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Compiler Correctness
In computing, compiler correctness is the branch of computer science that deals with trying to show that a compiler behaves according to its language specification. Techniques include developing the compiler using formal methods and using rigorous testing (often called compiler validation) on an existing compiler. Formal verification Two main formal verification approaches for establishing correctness of compilation are proving correctness of the compiler for all inputs and proving correctness of a compilation of a particular program (translation validation). Compiler correctness for all input programs Compiler validation with formal methods involves a long chain of formal, deductive logic. However, since the tool to find the proof ( theorem prover) is implemented in software and is complex, there is a high probability it will contain errors. One approach has been to use a tool that verifies the proof (a proof checker) which, because it is much simpler than a proof-finder, ...
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Computing
Computing is any goal-oriented activity requiring, benefiting from, or creating computer, computing machinery. It includes the study and experimentation of algorithmic processes, and the development of both computer hardware, hardware and software. Computing has scientific, engineering, mathematical, technological, and social aspects. Major computing disciplines include computer engineering, computer science, cybersecurity, data science, information systems, information technology, and software engineering. The term ''computing'' is also synonymous with counting and calculation, calculating. In earlier times, it was used in reference to the action performed by Mechanical computer, mechanical computing machines, and before that, to Computer (occupation), human computers. History The history of computing is longer than the history of computing hardware and includes the history of methods intended for pen and paper (or for chalk and slate) with or without the aid of tables. ...
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HOL (proof Assistant)
HOL (Higher Order Logic) denotes a family of interactive theorem proving systems using similar (higher-order) logics and implementation strategies. Systems in this family follow the LCF (Logic for Computable Functions) approach as they are implemented as a library which defines an abstract data type of proven theorems such that new objects of this type can only be created using the functions in the library which correspond to inference rules in higher-order logic. As long as these functions are correctly implemented, all theorems proven in the system must be valid. As such, a large system can be built on top of a small trusted kernel. Systems in the HOL family use ML or its successors. ML was originally developed along with LCF as a meta-language for theorem proving systems; in fact, the name stands for "Meta-Language". Underlying logic HOL systems use variants of classical higher-order logic, which has simple axiomatic foundations with few axioms and well-understood seman ...
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Reflections On Trusting Trust
Kenneth Lane Thompson (born February 4, 1943) is an American pioneer of computer science. Thompson worked at Bell Labs for most of his career where he designed and implemented the original Unix operating system. He also invented the B programming language, the direct predecessor to the C language, and was one of the creators and early developers of the Plan 9 operating system. Since 2006, Thompson has worked at Google, where he co-developed the Go language. A recipient of the Turing award, he is considered one of the greatest computer programmers of all time. Other notable contributions included his work on regular expressions and early computer text editors QED and ed, the definition of the UTF-8 encoding, and his work on computer chess that included the creation of endgame tablebases and the chess machine Belle. He won the Turing Award in 1983 with his long-term colleague Dennis Ritchie. Early life and education Thompson was born in New Orleans, Louisiana. When asked h ...
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Correctness (computer Science)
In theoretical computer science, an algorithm is correct with respect to a program specification, specification if it behaves as specified. Best explored is ''functional'' correctness, which refers to the input–output behavior of the algorithm: for each input it produces an output satisfying the specification. Within the latter notion, ''partial correctness'', requiring that ''if'' an answer is returned it will be correct, is distinguished from ''total correctness'', which additionally requires that an answer ''is'' eventually returned, i.e. the algorithm terminates. Correspondingly, to mathematical proof, prove a program's total correctness, it is sufficient to prove its partial correctness, and its termination. The latter kind of proof (termination proof) can never be fully automated, since the halting problem is undecidable problem, undecidable. For example, successively searching through integers 1, 2, 3, … to see if we can find an example of some phenomenon—say an ...
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Verification And Validation (software)
In software project management, software testing, and software engineering, verification and validation is the process of checking that a software engineer system meets specifications and requirements so that it fulfills its intended purpose. It may also be referred to as software quality control. It is normally the responsibility of software testers as part of the software development lifecycle. In simple terms, software verification is: "Assuming we should build X, does our software achieve its goals without any bugs or gaps?" On the other hand, software validation is: "Was X what we should have built? Does X meet the high-level requirements?" Definitions Verification and validation are not the same thing, although they are often confused. Boehm succinctly expressed the difference as * Verification: Are we building the product right? * Validation: Are we building the right product? "Building the product right" checks that the ''specifications'' are correctly implemented by ...
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Compiler
In computing, a compiler is a computer program that Translator (computing), translates computer code written in one programming language (the ''source'' language) into another language (the ''target'' language). The name "compiler" is primarily used for programs that translate source code from a high-level programming language to a lower level language, low-level programming language (e.g. assembly language, object code, or machine code) to create an executable program.Compilers: Principles, Techniques, and Tools by Alfred V. Aho, Ravi Sethi, Jeffrey D. Ullman - Second Edition, 2007 There are many different types of compilers which produce output in different useful forms. A ''cross-compiler'' produces code for a different Central processing unit, CPU or operating system than the one on which the cross-compiler itself runs. A ''bootstrap compiler'' is often a temporary compiler, used for compiling a more permanent or better optimised compiler for a language. Related software ...
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Test Case Reduction
In programming and software development, fuzzing or fuzz testing is an automated software testing technique that involves providing invalid, unexpected, or random data as inputs to a computer program. The program is then monitored for exceptions such as crashes, failing built-in code assertions, or potential memory leaks. Typically, fuzzers are used to test programs that take structured inputs. This structure is specified, such as in a file format or protocol and distinguishes valid from invalid input. An effective fuzzer generates semi-valid inputs that are "valid enough" in that they are not directly rejected by the parser, but do create unexpected behaviors deeper in the program and are "invalid enough" to expose corner cases that have not been properly dealt with. For the purpose of security, input that crosses a trust boundary is often the most useful. For example, it is more important to fuzz code that handles a file uploaded by any user than it is to fuzz the code ...
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Regression Testing
Regression testing (rarely, ''non-regression testing'') is re-running functional and non-functional tests to ensure that previously developed and tested software still performs as expected after a change. If not, that would be called a '' regression''. Changes that may require regression testing include bug fixes, software enhancements, configuration changes, and even substitution of electronic components ( hardware). As regression test suites tend to grow with each found defect, test automation is frequently involved. Sometimes a change impact analysis is performed to determine an appropriate subset of tests (''non-regression analysis''). Background As software is updated or changed, or reused on a modified target, emergence of new faults and/or re-emergence of old faults is quite common. Sometimes re-emergence occurs because a fix gets lost through poor revision control practices (or simple human error in revision control). Often, a fix for a problem will be " fragil ...
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Standard ML
Standard ML (SML) is a General-purpose programming language, general-purpose, High-level programming language, high-level, Modular programming, modular, Functional programming, functional programming language with compile-time type checking and type inference. It is popular for writing compilers, for programming language research, and for developing automated theorem proving, theorem provers. Standard ML is a modern dialect of ML (programming language), ML, the language used in the Logic for Computable Functions (LCF) theorem-proving project. It is distinctive among widely used languages in that it has a formal specification, given as typing rules and operational semantics in ''The Definition of Standard ML''. Language Standard ML is a functional programming language with some impure features. Programs written in Standard ML consist of Expression (computer science), expressions in contrast to statements or commands, although some expressions of type Unit type, unit are only eva ...
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Computer Science
Computer science is the study of computation, information, and automation. Computer science spans Theoretical computer science, theoretical disciplines (such as algorithms, theory of computation, and information theory) to Applied science, applied disciplines (including the design and implementation of Computer architecture, hardware and Software engineering, software). Algorithms and data structures are central to computer science. The theory of computation concerns abstract models of computation and general classes of computational problem, problems that can be solved using them. The fields of cryptography and computer security involve studying the means for secure communication and preventing security vulnerabilities. Computer graphics (computer science), Computer graphics and computational geometry address the generation of images. Programming language theory considers different ways to describe computational processes, and database theory concerns the management of re ...
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