lef t P N right P (N S) size P N1 p right(p) 1 .. size(p) S axiom P in Software Attach gs1 datamatrix barcode in Software lef t P N right P (N S) size P N1 p right(p) 1 .. size(p) S axiom P

lef t P N right P (N S) size P N1 p right(p) 1 .. size(p) S axiom P using barcode printer for software control to generate, create gs1 datamatrix barcode image in software applications. RFID A syntax is just a set of Software Data Matrix 2d barcode productions de ned on a set S of symbols. We de ne now what it means for a sequence of symbols to match a sequence of terminal symbols. For this, we use the following binary relation:.

match (N S) (N T ). The relation match is de 2d Data Matrix barcode for None ned by means of three axioms, which are the following:. match i, j, k, l , n1, n2, s1, s2 i 1 .. n1 j 0 .

. n1 1 k 1 ..

n2 l 0 .. n2 1 s1 1 .

. n1 S s2 1 ..

n2 T s1(j + 1) = s2(l + 1) i .. j s1 k .

. l s2 match i ..

j + 1 s1 k .. l + 1 s2 match.

Problems i, j, k, l, n1, n2, s1, s2, m, p i 1 .. n1 j 0 .

. n1 1 k 1 ..

n2 l 0 .. n2 1 s1 1 .

. n1 S s2 1 ..

n2 T m l .. n2 lef t(p) = s1(j + 1) right(p) l + 1 .

. m s2 match i ..

j s1 k .. l s2 match i .

. j + 1 s1 k ..

m s2 match Finally, we de ne the input as a sequence of terminal symbol of size s: formally, s N input 1 .. s T All previous modeling components can be entered in a context.

The input is said to be recognized by the syntax if the following holds: right(axiom) input match De ne an initial machine that does the recognition in one shot. This can be done by means of the following event:. parser when right(axiom) input match then r := TRUE end The purpose of this proje ct is to perform a complete model of this parser. The rst re nement contains the essence of the Earley parser. For this we introduce a variable item, which is a binary relation de ned as follows: item (P N) (N N).

18.2 Projects together with the followi ng invariant: p, k, i, j (p k) (i j) item k 0 .. size(p) i 0 .

. s j 0 ..

s i j 1 .. k right(p) i + 1 .

. j input match Besides the re nement of the parser event, this rst re nement is made of three events called: the scanner, the predictor, and the completer. The scanner adds a new item (p k+1) (i j+1) provided (p k) (i j) (where k < size(p) and j < s) is already stored and right(p)(k + 1) = input(j + 1) holds.

The predictor adds a new item (q 0) (j j) provided (p k) (i j) (where k < size(p)) is already stored and there is a production q such that lef t(q) = right(p)(k + 1). The completer adds a new item (q kp+1) (ip j) provided (p size(p)) (i j) is already stored and (q kp) (ip i) (where kp < size(q)) is also already stored, and nally right(q)(kp + 1) = lef t(p) holds. Prove (informally rst) with the help of the axioms for match that these events maintain the main invariant.

Re ne event parser. As can be seen, this rst re nement is highly non-deterministic. The goal of the project is to perform a number of re nements in order to obtain an e cient parser implemented as a nal sequential program.

. 18.2.3 The Schorr Wait Al Software barcode data matrix gorithm [7] The purpose of this project is to make a model for the Schorr Wait algorithm.

We are given a nite set N of node, a binary relation g (for graph ) built on this set, and a special node t (for top ). Let r be the image of {t} under the irre exive transitive closure of g: r = cl(g)[{t}]. We want to mark (in black) all elements of r.

De ne an initial machine with a one shot event mark performing this task. Re ne this machine by introducing a non-deterministic event progress. Initially only node t is marked.

Event progress marks a node which is related to an already marked node by means of relation g. Introduce the necessary invariant and re ne event mark. Re ne this machine by making it work in a depth- rst fashion.

For this introduce a current node and also a stack which is a linear list. Give invariant properties of the stack..

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