Editing Semantics (section)

== In various disciplines ==
=== Logic ===
{{main|Semantics of logic}}

Logicians study correct [[Logical reasoning|reasoning]] and often develop [[formal languages]] to express arguments and assess their correctness.<ref>{{multiref | {{harvnb|Riemer|2010|pp=173–174}} | {{harvnb|Jaakko|Sandu|2006|pp=13–14}} | {{harvnb|Shapiro|Kouri Kissel|2024|loc=Lead Section, § 2. Language}} }}</ref> One part of this process is to provide a semantics for a formal language to precisely define what its terms mean. A semantics of a formal language is a set of rules, usually expressed as a [[mathematical function]], that assigns meanings to formal language expressions.<ref>{{multiref | {{harvnb|Shapiro|Kouri Kissel|2024|loc=Lead Section, § 4. Semantics}} | {{harvnb|Jansana|2022|loc=§ 5. Algebraic Semantics}} | {{harvnb|Jaakko|Sandu|2006|pp=17–18}} }}</ref> For example, the language of first-order logic uses lowercase letters for [[individual constant]]s and uppercase letters for [[Predicate (mathematical logic)|predicates]]. To express the sentence "Bertie is a dog", the formula <math>D(b)</math> can be used where <math>b</math> is an individual constant for Bertie and <math>D</math> is a predicate for dog. Classical model-theoretic semantics assigns meaning to these terms by defining an [[Interpretation (logic)|interpretation function]] that maps individual constants to specific objects and predicates to [[Set (mathematics)|sets]] of objects or [[tuple]]s. The function maps <math>b</math> to Bertie and <math>D</math> to the set of all dogs. This way, it is possible to calculate the truth value of the sentence: it is true if Bertie is a member of the set of dogs and false otherwise.<ref>{{multiref | {{harvnb|Grimm|2009|pp=[https://books.google.com/books?id=QwyS2rZKnB0C&pg=PA116 116–117]}} | {{harvnb|Shapiro|Kouri Kissel|2024|loc=Lead Section, § 4. Semantics}} | {{harvnb|Magnus|Button|Thomas-Bolduc|Zach|2021|pp=193–195}} }}</ref>

Formal logic aims to determine whether arguments are [[deductively valid]], that is, whether the premises entail the conclusion.<ref>{{multiref | {{harvnb|Riemer|2010|pp=173–174}} | {{harvnb|Jaakko|Sandu|2006|pp=13–14}} | {{harvnb|Shapiro|Kouri Kissel|2024|loc=Lead Section}} | {{harvnb|Gregory|2017|p=[https://books.google.com/books?id=9heXDQAAQBAJ&pg=PA82 82]}} }}</ref> Entailment can be defined in terms of syntax or in terms of semantics. Syntactic entailment, expressed with the symbol <math>\vdash</math>, relies on [[rules of inference]], which can be understood as procedures to transform premises and arrive at a conclusion. These procedures only take the [[logical form]] of the premises on the level of syntax into account and ignore what meaning they express. Semantic entailment, expressed with the symbol <math>\vDash</math>, looks at the meaning of the premises, in particular, at their truth value. A conclusion follows semantically from a set of premises if the truth of the premises ensures the truth of the conclusion, that is, if any semantic interpretation function that assigns the premises the value ''true'' also assigns the conclusion the value ''true''.<ref>{{multiref | {{harvnb|Forster|2003|pp=[https://books.google.com/books?id=mVeTuaRwWssC&pg=PA74 74–75]}} | {{harvnb|Johnstone|1987|p=[https://books.google.com/books?id=_hlsBpVA3qkC&pg=PA23 23]}} | {{harvnb|Shapiro|Kouri Kissel|2024|loc=Lead Section, § 4. Semantics}} | {{harvnb|Jaakko|Sandu|2006|pp=17–20}} }}</ref>

=== Computer science ===
{{main|Semantics (computer science)}}

In computer science, the semantics of a [[Computer program|program]] is how it behaves when a computer runs it. Semantics contrasts with syntax, which is the particular form in which instructions are expressed. The same behavior can usually be described with different forms of syntax. In [[JavaScript]], this is the case for the commands <code>i += 1</code> and <code>i = i + 1</code>, which are syntactically different expressions to increase the value of the variable ''i'' by one. This difference is also reflected in different [[programming languages]] since they rely on different syntax but can usually be employed to create programs with the same behavior on the semantic level.<ref>{{multiref | {{harvnb|Fernández|2014|pp=[https://books.google.com/books?id=dzi5BQAAQBAJ&pg=PA10 10, 14–15]}} | {{harvnb|Dale|Weems|Headington|2003|pp=[https://books.google.com/books?id=VbyCFuJLgOMC&pg=PA42 42, 44]}} | {{harvnb|O’Regan|2020|p=[https://books.google.com/books?id=hnLJDwAAQBAJ&pg=PA193 193]}} }}</ref>

Static semantics focuses on semantic aspects that affect the [[compile time|compilation]] of a program. In particular, it is concerned with detecting errors of syntactically correct programs, such as [[type error]]s, which arise when an operation receives an incompatible [[data type]]. This is the case, for instance, if a function performing a numerical calculation is given a [[String (computer science)|string]] instead of a number as an argument.<ref>{{multiref | {{harvnb|Fernández|2014|pp=[https://books.google.com/books?id=dzi5BQAAQBAJ&pg=PA14 14–15]}} | {{harvnb|Fritzson|2010|p=[https://books.google.com/books?id=doNqLi7279wC&pg=PA703 703]}} | {{harvnb|Mosses|2003|p=[https://books.google.com/books?id=tMlrCQAAQBAJ&pg=PA167 167]}} }}</ref> Dynamic semantics focuses on the run time behavior of programs, that is, what happens during the [[Execution (computing)|execution]] of instructions.<ref>{{multiref | {{harvnb|Fernández|2014|pp=[https://books.google.com/books?id=dzi5BQAAQBAJ&pg=PA15 15–16]}} | {{harvnb|Fritzson|2010|p=[https://books.google.com/books?id=doNqLi7279wC&pg=PA703 703]}} | {{harvnb|Mosses|2003|p=[https://books.google.com/books?id=tMlrCQAAQBAJ&pg=PA167 167]}} }}</ref> The main approaches to dynamic semantics are [[denotational semantics|denotational]], [[axiomatic semantics|axiomatic]], and [[operational semantics]]. Denotational semantics relies on mathematical formalisms to describe the effects of each element of the code. Axiomatic semantics uses deductive logic to analyze which conditions must be in place before and after the execution of a program. Operational semantics interprets the execution of a program as a series of steps, each involving the transition from one [[State (computer science)|state]] to another state.<ref>{{multiref | {{harvnb|Fernández|2014|p=[https://books.google.com/books?id=dzi5BQAAQBAJ&pg=PA16 16]}} | {{harvnb|O’Regan|2020|pp=[https://books.google.com/books?id=hnLJDwAAQBAJ&pg=PA193 193–194]}} }}</ref>

=== Psychology ===
{{main|Semantics (psychology)}}
Psychological semantics examines psychological aspects of meaning. It is concerned with how meaning is represented on a cognitive level and what mental processes are involved in understanding and producing language. It further investigates how meaning interacts with other mental processes, such as the relation between language and perceptual experience.<ref>{{multiref | {{harvnb|Smith|Rips|Shoben|1975|pp=[https://books.google.com/books?id=o5LScJ9ecGUC&pg=PA1 1–3]}} | {{harvnb|Sanford|2009|pp=792–793, 796}} }}</ref>{{efn|Some theorists use the term ''psychosemantics'' to refer to this discipline while others understand the term in a different sense.<ref>{{multiref | {{harvnb|Halpern|Voĭskunskiĭ|1997|p=[https://books.google.com/books?id=02JK4iG16GAC&pg=PA21 21]}} | {{harvnb|Cohen|2009|p=[https://books.google.com/books?id=6U01MmL9fxsC&pg=PA59 59]}} }}</ref>}} Other issues concern how people learn new words and relate them to familiar things and concepts, how they infer the meaning of compound expressions they have never heard before, how they resolve ambiguous expressions, and how semantic illusions lead them to misinterpret sentences.<ref>{{harvnb|Sanford|2009|pp=793–797}}</ref>

One key topic is [[semantic memory]], which is a form of [[general knowledge]] of meaning that includes the knowledge of language, concepts, and facts. It contrasts with [[episodic memory]], which records events that a person experienced in their life. The comprehension of language relies on semantic memory and the information it carries about word meanings.<ref>{{multiref | {{harvnb|Smith|Rips|Shoben|1975|pp=[https://books.google.com/books?id=o5LScJ9ecGUC&pg=PA3 3–4]}} | {{harvnb|Hampton|2015|p=[https://books.google.com/books?id=GplGCgAAQBAJ&pg=PA125 125]}} | {{harvnb|Tulving|2001|p=[https://books.google.com/books?id=-wt1aZrGXLYC&pg=PA278 278]}} }}</ref> According to a common view, word meanings are stored and processed in relation to their semantic features. The feature comparison model states that sentences like "a robin is a bird" are assessed on a psychological level by comparing the semantic features of the word ''robin'' with the semantic features of the word ''bird''. The assessment process is fast if their semantic features are similar, which is the case if the example is a [[Prototype theory|prototype]] of the general category. For atypical examples, as in the sentence "a penguin is a bird", there is less overlap in the semantic features and the psychological process is significantly slower.<ref>{{multiref | {{harvnb|Sanford|2009|p=792}} | {{harvnb|Smith|Rips|Shoben|1975|pp=[https://books.google.com/books?id=o5LScJ9ecGUC&pg=PA3 3–4, 42]}} | {{harvnb|Hampton|2015|pp=[https://books.google.com/books?id=GplGCgAAQBAJ&pg=PA125 125–128]}} | {{harvnb|Shi|2017|pp=[https://books.google.com/books?id=4vatDgAAQBAJ&pg=PA85 85–86]}} }}</ref>