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Daniel Paul Friedman is a professor of Computer Science at Indiana University in Bloomington, Indiana. His research focuses on programming languages, and he is a prominent author in the field.
In computer science, recursion is a method of solving a computational problem where the solution depends on solutions to smaller instances of the same problem. Recursion solves such recursive problems by using functions that call themselves from within their own code. The approach can be applied to many types of problems, and recursion is one of the central ideas of computer science.
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In database theory, a conjunctive query is a restricted form of first-order queries using the logical conjunction operator. Many first-order queries can be written as conjunctive queries. In particular, a large part of queries issued on relational databases can be expressed in this way. Conjunctive queries also have a number of desirable theoretical properties that larger classes of queries do not share.
In computability theory and computational complexity theory, an undecidable problem is a decision problem for which it is proved to be impossible to construct an algorithm that always leads to a correct yes-or-no answer. The halting problem is an example: it can be proven that there is no algorithm that correctly determines whether arbitrary programs eventually halt when run.
In computability theory, the halting problem is the problem of determining, from a description of an arbitrary computer program and an input, whether the program will finish running, or continue to run forever. The halting problem is undecidable, meaning that no general algorithm exists that solves the halting problem for all possible program–input pairs.
Concolic testing is a hybrid software verification technique that performs symbolic execution, a classical technique that treats program variables as symbolic variables, along a concrete execution path. Symbolic execution is used in conjunction with an automated theorem prover or constraint solver based on constraint logic programming to generate new concrete inputs with the aim of maximizing code coverage. Its main focus is finding bugs in real-world software, rather than demonstrating program correctness.
In information technology a reasoning system is a software system that generates conclusions from available knowledge using logical techniques such as deduction and induction. Reasoning systems play an important role in the implementation of artificial intelligence and knowledge-based systems.
In mathematics and mathematical logic, Boolean algebra is a branch of algebra. It differs from elementary algebra in two ways. First, the values of the variables are the truth values true and false, usually denoted 1 and 0, whereas in elementary algebra the values of the variables are numbers. Second, Boolean algebra uses logical operators such as conjunction (and) denoted as ∧, disjunction (or) denoted as ∨, and the negation (not) denoted as ¬. Elementary algebra, on the other hand, uses arithmetic operators such as addition, multiplication, subtraction and division. Boolean algebra is therefore a formal way of describing logical operations, in the same way that elementary algebra describes numerical operations.
References
- 1 2 Will Byrd (August 2009). Relational Programming in miniKanren: Techniques, Applications, and Implementations (PDF) (Ph.D.). Indiana University.
- ↑ Will Byrd, Eric Holk, and Dan Friedman (2012). "miniKanren, live and untagged: Quine generation via relational interpreters (programming pearl)" (PDF). Proceedings of the 2012 Annual Workshop on Scheme and Functional Programming. ACM: 8–29.
{{cite journal}}: CS1 maint: multiple names: authors list (link) - ↑ Dan Friedman; Will Byrd; Oleg Kiselyov (2005). The Reasoned Schemer. MIT Press. ISBN 9780262562140.