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. 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. The definition below mimics the usual semantics of formulas in Kripke models, reformulated here in terms of simplicial models:

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

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. Another set of resources to be tested for inclusion in the EOSC services are the IVOA-standardised 2 xxxxx://xxx.xxxx-xxx.xx/eosc-hub-week-2020/agenda/service-onboarding-catalogue-services 3 xxxxx://xxx.xxxxxxx.xx/ semantic vocabularies4. The activity of checking how this integration could be done has already started, however progress on the EOSC side is currently not defined well enough to provide a clear connection at this stage of the project.

Semantics. Creating a framework for semantic markup and validation, to include ETL validation and the definition of common data types for cross-study query and analysis. Largely defined by the OncoTrack request and extended to requirements from other supported projects. Initial work to provide a prototype area for users and projects to save, export and share results. The original request covers a large development effort, which will be continues in succeeding phases. Extension to the viewing, selection and reporting of data, defined by OncoTrack and extended to other projects and new data types. The ongoing effort to provide continuous integration and unit testing combined. The release cycle will include a 4-week testing period involving developers and end users. Export of raw data files from processed data or from links to the original data, required for OncoTrack and other projects. Maintenance of provenance information covering database versions and dates. Selection of more than 2 cohorts, manually or by automated procedures. Reporting and analysis of all selected cohorts Performance issues identified for large data volumes may be addressed by the release of Postgres 9.3 which promises improved support. Initially test to what extent this resolves the issues, then improve performance further in critical areas. Comparable metadata and summary data for multiple data types. Requested by OncoTrack and other projects.

Semantics check permission ∀u ∈ dom(P) ∩ dom(M) : M(u) ∈ P(u) P ▶M M Fig. 3. Checking permissions. ( ❽M (u, v) := (l, M u N ) if v = (l, N ) 8>N (u') if u' ∈ dom(N ) v if v ∈/ Ref (M ❽ N )(u') := <M(u') if u' ∈ dom(M)\dom(N ) ∧ u < u' > undefined if u' ∈ dom(M)\dom(N ) ∧ u ≥ u' (M(u).p if u ∈ dom(M)M :undefined if u' ∈/ dom(M) ∪ dom(N ) ( .p)(u) := undefined if u ∈/ dom(M) Fig. 4. Auxiliary definitions. R ▶ M M .p checks the read permission for these paths extended with property ❽u