Semantics Sample Clauses
Semantics. Expressions reduce according to a call-by-value strategy, for which we define evaluation contexts thus:
Semantics. SECA comes with four semantics, for different purposes. The standard xxxxx- tics defines how programs are executed. The energy-aware semantics addition- ally traces the energy consumption during program execution in a skyline. The symbolic execution semantics executes all possible paths through a program. The energy-aware symbolic execution semantics traces all possible skylines a program can produce. The focus of this paper is the last one; the others are formally defined in a technical report [19]. Below, we will informally discuss the energy-aware semantics, as it is a useful foundation to understand the energy- aware symbolic execution semantics.
Semantics. The definition below mimics the usual semantics of formulas in Kripke models, reformulated here in terms of simplicial models:
Semantics. Figure 3 defines the semantic domains and the inference rules for a big-step evaluation judgment of the form x, R, W € H; u; e ‹→ Hj; uj; v ∈ R W R W This judgment declares that given a variable environment ρ and indexed collections and of read and write permissions, the expression e transforms the initial heap H to the final xxxx Xx and returns value v. Furthermore, it threads a time stamp u, uj Stamp that is incremented at each property write operation and at each permit expression. The permission collections and are indexed by the time stamps of the heaps for which the permissions were granted. The time stamp of a permission uniquely identifies different executions of permit expressions and determines their relative order with respect to heap modifications. ∈ M M A value v Val is either a reference or a closure consisting of an environment and a lambda expression. The representation of a reference is a pair of a heap address A and a collection of access paths, indexed by time stamps. The collection records all permitted access paths that have been traversed during evaluation so far to obtain this reference value. The indexing is again used for marking modifications with time stamps. This representation is dictated by the design choice of path dependency (see Sec. 2.1). A heap maps a location to an object and an object maps a property name to a pair of a time stamp and a value. The time stamp indicates the time of the write operation that last assigned the property. It is required to implement the “sticky update” from Sec. 2.4. x, R, W € H; u; e0 ‹→ H ; u ; (ρ , λx.e) ρ, R, W € Hj; uj; e1 ‹→ Hjj; ujj; v1 ρj[x ›→ v1], R, W € Hjj; ujj; e ‹→ Hjjj; ujjj; v x, R, W € H; u; e0(e1) ‹→ Hjjj; ujjj; v NEW A ∈/ dom(H) ρ, R, W € H; u; new ‹→ H[A ›→ ∅]; u; (A, ∅) PUT x, R, W € H; u; e1 ‹→ Hj; uj; (A, M) x, R, W € Hj; uj; e2 ‹→ Hjj; ujj; v W €chk M.p Hjjj = Hjj[A ›→ Hjj(A)[p ›→ (ujj, v)]] x, R, W € H; u; e1.p := e2 ‹→ Hjjj; ujj + 1; v GET x, R, W € H; u; e ‹→ Hj; uj; (A, M) R €chk M.p < x, R, W € H; u; e.p ‹→ Hj; uj; M.p Hj(A)(p) PERMIT ρj, R[u ›→ Lr ], W[u ›→ Lw ] € H; u + 1; e ‹→ Hj; uj; v ρj = ρ[x ›→ ρ(x) a [u ›→ ε]] x, R, W € H; u; permit x : Lr, Lw in e ‹→ Hj; uj; v
Semantics. This section discusses the semantics of the flow language and the way to integrate it with Event-B. In particular we show how to reason about flow and machine consistency in the terms of machine properties rather than flow or machine traces. But first we use the traces semantics to formally integrate flows with Event-B. The following defines the traces of a flow expression. traces(jskip) = {()} bj j n traces(jstart) = {(jstart)} traces( stop) = {s | n ∈ N ∧ s ≤ ( stop) } b {( )} traces(ei.a) traces(p; q) traces(p|q) traces(∗(p)) traces(pǁEq) = ei.a b {s z | s z ∈ traces(p) ∧ z = ( stop)}∪ = ^ ^ j {s^t | s^z ∈ traces(p) ∧ t ∈ traces(q) ∧ z =ƒ (jstop)} b = traces(p) ∪ traces(q) b | ∗ = traces(p (p; (p))) =b {S(sǁEt | s ∈ traces(p) ∧ t ∈ traces(q)} Here s t states that trace s is a prefix of trace t; α(x) is an alphabet of x (set of all events occurring in x). The parallel composition operator is defined as a collection of possible event interleavings:
Semantics. The semantics of the language of agreements L is based on a possible worlds model We rst de ne a class of models M De nition M hW i is a tuple associating the possible multi agent world states W a function that assigns truth values to formulae and an acces sibility relation associated to programs Now focusing on the actions performed by agents within a multi agent system we de ne the set of paths along which the state of the multi agent system may pass This set of paths is used to de ne our notion of commitment i e what it means for an agent to be bound to uphold an agreement see constraints " in table and s t i i g
Semantics. All of the semantics of version zero (0) of this box, as defined in [ISO], apply to this version of the box with the following additional semantics specifically for SubtitleSampleEntry():
Semantics. From the semantic viewpoint a major objective is a clear semantic dissemination of all measured and calculated values for the integration into the VIM. In order to achieve this goal, the Collaborative Semantic Vocabulary Creation Cycle (CSVCC) will be introduced.
(1) The CSVCC five-step plan helps to systematically collect the required data for the controlled semantic declaration of values, (2) provides common understanding of data to all participants (users, developers, experts, and doctors, (3) maintain the quality of the controlled vocabulary at a high level. The PRECIOUS vocabulary collection phase currently utilises an online vocabulary management system for collecting parameter definitions from PRECIOUS partners (see Figure 21). The development of the CSVCC is ongoing and will be described in more detail in deliverable D4.4.
Semantics. The semantics of a data signature sig = (S, F ), i.e., the values in its sorts, is constituted by equivalence classes of ground terms. The value of a ) ) ground term t denoted t , is defined by t = {t′ | t′ ≡ t}. Here, we assume an equivalence on ground terms, ( ) ( ), which is sort-safe: if t1 t2 then sortt(t1)= sortt(t2). Such an equivalence could be specified as a set of equations (equational specification [7]) or as a set of rewrite rules. ) The semantics of a data signature sig = (S, F ) is then the multi-sorted initial algebra = ( s s S , ƒf f F ), where s = t t s( ) is the set of values of sort s; and for each function symbol ( f :: s1,..., sn s ) F there is a function ƒf : s1 ... sn s defined by ƒf ( t1 ,..., tn )= f (t1,..., tn) , where t1,..., tn are ground terms of sorts s1,..., sn, respectively. The set of all possible values is = s s S . Function sortv : S gives the sort of a value; it is extended to sequences of values as usual. A valuation for X X is a function assigning values to variables: ϑ : X , which is sort-safe: sortt(x) = sortv(ϑ(x)). The set of all valuations for X is denoted UX . The extension to evaluate terms based on a valuation ϑ is called a term evaluation and denoted by ϑT : T (X) → U . It is defined as ϑT (x) = ϑ(x) and ϑT (f (t1,..., tn)) =ƒf (ϑT (t1),..., ϑT (tn)). For a sequence of distinct variables x¯ = x0 ... xn ∈ X∗ and a sequence of values w¯ = w0 ... wn ∈ U∗, we denote with x¯ w¯ the valuation in U{x0 ,...,xn} defined by (x¯ w¯)(xi) = wi for all 0 ≤ i ≤ n. The semantics of a ground term mapping m ∈ T (∅)X is the valuation m defined as m (x)= m(x) for all x ∈ X. ) ) ) In our test algorithm, we need to represent the values in a valuation ϑ ∈ UX (tmap(ϑ))(x)= t ⇒ ϑ(x)= t), for all x ∈ X. as terms again. We therefore use any term mapping tmap(ϑ) ∈T (∅)X satisfying For sort Bool we assume that ) ) interprets ground terms in TBool(∅) as usual, e.g., True = true. Boolean terms can be seen as formulas, for which we can consider their satisfiability. A Boolean term t ∈ TBool(X) is satisfiable if there exists a valuation ϑ vars(t) such that ϑT (t) = true. Satisfiability, however, is undecidable in general. Hence, a tool solving satisfiability problems in our algorithms may return ‘unknown’. Therefore we will distinguish explicitly between semantic satisfiability and a tool solver, with solver(t) returning either sat, unsat, or unknown. Moreover, we assume that solver allows to retrieve a valuation that witnesses satisfiabilit...
Semantics. The study of semantics discusses the connection between conventional meaning and words. An intriguing question to ask is: What can semantics tell us about the word “prayer”? Certainly, background analysis of this concept and its semantic qualities would appear to answer questions posed in this thesis. However, there is an important nuance between a semantic study of the word “prayer” and a qualitative linguistic study of the concept of prayer. Pragmatics. Pragmatics is the study of how linguistic meaning is affected by context. As previously mentioned, prayer is recognized as a speech act. Speech act theory claims that some utterances are not simply true or false. These utterances, speech acts, are successful or unsuccessful in having an effect on the world by being spoken. Examples include naming, marrying, swearing in, proclaiming, etc. However, to be successful, speech acts have certain linguistic and contextual requirements called felicity conditions. Analysis of how prayer functions as a speech act is covered in the next chapter.