Type systemIn computer programming, a type system is a logical system comprising a set of rules that assigns a property called a type (for example, integer, floating point, string) to every "term" (a word, phrase, or other set of symbols). Usually the terms are various constructs of a computer program, such as variables, expressions, functions, or modules. A type system dictates the operations that can be performed on a term. For variables, the type system determines the allowed values of that term.
Type safetyIn computer science, type safety and type soundness are the extent to which a programming language discourages or prevents type errors. Type safety is sometimes alternatively considered to be a property of facilities of a computer language; that is, some facilities are type-safe and their usage will not result in type errors, while other facilities in the same language may be type-unsafe and a program using them may encounter type errors.
Runtime verificationRuntime verification is a computing system analysis and execution approach based on extracting information from a running system and using it to detect and possibly react to observed behaviors satisfying or violating certain properties. Some very particular properties, such as datarace and deadlock freedom, are typically desired to be satisfied by all systems and may be best implemented algorithmically. Other properties can be more conveniently captured as formal specifications.
Type inferenceType inference refers to the automatic detection of the type of an expression in a formal language. These include programming languages and mathematical type systems, but also natural languages in some branches of computer science and linguistics. Types in a most general view can be associated to a designated use suggesting and restricting the activities possible for an object of that type. Many nouns in language specify such uses. For instance, the word leash indicates a different use than the word line.
Type theoryIn mathematics, logic, and computer science, a type theory is the formal presentation of a specific type system, and in general, type theory is the academic study of type systems. Some type theories serve as alternatives to set theory as a foundation of mathematics. Two influential type theories that were proposed as foundations are Alonzo Church's typed λ-calculus and Per Martin-Löf's intuitionistic type theory. Most computerized proof-writing systems use a type theory for their foundation, a common one is Thierry Coquand's Calculus of Inductive Constructions.
Runtime systemIn computer programming, a runtime system or runtime environment is a sub-system that exists both in the computer where a program is created, as well as in the computers where the program is intended to be run. The name comes from the compile time and runtime division from compiled languages, which similarly distinguishes the computer processes involved in the creation of a program (compilation) and its execution in the target machine (the run time). Most programming languages have some form of runtime system that provides an environment in which programs run.
Data typeIn computer science and computer programming, a data type (or simply type) is a collection or grouping of data values, usually specified by a set of possible values, a set of allowed operations on these values, and/or a representation of these values as machine types. A data type specification in a program constrains the possible values that an expression, such as a variable or a function call, might take. On literal data, it tells the compiler or interpreter how the programmer intends to use the data.
Undefined behaviorIn computer programming, undefined behavior (UB) is the result of executing a program whose behavior is prescribed to be unpredictable, in the language specification to which the computer code adheres. This is different from unspecified behavior, for which the language specification does not prescribe a result, and implementation-defined behavior that defers to the documentation of another component of the platform (such as the ABI or the translator documentation).
Type conversionIn computer science, type conversion, type casting, type coercion, and type juggling are different ways of changing an expression from one data type to another. An example would be the conversion of an integer value into a floating point value or its textual representation as a string, and vice versa. Type conversions can take advantage of certain features of type hierarchies or data representations.
Type introspectionIn computing, type introspection is the ability of a program to examine the type or properties of an object at runtime. Some programming languages possess this capability. Introspection should not be confused with reflection, which goes a step further and is the ability for a program to manipulate the values, metadata, properties, and functions of an object at runtime. Some programming languages also possess that capability (e.g., Java, Python, Julia, and Go). Type introspection is a core feature of Ruby.
Dependent typeIn computer science and logic, a dependent type is a type whose definition depends on a value. It is an overlapping feature of type theory and type systems. In intuitionistic type theory, dependent types are used to encode logic's quantifiers like "for all" and "there exists". In functional programming languages like Agda, ATS, Coq, F*, Epigram, and Idris, dependent types help reduce bugs by enabling the programmer to assign types that further restrain the set of possible implementations.
Strong and weak typingIn computer programming, one of the many ways that programming languages are colloquially classified is whether the language's type system makes it strongly typed or weakly typed (loosely typed). However, there is no precise technical definition of what the terms mean and different authors disagree about the implied meaning of the terms and the relative rankings of the "strength" of the type systems of mainstream programming languages.
Dynamic testingDynamic testing (or dynamic analysis) is a term used in software engineering to describe the testing of the dynamic behavior of code. That is, dynamic analysis refers to the examination of the physical response from the system to variables that are not constant and change with time. In dynamic testing the software must actually be compiled and run. It involves working with the software, giving input values and checking if the output is as expected by executing specific test cases which can be done manually or with the use of an automated process.
Vulnerability (computing)Vulnerabilities are flaws in a computer system that weaken the overall security of the device/system. Vulnerabilities can be weaknesses in either the hardware itself, or the software that runs on the hardware. Vulnerabilities can be exploited by a threat actor, such as an attacker, to cross privilege boundaries (i.e. perform unauthorized actions) within a computer system. To exploit a vulnerability, an attacker must have at least one applicable tool or technique that can connect to a system weakness.
Dynamic program analysisDynamic program analysis is analysis of computer software that involves executing the program in question (as opposed to static program analysis, which does not). Dynamic program analysis includes familiar techniques from software engineering such as unit testing, debugging, and measuring code coverage, but also includes lesser-known techniques like program slicing and invariant inference. Dynamic program analysis is widely applied in security in the form of runtime memory error detection, fuzzing, dynamic symbolic execution, and taint tracking.
Reference (computer science)In computer programming, a reference is a value that enables a program to indirectly access a particular data, such as a variable's value or a record, in the computer's memory or in some other storage device. The reference is said to refer to the datum, and accessing the datum is called dereferencing the reference. A reference is distinct from the datum itself. A reference is an abstract data type and may be implemented in many ways. Typically, a reference refers to data stored in memory on a given system, and its internal value is the memory address of the data, i.
Software testingSoftware testing is the act of examining the artifacts and the behavior of the software under test by validation and verification. Software testing can also provide an objective, independent view of the software to allow the business to appreciate and understand the risks of software implementation. Test techniques include, but are not necessarily limited to: analyzing the product requirements for completeness and correctness in various contexts like industry perspective, business perspective, feasibility and viability of implementation, usability, performance, security, infrastructure considerations, etc.
FuzzingIn 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, e.g., in a or protocol and distinguishes valid from invalid input.
Dynamic compilationDynamic compilation is a process used by some programming language implementations to gain performance during program execution. Although the technique originated in Smalltalk, the best-known language that uses this technique is Java. Since the machine code emitted by a dynamic compiler is constructed and optimized at program runtime, the use of dynamic compilation enables optimizations for efficiency not available to statically-compiled programs (i.e.
Type classIn computer science, a type class is a type system construct that supports ad hoc polymorphism. This is achieved by adding constraints to type variables in parametrically polymorphic types. Such a constraint typically involves a type class T and a type variable a, and means that a can only be instantiated to a type whose members support the overloaded operations associated with T.
