Paper Info
Title
Dynamic ADTs: a "don't ask, don't tell" policy for data abstraction.
Abstract
We outline an approach to abstract data types (ADTs) that allows an object of the type specified by the ADT to take on one of many possible representations. A dynamic abstract data type (DADT) is dual to dynamic algorithm selection and facilitates profiling of data in conjunction with the profiling of code. It also permits a programmer to delay or ignore details pertaining to data representation and enhance the efficiency of some algorithms by changing representations at run time without writing code extraneous to the algorithm itself. Additionally, we demonstrate that run time optimization of data objects is possible and allows for acceptable performance compared to traditional ADTs. An implementation is presented in Common Lisp.
Year
DOI
Venue
2007
10.1145/1622123.1622152
ILC
Keywords
Field
DocType
traditional adts,abstract data type,run time,possible representation,data representation,run time optimization,common lisp,data abstraction,dynamic adts,data object,dynamic algorithm selection,dynamic abstract data type,functional programming,network simulation,network analysis,functional languages,lisp,network flow,scheme
Abstract data type,Common Lisp,Programming language,Programmer,External Data Representation,Functional programming,Profiling (computer programming),Computer science,Lisp,Theoretical computer science,Dynamic problem
Conference
Citations 
PageRank 
References 
1
0.35
8
Authors
3
Name
Order
Citations
PageRank
Geoff Wozniak1252.05
Mark Daley216622.18
Stephen M. Watt367184.72