Our proposal has the following key features: 1) The separation of a distributed program into a pure algorithm (PurAl) and a distribution/communication declaration (DUAL). This yields flexible programs capable of handling different kinds of data\program distribution with no change to the pure algorithm. 2) Implicit or automatic handling of communication via externally mapped variables and generalizations of assignment and reference to these variables. This provides unified device independent view and processing of internal data and external distributed data at the user programming language level. 3) Programs need only know of the direct binds with distributed correspondents (mailbox driver, file manager, remote task, window manager etc.). This avoids the need for a central description of all the interconnections. The main short-range benefits of this proposal are to facilitate parallel computations. Parallel programming is a fundamental challenge in computer science, nowadays. Improving these techniques will lead to simplify the programming, eliminate the communication statements, and unify the various communication by using an implicit method for the transfer of data which is becoming essential with the proliferation of distributed networked environment. We present 2 experiments of separation between PurAl and DUAL, using a preprocessor or an object-type library. This new approach might be of interest to both academic and industrial researchers.