We describe how an environment can be extended to support the process of software development. Our approach is based on the AI planning paradigm. Processes are formally defined hierarchically via plan operators, using multiple levels of abstraction. Plans are constructed dynamically from the operators; the sequences of actions in plans are tailored to the context of their use. and conflicts among actions are prevented. Monitoring of the development process, to detect and avert process errors,

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... accomplished by plan recognition; this establishes a context in which programmer-selected goals can be automated via plan generation. We also show how nonmonotonic reasoning can be used to make an independent assessment of the credibility of complex process alternatives, and yet accede to the programmer's superior judgment. This extension to intelligent assistance provides deeper understanding of software processes. Goals are logical expressions composed of the state predicates. A plan is a hierarchical, partial order of operators (with bound