The landscape of computing is continually changing. New achievements bring new possibilities to users and pose new challenges to both practitioners and theoreticians.
New frontiers of computing include such issues as distributed computing, location-independence, remote programming, interaction and smart agents.

Are APL, J and in general array processing languages (APLs) still able to live up to these challenges? Are APLers brave enough to come out of their niches and once again take their place on the leading edge of computer science?
Consider how APL on its inception set the agenda for modern computing: interpretation, standard set of primitives designed for machine independence, inter process communication, parallelism, typed I/O.
In the following years developers of APLs came out with a wealth of enrichments of the original environment: full screen editors, object-oriented extensions, new control flow primitives, interfaces with other languages, environments and operating systems.
The time has come to promote a new and central role for array processing languages in the new territories of end-user computing through their expressiveness, of INTERNET computing through the possibility of encapsulating data and programs, of high performance computing through their native management of parallelism.

Contributions are sought which will emphasize how array processing languages are a significant response to new demands, how they allow the rapid development of significant applications both in classical and in new fields of use, how they provide adequate settings for users to develop their own applications.

Topics of interest include, but are not limited to:

  1. State of the art of APLs:
    Present situation and future directions

  2. Computer Science:
    Human Computer Interaction
    Object-Oriented Programming
    Parallel Architectures
    Parallelism and Concurrency
    Meta-level Programming
    INTERNET Computing

  3. Discrete Mathematics, Algorithms and new computing paradigms:
    Neural Networks
    Genetic Algorithms
    DNA computing

  4. Applications:
    Finance and Financial Maths
    Economics and Social Sciences
    Insurance and Actuarial Maths
    Statistics and Operational Research
    Image Processing
    Simulation of physical, biological and social phenomena

  5. Education:
    Teaching APLs
    Teaching with APLs

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