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The Belief-Desire-Intention (BDI) software model (usually referred to simply, but ambiguously, as BDI) is a software model developed for programming intelligent agents. Superficially characterized by the implementation of an agent's beliefs, desires and intentions, it actually uses these concepts to solve a particular problem in agent programming. In essence, it provides a mechanism for separating the activity of selecting a plan (from a plan library) from the execution of currently active plans. Consequently, BDI agents are able to balance the time spent on deliberating about plans (choosing what to do) and executing those plans (doing it). A third activity, creating the plans in the first place (planning), is not within the scope of the model, and is left to the system designer and programmer.

Mutation testing (or Mutation analysis) is a method of software testing, which involves modifying program's source code in small ways.[1] These, so-called mutations, are based on well-defined mutation operators that either mimic typical programming errors (such as using the wrong operator or variable name) or force the creation of valuable tests (such as driving each expression to zero). The purpose is to help the tester develop effective tests or locate weaknesses in the test data used for the program or in sections of the code that are seldom or never accessed during execution.

For example, consider the following C++ code fragment: if (a && b) c = 1; else c = 0; The condition mutation operator would replace '&&' with '||' and produce the following mutant: if (a || b) c = 1; else c = 0;

Many mutation operators can produce equivalent mutants. For example, consider the following code fragment: int index=0; while (...) { . . .; index++; if (index==10) break; } Boolean relation mutation operator will replace "==" with ">=" and produce the following mutant: int index=0; while (...) { . . .; index++; if (index>=10) break; }

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