-venue papers
5as first author
0since 2021 · last 2003
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Human-computer interaction and ubiquitous computing · 3 · 3 first-authorArtificial intelligence and machine learning · 1 · 1 first-authorSoftware engineering, systems software and programming languages · 1 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Human-computer interaction and pervasive computing
2 papers
Interaction techniques and input · 72% User interface design and tools · 28%
Software engineering, system software, and programming languages
1 paper
Programming languages and type systems · 100%

Topics — the 2 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Interaction techniques and input › surface computing
interactive table
0.011996
FOCUS: The Interactive Table for Product Comparison and Selection · ACM Symposium on User Interface Software and Technology 1996
Programming languages and type systems
logic programming
0.011989
A spreadsheet interface for logic programming · CHI 1989

Methods — techniques the papers use, named apart from their topics

programming by example · 0.0constraint programming · 0.0
YearPublicationVenuePosition
2003 Visualization and Analysis of Formula One Racing Results with InfoZoom - the Demo
Michael Spenke, Christian Beilken
INTERACT1
2001 Visualization and interactive analysis of blood parameters with InfoZoom
Michael Spenke
Artif. Intell. Medicine1
1996 FOCUS: The Interactive Table for Product Comparison and Selection
abstract
S.41-50
Michael Spenke, Christian Beilken, Thomas Berlage
ACM Symposium on User Interface Software and Technology1
1989 A spreadsheet interface for logic programming
abstract
We present PERPLEX, a programming environment intended for the end-user. In its design, the concepts of logic programming and spreadsheets are combined. Thus, on the one hand, logic programming becomes an interactive, incremental task where the user gets direct visual feedback, on the other hand, functionality and scope of a conventional spreadsheet program are considerably extended. In order to perform calculations and queries, constraints are imposed on the contents of the spreadsheet cells. New predicates can be defined using a programming-by-example technique: Rules are extracted from the user's solutions for example problems. Thus, concrete intermediate results take over the role of abstract logic variables in the programming process. PERPLEX has been successfully implemented on a Symbolics Lisp Machine.
Michael Spenke, Christian Beilken
CHI1
1984 A Language Independent Error Recovery Method for LL(1) Parsers
abstract
Abstract An efficient and systematic LL(1) error recovery method is presented that has been implemented for an LL(1) parser generator. Error messages which provide good diagnostic information are generated automatically. Error correction is done by discarding some input symbols and popping up some symbols from the parsing‐stack in order to restore the parser to a valid configuration. Thus, symbol deletions and insertions are simulated. The choice between different possible corrections is made by comparing the cost of the inserted (popped) symbols with the reliability value of the recovery symbol (the first input symbol that is not discarded). Our concept of reliability is based on the observation that input symbols differ from each other in their ability to serve as recovery points. A high reliability value of a symbol asserts that it was probably not placed in the input by accident. So it is reasonable not to discard that symbol but to resume parsing. This is done even if a string with high insert‐cost has to be inserted before that symbol in order to fit it to the part of the program that has already been analysed. The error recovery routine is invoked only when an error is detected. Thus, there is no additional time required for parsing correct programs. Error‐correcting parsers for different languages, including Pascal, have been generated. Some experimental results are summarized.
Michael Spenke, Heinz Mühlenbein, Monika Mevenkamp, Friedemann Mattern, Christian Beilken
Softw. Pract. Exp.1