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Strategies for building large systems that can be easily adapted for new situations with only minor programming modifications. Time pressures encourage programmers to write code that works well for a narrow purpose, with no room to grow. But the best systems are evolvable; they can be adapted for new situations by adding code, rather than changing the existing code. The authors describe techniques they have found effective--over their combined 100-plus years of programming experience--that will help programmers avoid programming themselves into corners. The authors explore ways to enhance flexibility by: • Organizing systems using combinators to compose mix-and-match parts, ranging from small functions to whole arithmetics, with standardized interfaces • Augmenting data with independent annotation layers, such as units of measurement or provenance • Combining independent pieces of partial information using unification or propagation • Separating control structure from problem domain with domain models, rule systems and pattern matching, propagation, and dependency-directed backtracking • Extending the programming language, using dynamically extensible evaluators