Syntax Analyzer Parser
|
|
- Agnieszka Kosińska
- 6 lat temu
- Przeglądów:
Transkrypt
1 Syntax Analyzer Parser ASU Textbook Chapter , 4.7, 4.8 Tsan-sheng Hsu 1
2 a program represented by a sequence of tokens Main tasks parser if it is a legal program, then output some abstract representation of the program Abstract representations of the input program: abstract-syntax tree + symbol table intermediate code object code Context free grammar (CFG) is used to specify the structure of legal programs. Compiler notes #3, Tsan-sheng Hsu, IIS 2
3 Context free grammar (CFG) Definitions: G = (T, N, P, S), where T : a set of terminals (in lower case letters); N: a set of nonterminals (in upper case letters); P : productions of the form A X 1, X 2,..., X m, where A N and X i T N; S: the starting nonterminal, S N. Notations: terminals : lower case English strings, e.g., a, b, c,... nonterminals: upper case English strings, e.g., A, B, C,... α, β, γ (T N) α, β, γ: alpha, beta and gamma. ɛ: epsilon. A X 1 A X 2 } A X 1 X 2 Compiler notes #3, Tsan-sheng Hsu, IIS 3
4 How does a CFG define a language? The language defined by the grammar is the set of strings (sequence of terminals) that can be derived from the starting nonterminal. How to derive something? Start with: current sequence = the starting nonterminal. Repeat find a nonterminal X in the current sequence find a production in the grammar with X on the left of the form X α, where α is ɛ or a sequence of terminals and/or nonterminals. create a new current sequence in which α replaces X Until current sequence contains no nonterminals. We derive either ɛ or a string of terminals. This is how we derive a string of the language. Compiler notes #3, Tsan-sheng Hsu, IIS 4
5 Example Grammar: E int E E E E E / E E ( E ) E = E E = 1 E = 1 E/E = 1 E/2 = 1 4/2 Details: The first step was done by choosing the second production. The second step was done by choosing the first production. Conventions: = : means derives in one step ; + = : means derives in one or more steps ; = : means derives in zero or more steps ; In the above example, we can write E = + 1 4/2. Compiler notes #3, Tsan-sheng Hsu, IIS 5
6 Language The language defined by a grammar G is L(G) = {w S + = ω}, where S is the starting nonterminal and ω is a sequence of terminals or ɛ. An element in a language is ɛ or a sequence of terminals in the set defined by the language. More terminology: E = = 1 4/2 is a derivation of 1 4/2 from E. There are several kinds of derivations that are important: The derivation is a leftmost one if the leftmost nonterminal always gets to be chosen (if we have a choice) to be replaced. It is a rightmost one if the rightmost nonterminal is replaced all the times. Compiler notes #3, Tsan-sheng Hsu, IIS 6
7 A way to describe derivations Construct a derivation or parse tree as follows: start with the starting nonterminal as a single-node tree REPEAT choose a leaf nonterminal X choose a production X α symbols in α become children of X UNTIL no more leaf nonterminal left Need to annotate the order of derivation on the nodes. E = E E = 1 E = 1 E/E = 1 E/2 = 1 4/2 (2) E (1) E E 1 (5) E / E 4 (3) 2 (4) Compiler notes #3, Tsan-sheng Hsu, IIS 7
8 Example: Grammar: E int E E E E E/E E (E) E E E Parse tree examples 1 E / E 4 2 leftmost derivation Using 1 4/2 as the input, the left parse tree is derived. A string is formed by reading the leaf nodes from left to right, which gives 1 4/2. The string 1 4/2 has another parse tree on the right. E 1 E E / E 4 E 2 rightmost derivation Some standard notations: Given a parse tree and a fixed order (for example leftmost or rightmost) we can derive the order of derivation. For the semantic of the parse tree, we normally interpret the meaning in a bottom-up fashion. That is, the one that is derived last will be serviced first. Compiler notes #3, Tsan-sheng Hsu, IIS 8
9 Ambiguous grammar If for grammar G and string S, there are more than one leftmost derivation for S, or more than one rightmost derivation for S, or more than one parse tree for S, then G is called ambiguous. Note: the above three conditions are equivalent in that if one is true, then all three are true. Q?: How to prove this? Hint: Any unannotated tree can be annotated with a leftmost numbering. Problems with an ambiguous grammar: Ambiguity can make parsing difficult. Underlying structure is ill-defined: in the example, the precedence is not uniquely defined, e.g., the leftmost parse tree groups 4/2 while the rightmost parse tree groups 1 4, resulting in two different semantics. Compiler notes #3, Tsan-sheng Hsu, IIS 9
10 Common grammar problems Lists: that is, zero or more ID s separated by commas: Note it is easy to express one or more ID s: <idlist> <idlist>, ID ID For zero or more ID s, <idlist> ɛ ID <idlist>, <idlist> won t work due to ɛ; it can generate: ID,, ID <idlist> ɛ <idlist>, ID ID won t work either because it can generate:, ID, ID We should separate out the empty list from the general list of one or more ID s. <opt-idlist> ɛ <nonemptyidlist> <nonemptyidlist> <nonemptyidlist>, ID ID Expressions: precedence and associativity as discussed next. Compiler notes #3, Tsan-sheng Hsu, IIS 10
11 Grammar that expresses precedence correctly Use one nonterminal for each precedence level Start with lower precedence (in our example ) Original grammar: E int E E E E E/E E (E) Revised grammar: E E E T T T/T F F int (E) E E E E T T F 1 T / T F F 4 2 rightmost derivation T / T ERROR F 2 Compiler notes #3, Tsan-sheng Hsu, IIS 11
12 More problems with associativity However, the above grammar is still ambiguous, and parse trees may not express the associative of and /. Example: Revised grammar: E E E T T T/T F F int (E) E E E E E T T F 2 T F 3 F 4 E E E T E E rightmost derivation rightmost derivation value = (2 3) 4 = 5 value = 2 (3 4) = 3 Problems with associativity: The rule E E E has E on both sides of. Need to make the second E to some other nonterminal parsed earlier. Similarly for the rule E E/E. F 2 T F 3 T F 4 Compiler notes #3, Tsan-sheng Hsu, IIS 12
13 Grammar considering associative rules Original grammar: E int E E E E E/E E (E) Revised grammar: E E E T T T/T F F int (E) Final grammar: E E T T T T/F F F int (E) Example: E E T E T F T F 4 F 3 2 leftmost/rightmost derivation value = (2 3) 4 = 5 Compiler notes #3, Tsan-sheng Hsu, IIS 13
14 Recursive productions: Rules for associativity E E T is called a left recursive production. A + = Aα. E T E is called a right recursive production. A + = αa. E E E is both left and right recursion. If one wants left associativity, use left recursion. If one wants right associativity, use right recursion. Compiler notes #3, Tsan-sheng Hsu, IIS 14
15 How to use CFG Breaks down the problem into pieces. Think about a C program: Declarations: typedef, struct, variables,... Procedures: type-specifier, function name, parameters, function body. function body: various statements. Example: <procedure> <type-def> ID <opt-params><opt-decl> {<opt-statements>} <opt-params> (<list-params>) <list-params> ɛ <nonemptyparlist> <nonemptyparlist> <nonemptyidlist>, ID ID One of purposes to write a grammar for a language is for others to understand. It will be nice to break things up into different levels in a top-down easily understandable fashion. Compiler notes #3, Tsan-sheng Hsu, IIS 15
16 Useless terms A non-terminal X is useless if either a sequence includes X cannot be derived from the starting nonterminal, or no string can be derived starting from X, where a string means ɛ or a sequence of terminals. Example 1: S A B A + ɛ B digit B digit C. B In Example 1: C is useless and so is the last production. Any nonterminal not in the right-hand side of any production is useless! Compiler notes #3, Tsan-sheng Hsu, IIS 16
17 More examples for useless terms Example 2: Y is useless. S X Y X ( ) Y ( Y Y ) Y derives more and more nonterminals and is useless. Any recursively defined nonterminal without a production of deriving ɛ or a string of all terminals is useless! Direct useless. Indirect useless: one can only derive direct useless terms. From now on, nonterminals. we assume a grammar contains no useless Compiler notes #3, Tsan-sheng Hsu, IIS 17
18 Non-context free grammars Some grammar is not CFG, that is, it may be context sensitive. Expressive power of grammars (in the order of small to large): Regular expressions FA. Context-free grammar Context-sensitive {ωcω ω is a string of a and b s} cannot be expressed by CFG. Compiler notes #3, Tsan-sheng Hsu, IIS 18
19 Top-down parsing There are O(n 3 )-time algorithms to parse a language defined by CFG, where n is the number of input tokens. For practical purpose, we need faster algorithms. Here we make restrictions to CFG so that we can design O(n)-time algorithms. Recursive-descent parsing : top-down parsing that allows backtracking. Attempt to find a leftmost derivation for an input string. Try out all possibilities, that is, do an exhaustive search to find a parse tree that parses the input. Compiler notes #3, Tsan-sheng Hsu, IIS 19
20 Example for recursive-descent parsing S cad A bc a Input: cad S S S c A d c A d c A d b c a error!! backtrack Problems with the above approach: still too slow! want to select a derivation without ever causing backtracking! trick: use lookahead symbols. Solution: use LL(1) grammars that can be parsed in O(n) time. first L: scan the input from left-to-right second L: find a leftmost derivation (1): allow one lookahead token! Compiler notes #3, Tsan-sheng Hsu, IIS 20
21 Predictive parser for LL(1) grammars How a predictive parser works: start by pushing the starting nonterminal into the STACK and calling the scanner to get the first token. LOOP: if top-of-stack is a nonterminal, then use the current token and the PARSING TABLE to choose a production pop the nonterminal from the STACK and push the above production s right-hand-side GOTO LOOP. if top-of-stack is a terminal and matches the current token, then pop STACK and ask scanner to provide the next token GOTO LOOP. if STACK is empty and there is no more input, then ACCEPT! If none of the above succeed, then FAIL! STACK is empty and there is input left. top-of-stack is a terminal, but does not match the current token top-of-stack is a nonterminal, but the corresponding PARSING TA- BLE entry is ERROR! Compiler notes #3, Tsan-sheng Hsu, IIS 21
22 Example for parsing an LL(1) grammar grammar: S ɛ (S) [S] input: ([ ]) input stack action ( S pop, push (S) ( (S) pop, match with input ([ S) pop, push [S] ([ [S]) pop, match with input ([ ] S]) pop, push ɛ ([ ] ]) pop, match with input ([ ]) ) pop, match with input ([ ]) accept S ( S ) [ S ] ε leftmost derivation Use the current input token to decide which production to derive from the top-of-stack nonterminal. Compiler notes #3, Tsan-sheng Hsu, IIS 22
23 About LL(1) It is not always possible to build a predictive parser given a CFG; It works only if the CFG is LL(1)! For example, the following grammar is not LL(1), but is LL(2). Grammar: S (S) [S] () [ ] Try to parse the input (). input stack action ( S pop, but use which production? In this example, we need 2-token look-ahead. If the next token is ), push (). If the next token is (, push (S). Two questions: How to tell whether a grammar G is LL(1)? How to build the PARSING TABLE? Compiler notes #3, Tsan-sheng Hsu, IIS 23
24 Properties of non-ll(1) grammars Theorem 1: A CFG grammar is not LL(1) if it is left-recursive. Definitions: recursive grammar: a grammar is recursive if the following is true for a nonterminal X in G: X = + αxβ. G is left-recursive if X = + Xβ. G is immediately left-recursive if X = Xβ. Compiler notes #3, Tsan-sheng Hsu, IIS 24
25 Example of removing immediate left-recursion Need to remove left-recursion to come out an LL(1) grammar. Example: Grammar G: A Aα β, where β does not start with A Revised grammar G : A βa A αa ɛ The above two grammars are equivalent. That is L(G) L(G ). A A Example: input baa β b α a b A a a leftmost derivation original grammar G b A a A a A ε leftmost derivation revised grammar G Compiler notes #3, Tsan-sheng Hsu, IIS 25
26 Rule for removing immediate left-recursion Both grammars recognize the same string, left-recursive. but G is not However, G is clear and intuitive. General rule for removing immediately left-recursion: Replace A Aα 1 Aα m β 1 β n with A β 1 A β n A A α 1 A α m A ɛ This rule does not work if α i = ɛ for some i. This is called a direct cycle in a grammar. May need to worry about whether the semantics are equivalent between the original grammar and the transformed grammar. Compiler notes #3, Tsan-sheng Hsu, IIS 26
27 Algorithm 4.1 Algorithm 4.1 systematically eliminates left recursion and works only if the input grammar has no cycles or ɛ-productions. Cycle: A + = A ɛ-production: A ɛ It is possible to remove cycles and all but one ɛ-production using other algorithms. Input: grammar G without cycles and ɛ-productions. Output: An equivalent grammar without left recursion. Number the nonterminals in some order A 1, A 2,..., A n for i = 1 to n do for j = 1 to i 1 do replace A i A j γ with A i δ 1 γ δ k γ where A j δ 1 δ k are all the current A j -productions. Eliminate immediate left-recursion for A i New nonterminals generated above are numbered A i+n Compiler notes #3, Tsan-sheng Hsu, IIS 27
28 Algorithm 4.1 Discussions Intuition: Consider only the productions where the leftmost item on the right hand side are nonterminals. If it is always the case that A i + = Aj α implies i < j, then it is not possible to have left-recursion. Why cycles are not allowed? For the procedure of removing immediate left-recursion. Why ɛ-productions are not allowed? Inside the loop, when A j ɛ, that is some δ g = ɛ, and the prefix of γ is some A k where k < i, it generates A i A k, k < i. Compiler notes #3, Tsan-sheng Hsu, IIS 28
29 Trace an instance of Algorithm 4.1 After each i-loop, only productions of the form A i A k γ, i < k remain. i = 1 allow A 1 A k α, k before removing immediate left-recursion remove immediate left-recursion for A 1 i = 2 j = 1: replace A 2 A 1 γ by A 2 (A k1 α 1 A kp α p )γ, where A 1 (A k1 α 1 A kp α p ) and k j > 1 k j remove immediate left-recursion for A 2 i = 3 j = 1: replace A 3 A 1 γ 1 j = 2: replace A 3 A 2 γ 2 remove immediate left-recursion for A 3 Compiler notes #3, Tsan-sheng Hsu, IIS 29
30 Example Original Grammar: (1) S Aa b (2) A Ac Sd e Ordering of nonterminals: S A 1 and A A 2. i = 1 do nothing as there is no immediate left-recursion for S i = 2 replace A Sd by A Aad bd hence (2) becomes A Ac Aad bd e after removing immediate left-recursion: A bda ea A ca ada ɛ resulting grammar: S Aa b A bda ea A ca ada ɛ Compiler notes #3, Tsan-sheng Hsu, IIS 30
31 Second property for non-ll(1) grammars Theorem 2: G is not LL(1) if a nonterminal has two productions whose right-hand-sides have a common prefix. Have left-factors. Example: S (S) () In this example, the common prefix is (. This problem can be solved by using the left-factoring trick. A αβ 1 αβ 2 Transform to: A αa A β 1 β 2 Example: S (S) () Transform to S (S S S) ) Compiler notes #3, Tsan-sheng Hsu, IIS 31
32 Algorithm for left-factoring Input: context free grammar G Output: equivalent left-factored context-free grammar G for each nonterminal A do find the longest non-ɛ prefix α that is common to right-hand sides of two or more productions; replace A αβ 1 αβ n γ 1 γ m with A αa γ 1 γ m A β 1 β n repeat the above process until A has no two productions with a common prefix; Compiler notes #3, Tsan-sheng Hsu, IIS 32
33 Left-factoring and left-recursion removal Original grammar: S (S) SS () To remove immediate left-recursion, we have S (S)S ()S S SS ɛ To do left-factoring, we have S (S S S)S )S S SS ɛ A grammar is not LL(1) if it is left recursive or has left-factors. However, grammars that are not left recursive and have no left-factors may still not be LL(1). Compiler notes #3, Tsan-sheng Hsu, IIS 33
34 Definition of LL(1) grammars To see if a grammar is LL(1), we need to compute its FIRST and FOLLOW sets, which are used to build its parsing table. FIRST sets: Definition: let α be a sequence of terminals and/or nonterminals or ɛ FIRST(α) is the set of terminals that begin the strings derivable from α if α can derive ɛ, then ɛ FIRST(α) FIRST(α) = {t (t is a terminal and α = tβ) or ( t = ɛ and α = ɛ)} Compiler notes #3, Tsan-sheng Hsu, IIS 34
35 How to compute FIRST(X)? (1/2) X is a singleton. X is a terminal: FIRST(X) = {X} X is ɛ: FIRST(X) = {ɛ} X is a nonterminal: must check all productions with X on the left-hand side. That is, for all X Y 1 Y 2 Y k perform the following steps: put FIRST(Y 1 ) {ɛ} into FIRST(X) if ɛ FIRST(Y 1 ), then put FIRST(Y 2 ) {ɛ} into FIRST(X) if ɛ FIRST(Y k 1 ), then put FIRST(Y k ) {ɛ} into FIRST(X) if ɛ FIRST(Y i ) for each 1 i k, then put ɛ into FIRST(X) Compiler notes #3, Tsan-sheng Hsu, IIS 35
36 How to compute FIRST(X)? (2/2) Algorithm to compute FIRST s for all non-terminals. compute FIRST s for ɛ and all terminals; initialize FIRST s for all non-terminals to ; Repeat for all nonterminals X do apply the steps to compute F IRST (X) Until no items can be added to any FIRST set; The time complexity of this algorithm. at least one item, terminal or ɛ, is added to some FIRST set in an iteration; total number of items in all FIRST sets are ( T + 1) N, where T is the set of terminals and N is the set of nonterminals. O( N 2 T ). Compiler notes #3, Tsan-sheng Hsu, IIS 36
37 Example for computing FIRST(X) Start with computing FIRST for the last production and walk your way up. Grammar E E T E T E ɛ T F T T / F T ɛ F int (E) H E T FIRST(F ) = {int, (} FIRST(T ) = {/, ɛ} FIRST(T ) = {int, (}, since ɛ FIRST(F ), that s all. FIRST(E ) = {, ɛ} FIRST(H) = {, int, (} FIRST(E) = {, int, (}, since ɛ FIRST(E ). FIRST(ɛ) = {ɛ} Compiler notes #3, Tsan-sheng Hsu, IIS 37
38 How to compute FIRST(α)? Given FIRST(X) for each terminal and nonterminal X, compute FIRST(α) for α being a sequence of terminals and/or nonterminals To build a parsing table, we need FIRST(α) for all α such that X α is a production in the grammar. Let α = X 1 X 2 X n. Perform the following steps in sequence: put FIRST(X 1 ) {ɛ} into FIRST(α) if ɛ FIRST(X 1 ), then put FIRST(X 2 ) {ɛ} into FIRST(α) if ɛ FIRST(X n 1 ), then put FIRST(X n ) {ɛ} into FIRST(α) if ɛ FIRST(X i ) for each 1 i n, then put {ɛ} into FIRST(α). Compiler notes #3, Tsan-sheng Hsu, IIS 38
39 Example for computing FIRST(α) Grammar E E T E T E ɛ T F T T /F T ɛ F int (E) FIRST(F ) = {int, (} FIRST(T ) = {/, ɛ} FIRST(T ) = {int, (}, since ɛ FIRST(F ), that s all. FIRST(E ) = {, ɛ} FIRST(E) = {, int, (}, since ɛ FIRST(E ). FIRST(ɛ) = {ɛ} FIRST(E T ) = {, int, (} FIRST( T E ) = { } FIRST(ɛ) = {ɛ} FIRST(F T ) = {int, (} FIRST(/F T ) = {/} FIRST(ɛ) = {ɛ} FIRST(int) = {int} FIRST((E)) = {(} FIRST(T E ) = (FIRST(T ) {ɛ}) (FIRST(E ) {ɛ}) {ɛ} Compiler notes #3, Tsan-sheng Hsu, IIS 39
40 Why do we need FIRST(α)? During parsing, suppose top-of-stack is a nonterminal A and there are several choices A α 1 A α 2 A α k for derivation, and the current lookahead token is a If a FIRST(α i ), then pick A α i for derivation, pop, and then push α i. If a is in several FIRST(α i ) s, then the grammar is not LL(1). Question: if a is not in any FIRST(α i ), does this mean the input stream cannot be accepted? Maybe not! What happen if ɛ is in some FIRST(α i )? Compiler notes #3, Tsan-sheng Hsu, IIS 40
41 FOLLOW sets Assume there is a special EOF symbol $ ends every input. Add a new terminal $. Definition: for a nonterminal X, FOLLOW(X) is the set of terminals that can appear immediately to the right of X in some partial derivation. That is, S = + α 1 Xtα 2, where t is a terminal. If X can be the rightmost symbol in a derivation, then $ is in FOLLOW(X). FOLLOW(X) = {t (t is a terminal and S = + α 1 Xtα 2 ) or ( t is $ and S = + αx)}. Compiler notes #3, Tsan-sheng Hsu, IIS 41
42 How to compute FOLLOW(X)? If X is the starting nonterminal, put $ into FOLLOW(X). Find the productions with X on the right-hand-side. for each production of the form Y αxβ, put FIRST(β) {ɛ} into FOLLOW(X). if ɛ FIRST(β), then put FOLLOW(Y ) into FOLLOW(X). for each production of the form Y αx, put FOLLOW(Y ) into FOLLOW(X). Repeat the above process for all nonterminals until nothing can be added to any FOLLOW set. To see if a given grammar is LL(1) and also to build its parsing table: compute FIRST(α) for every production X α compute FOLLOW(X) for all nonterminals X Note that FIRST and FOLLOW sets are always sets of terminals, plus, perhaps, ɛ for some FIRST sets. Compiler notes #3, Tsan-sheng Hsu, IIS 42
43 A complete example Grammar S Bc DB B ab cs D d ɛ α FIRST(α) FOLLOW(α) D {d, ɛ} {a, c} B {a, c} {c, $} S {a, c, d} {c, $} Bc {a, c} DB {d, a, c} ab {a} cs {c} d {d} ɛ {ɛ} Compiler notes #3, Tsan-sheng Hsu, IIS 43
44 Why do we need FOLLOW sets? Note FOLLOW(S) always includes $. Situation: During parsing, the top-of-stack is a nonterminal X and the lookahead symbol is a. Assume there are several choices for the nest derivation: X α 1 X α k If a FIRST(α gi ) for only one g i, then we use that derivation. If a FIRST(α i ) for two i, then this grammar is not LL(1). If a FIRST(α i ) for all i, then this grammar can still be LL(1)! If there exists some g i such that α gi = ɛ and a FOLLOW(X), then we can can use the derivation X α gi. Compiler notes #3, Tsan-sheng Hsu, IIS 44
45 Grammars that are not LL(1) A grammar is not LL(1) if there exists productions A α β and any one of the followings is true: FIRST(α) FIRST(β). ɛ FIRST(α) and FIRST(β) FOLLOW(A). ɛ FIRST(α) and ɛ FIRST(β). If a grammar is not LL(1), then you cannot write a linear-time predictive parser as described above; If a grammar is not LL(1), then we do not know to use the production A α or the production A β when the lookahead symbol is a in the following cases, respectively, a FIRST(α) FIRST(β); a FIRST(β) FOLLOW(A); a FOLLOW(A). Compiler notes #3, Tsan-sheng Hsu, IIS 45
46 A complete example (1/2) Grammar: <prog head> PROG ID <file list> SEMICOLON <file list> ɛ L PAREN <file list> SEMICOLON FIRST and FOLLOW sets: α FIRST(α) FOLLOW(α) ɛ {ɛ} <prog head> {PROG} {$} <file list> {ɛ, L PAREN} {SEMICOLON} PROG ID <file list> SEMICOLON {PROG} L PAREN <file list> SEMICOLON {LPAREN} Compiler notes #3, Tsan-sheng Hsu, IIS 46
47 A complete example (2/2) Input: PROG ID SEMICOLON Input stack action <prog head> $ PROG <prog head> $ pop, push PROG PROG ID <file list> SEMICOLON $ match input ID ID <file list> SEMICOLON $ match input SEMICOLON <file list> SEMICOLON $ WHAT TO DO? Last actions: Two choices: <file list> ɛ L PAREN <file list> SEMICOLON SEMICOLON FIRST(ɛ) and SEMICOLON FIRST(L PAREN <file list> SEMICOLON) <file list> = ɛ SEMICOLON FOLLOW(<file list>) Hence we use the derivation <file list> ɛ Compiler notes #3, Tsan-sheng Hsu, IIS 47
48 LL(1) parsing table (1/2) Grammar: S XC X a ɛ C a ɛ α FIRST(α) FOLLOW(α) S {a, ɛ} {$} X {a, ɛ} {a, $} C {a, ɛ} {$} ɛ {ɛ} a {a} XC {a, ɛ} Check for possible conflicts in X a ɛ. FIRST(a) FIRST(ɛ) = ɛ FIRST(ɛ) and FOLLOW(X) FIRST(a) = {a} Conflict!! ɛ FIRST(a) Check for possible conflicts in C a ɛ. FIRST(a) FIRST(ɛ) = ɛ FIRST(ɛ) and FOLLOW(C) FIRST(a) = ɛ FIRST(a) Compiler notes #3, Tsan-sheng Hsu, IIS 48
49 LL(1) parsing table (2/2) Parsing table: a $ S S XC S XC X conflict X ɛ C C a C ɛ Compiler notes #3, Tsan-sheng Hsu, IIS 49
50 Bottom-up parsing (Shift-reduce parsers) Intuition: construct the parse tree from the leaves to the root. Grammar: S AB A S B A B A Example: A x Y B w Z x w x w x w x w Y xb Z wp Input xw. This grammar is not LL(1). Compiler notes #3, Tsan-sheng Hsu, IIS 50
51 Rightmost derivation: S = rm S + = rm Definitions (1/2) α: the rightmost nonterminal is replaced. α: α is derived from S using one or more rightmost derivations. α is called a right-sentential form. In the previous example: S = AB = Aw = xw. rm rm rm Define similarly leftmost derivations. handle : a handle for a right-sentential form γ is the combining of the following two information: a production rule A β and a position in γ where β can be found. Compiler notes #3, Tsan-sheng Hsu, IIS 51
52 Definitions (2/2) Example: S aabe A Abc b B d input: abbcde γ aabcde is a right-sentential form A Abc and position 2 in γ is a handle for γ reduce : replace a handle in a right-sentential form with its left-hand-side. In the above example, replace Abc in γ with A. A right-most derivation in reverse can be obtained by handle reducing. Compiler notes #3, Tsan-sheng Hsu, IIS 52
53 STACK implementation Four possible actions: shift: shift the input to STACK. reduce: perform a reversed rightmost derivation. accept error STACK INPUT ACTION $ xw$ shift $x w$ reduce by A x $A w$ shift $Aw $ reduce by B w $AB $ reduce by S AB $S $ accept A S B A B A x w x w x w x w S = AB = Aw = rm rm rm xw. Compiler notes #3, Tsan-sheng Hsu, IIS 53
54 Viable prefix Definition: the set of prefixes of right sentential forms that can appear on the top of the stack. Some prefix cannot appear on the top of the stack during parsing. xw is a right sentential form. The prefix xw is not a viable prefix. You cannot have the situation that the suffix of xw is a handle. Note: when doing bottom-up, that is reversed rightmost derivation, the first reduction must be from a handle that is a prefix of the input string; it cannot be the case a handle on the right is reduced before a handle on the left in a right sentential form; the handle can be found on the top of the stack; Compiler notes #3, Tsan-sheng Hsu, IIS 54
55 Model of a shift-reduce parser stack $ s 0 s 1... sm a 0 a 1... a i... a n $ driver action table GOTO table input output Push-down automata! Current state S m encodes the symbols that has been shifted and the handles that are currently being matched. $S 0 S 1 S m a i a i+1 a n $ represents a right sentential form. GOTO table: when a reduce action is taken, which handle to replace; Action table: when a shift action is taken, which state currently in, that is, how to group symbols into handles. The power of context free grammars is equivalent to nondeterministic push down automata. Compiler notes #3, Tsan-sheng Hsu, IIS 55
56 LR parsers By Don Knuth at LR(k): see all of what can be derived from the right side with k input tokens lookahead. first L: scan the input from left to right second R: reverse rightmost derivation (k): with k lookahead tokens. Be able to decide the whereabout of a handle after seeing all of what have been derived so far plus k input tokens lookahead. x 1, x 2,..., x i, x i+1,..., x i+j, x i+j+1,..., x i+j+k 1,... a handle lookahead tokens Top-down parsing for LL(k) grammars: be able to choose a production by seeing only the first k symbols that will be derived from that production. Compiler notes #3, Tsan-sheng Hsu, IIS 56
57 LR(0) parsing Construct an FSA to recognize all possible viable prefixes. An LR(0) item ( item for short) is a production, with a dot at some position in the RHS (right-hand side). For example: A XY Z A XY Z A X Y Z A XY Z A XY Z A ɛ A The dot indicates the place of a handle. Assume G is a grammar with the starting symbol S. Augmented grammar G is to add a new starting symbol S and a new production S S to G. We assume working on the augmented grammar from now on. Compiler notes #3, Tsan-sheng Hsu, IIS 57
58 Closure The closure operation closure(i), where I is a set of items, is defined by the following algorithm: If A α Bβ is in closure(i), then at some point in parsing, we might see a substring derivable from Bβ as input; if B γ is a production, we also see a substring derivable from γ at this point. Thus B γ should also be in closure(i). What does closure(i) mean informally? When A α Bβ is encountered during parsing, then this means we have seen α so far, and expect to see Bβ later before reducing to A. At this point if B γ is a production, then we may also want to see B γ in order to reduce to B, and then advance to A αb β. Using closure(i) to record all possible things that we have seen in the past and expect to see in the future. Compiler notes #3, Tsan-sheng Hsu, IIS 58
59 Example for the closure function Example: E is the new starting symbol, and E is the original starting symbol. E E E E + T T T T F F F (E) id closure({e E}) = {E E, E E + T, E T, T T F, T F, F (E), F id} Compiler notes #3, Tsan-sheng Hsu, IIS 59
60 GOTO table GOT O(I, X), where I is a set of items and X is a legal symbol, means If A α Xβ is in I, then closure({a αx β}) GOT O(I, X) Informal meanings: currently we have seen A α Xβ expect to see X if we see X, then we should be in the state closure({a αx β}). Use the GOTO table to denote the state to go to once we are in I and have seen X. Compiler notes #3, Tsan-sheng Hsu, IIS 60
61 Sets-of-items construction Canonical LR(0) items : the set of all possible DFA states, where each state is a set of LR(0) items. Algorithm for constructing LR(0) parsing table. C {closure({s S})} repeat for each set of items I in C and each grammar symbol X such that GOT O(I, X) and not in C do add GOT O(I, X) to C until no more sets can be added to C Kernel of a state: items not of the form X β or of the form S S Given the kernel of a state, all items in the state can be derived. Compiler notes #3, Tsan-sheng Hsu, IIS 61
62 Example of sets of LR(0) items I 0 = closure({e E}) = {E E, Grammar: E E E E + T T T T F F F (E) id E E + T, E T, T T F, T F, F (E), Canonical LR(0) items: I 1 = GOT O(I 0, E) = {E E, E E +T } I 2 = GOT O(I 0, T ) = {E T, T T F } F id} Compiler notes #3, Tsan-sheng Hsu, IIS 62
63 Transition diagram (1/2) E + T * I 0 I1 I6 I9 I F I3 ( I4 id I5 T * F I2 I7 I10 ( I4 F I ( id 3 I5 ( E ) I I 4 8 I11 id T id F + I I 6 5 I2 I 3 7 Compiler notes #3, Tsan-sheng Hsu, IIS 63
64 Transition diagram (2/2) id I 0 E >.E E >. E+T E >.T T >.T*F T >.F F >.(E) F >.id ( F I 1 E + T E > E+. T E > E. T >. T*F E > E. + T T >.F F F >.(E) F >.id ( T I 2 E > T. T > T.*F * I 6 I 7 T > T*.F F >.(E) F >. id id I 5 I 4 F ( I 3 I 9 E > E+T. T > T.*F I 10 T > T*F. * I 7 id I 4 I 3 T > F. I 5 I 5 F > id. id I 4 F > (. E ) E >. E + T E >.T T >. T * F T >. F F >. ( E ) F >. id E F T I 8 F > ( E. ) E > E. + T I 2 ) + I 6 I 11 F > ( E ). ( I 3 Compiler notes #3, Tsan-sheng Hsu, IIS 64
65 Meaning of LR(0) transition diagram E + T is a viable prefix that can happen on the top of the stack while doing parsing. after seeing E + T, we are in state I 7. I 7 = {T T F, F (E), F id} We expect to follow one of the following three possible derivations: E = rm = rm = rm = rm = rm E E + T E + T F E + T id E + T F id E = rm = rm = rm = rm E E + T E + T F E + T (E) E = rm = rm = rm = rm E E + T E + T F E + T id Compiler notes #3, Tsan-sheng Hsu, IIS 65
66 Definitions of closure(i) and GOT O(I, X) closure(i): a state/configuration during parsing recording all possible things that we are expecting. If A α Bβ I, then it means in the middle of parsing, α is on the top of the stack; at this point, we are expecting to see Bβ; after we saw Bβ, we will reduce αbβ to A and make A top of stack. To achieve the goal of seeing Bβ, we expect to perform some operations below: We expect to see B on the top of the stack first. If B γ is a production, then it might be the case that we shall see γ on the top of the stack. If it does, we reduce γ to B. Hence we need to include B γ into closure(i). GOT O(I, X): when we are in the state described by I, and then a new symbol X is pushed into the stack, If A α Xβ is in I, then closure({a αx β}) GOT O(I, X). Compiler notes #3, Tsan-sheng Hsu, IIS 66
67 Parsing example Input: id * id + id STACK input action $ I 0 id*id+id$ $ I 0 id I 5 * id + id$ shift 5 $ I 0 F * id + id$ reduce by F id $ I 0 F I 3 * id + id$ in I 0, saw F, goto I 3 $ I 0 T I 2 * id + id$ reduce by T F $ I 0 T I 2 * I 7 id + id$ shift 7 $ I 0 T I 2 * I 7 id I 5 + id$ shift 5 $ I 0 T I 2 * I 7 F I 10 + id$ reduce by F id $ I 0 T I 2 + id$ reduce by T F $ I 0 E I 1 + id$ reduce by T T F $ I 0 E I 1 + I 6 id$ shift 6 $ I 0 E I 1 + I 6 id I 5 $ shift 5 $ I 0 E I 1 + I 6 F I 3 $ reduce by F id Compiler notes #3, Tsan-sheng Hsu, IIS 67
68 LR(0) parsing LR parsing without lookahead symbols. Constructed from DFA for recognizing viable prefixes. In state I i if A α aβ is in I i then perform shift while seeing the terminal a in the input, and then go to the state closure({a αa β}) if A β is in I i, then perform reduce by A β and then go to the state GOT O(I, A) where I is the state on the top of the stack after removing β Conflicts: shift/reduce conflict reduce/reduce conflict Very few grammars are LR(0). For example: In I 2, you can either perform a reduce or a shift when seeing * in the input However, it is not possible to have E followed by *. Thus we should not perform reduce. Use FOLLOW(E) as look ahead information to resolve some conflicts. Compiler notes #3, Tsan-sheng Hsu, IIS 68
69 SLR(1) parsing algorithm Using FOLLOW sets to resolve conflicts in constructing SLR(1) parsing table, where the first S stands for simple. Input: an augmented grammar G Output: the SLR(1) parsing table Construct C = {I 0, I 1,..., I n } the collection of sets of LR(0) items for G. The parsing table for state I i is determined as follows: If A α aβ is in I i and GOT O(I i, a) = I j, then action(i i, a) is shift j for a being a terminal. If A α is in I i, then action(i i, a) is reduce by A α for all terminal a FOLLOW(A); here A S If S S is in I i, then action(i i, $) is accept. If any conflicts are generated by the above algorithm, we say the grammar is not SLR(1). Compiler notes #3, Tsan-sheng Hsu, IIS 69
70 SLR(1) parsing table action GOTO state id + * ( ) $ E T F 0 s5 s s6 accept 2 r2 s7 r2 r2 3 r4 r4 r4 r4 4 s5 s r6 r6 r6 r6 6 s5 s s5 s s6 s11 9 r1 s7 r1 r1 10 r3 r3 r3 r3 11 r5 r5 r5 r5 ri means reduce by production numbered i. si means shift and then go to state I i. Use FOLLOW sets to resolve some conflicts. Compiler notes #3, Tsan-sheng Hsu, IIS 70
71 Discussion (1/3) Every SLR(1) grammar is unambiguous, but there are many unambiguous grammars that are not SLR(1). Example: S L = R R L R id R L States: I 0 : S S S L = R S R L R L id R L I 1 : S S I 2 : S L = R R L Compiler notes #3, Tsan-sheng Hsu, IIS 71
72 Discussion (2/3) I 3 : S R I 4 : L R R L L R L id I 5 : L id I 6 : S L = R R L L R L id I 7 : L R I 8 : R L id I 0 S >.S S >.L = R S >.R L >. * R L >. id R >. L * L I 5 L > id. * S I 4 L > *. R R >. L L >. * R L >. id I 1 S > S. L I 2 = R I 8 R > L. R S > L. = R R > L. I 3 S > R. I 7 L > * R. * I 6 S > L =. R R >. L L >. * R L >. id I 9 R S > L = R. I 9 : S L = R Compiler notes #3, Tsan-sheng Hsu, IIS 72
73 Discussion (3/3) Suppose the stack has $I 0 LI 2 and the input is =. We can either shift 6, or reduce by R L, since = FOLLOW(R). This grammar is ambiguous for SLR(1) parsing. However, we should not perform a R L reduction. After performing the reduction, the viable prefix is $R; = FOLLOW($R); = FOLLOW( R); That is to say, we cannot find a right sentential form with the prefix R =. We can find a right sentential form with R = Compiler notes #3, Tsan-sheng Hsu, IIS 73
74 Canonical LR LR(1) In SLR(1) parsing, if A α is in state I i, and a FOLLOW(A), then we perform the reduction A α. However, it is possible that when state I i is on the top of the stack, we have viable prefix βα on the top of the stack, and βa cannot be followed by a. In this case, we cannot perform the reduction A α. It looks difficult to find the FOLLOW sets for every viable prefix. We can solve the problem by knowing more left context using the technique of lookahead propagation. Compiler notes #3, Tsan-sheng Hsu, IIS 74
75 LR(1) items An LR(1) item is in the form of [A α β, a], where the first field is an LR(0) item and the second field a is a terminal belonging to a subset of FOLLOW(A). Intuition: perform a reduction based on an LR(1) item [A α, a] only when the next symbol is a. Formally: [A α β, a] is valid (or reachable) for a viable prefix γ if there exists a derivation S = δaω = rm rm δαβω, where γ = δα either a FIRST(ω) or ω = ɛ and a = $. Compiler notes #3, Tsan-sheng Hsu, IIS 75
76 LR(1) parsing example Grammar: S BB B ab b S = aabab = aaabab rm rm viable prefix aaa can reach [B a B, a] S = BaB = BaaB rm rm viable prefix Baa can reach [B a B, $] Compiler notes #3, Tsan-sheng Hsu, IIS 76
77 Finding all LR(1) items Ideas: redefine the closure function. Suppose [A α Bβ, a] is valid for a viable prefix γ δα. In other words, S = δaaω = δαbβaω. rm rm Then for each production B η, assume βaω derives the sequence of terminals bc. S = rm δαb βaω = rm δαb bc = rm δα η bc Thus [B η, b] is also valid for γ for each b FIRST(βa). Note a is a terminal. So FIRST(βa) = FIRST(βaω). Lookahead propagation. Compiler notes #3, Tsan-sheng Hsu, IIS 77
78 Algorithm for LR(1) parsers closure 1 (I) repeat for each item [A α Bβ, a] in I do if B η is in G then add [B η, b] to I for each b FIRST(βa) until no more items can be added to I return I GOT O 1 (I, X) let J = {[A αx β, a] [A α Xβ, a] I}; return closure 1 (J) items(g ) C {closure 1 ({[S S, $]})} repeat for each set of items I C and each grammar symbol X such that GOT O 1 (I, X) and GOT O 1 (I, X) C do add GOT O 1 (I, X) to C until no more sets of items can be added to C Compiler notes #3, Tsan-sheng Hsu, IIS 78
79 Example for constructing LR(1) closures Grammar: S S S CC C cc d closure 1 ({[S S, $]}) = {[S S, $], [S CC, $], [C cc, c/d], [C d, c/d]} Note: FIRST(ɛ$) = {$} FIRST(C$) = {c, d} [C cc, c/d] means [C cc, c] and [C cc, d]. Compiler notes #3, Tsan-sheng Hsu, IIS 79
80 LR(1) Transition diagram d I 0 S >. S, $ S >. CC, $ C >. cc, c/d C >.d, c/d d c I 3 C C > c.c, c/d C >.cc, c/d C >.d, c/d S I 2 S > C.C, $ C >.cc, $ C >.d, $ C c I 8 C > cc., c/d I 1 S > S., $ C c d I 5 S > CC., $ I 6 C > c.c, $ C >.cc, $ C >.d, $ d I 7 C > d., $ c C I 9 C > cc., $ I 4 C > d., c/d Compiler notes #3, Tsan-sheng Hsu, IIS 80
81 LR(1) parsing example Input cdccd STACK INPUT ACTION $ I 0 cdccd$ $ I 0 c I 3 dccd$ shift 3 $ I 0 c I 3 d I 4 ccd$ shift 4 $ I 0 c I 3 C I 8 ccd$ reduce by C d $ I 0 C I 2 ccd$ reduce by C cc $ I 0 C I 2 c I 6 cd$ shift 6 $ I 0 C I 2 c I 6 c I 6 d$ shift 6 $ I 0 C I 2 c I 6 c I 6 d$ shift 6 $ I 0 C I 2 c I 6 c I 6 d I 7 $ shift 7 $ I 0 C I 2 c I 6 c I 6 C I 9 $ reduce by C cc $ I 0 C I 2 c I 6 C I 9 $ reduce by C cc $ I 0 C I 2 C I 5 $ reduce by S CC $ I 0 S I 1 $ reduce by S S $I 0 S $ accept Compiler notes #3, Tsan-sheng Hsu, IIS 81
82 Generating LR(1) parsing table Construction of canonical LR(1) parsing tables. Input: an augmented grammar G Output: the canonical LR(1) parsing table, i.e., the ACT ION 1 table Construct C = {I 0, I 1,..., I n } the collection of sets of LR(1) items form G. Action table is constructed as follows: if [A α aβ, b] I i and GOT O 1 (I i, a) = I j, then action 1 [I i, a] = shift j for a is a terminal. if [A α, a] I i and A S, then action 1 [I i, a] = reduce by A α if [S S., $] I i, then action 1 [I i, $] = accept. If conflicts result from the above rules, then the grammar is not LR(1). The initial state of the parser is the one constructed from the set containing the item [S S, $]. Compiler notes #3, Tsan-sheng Hsu, IIS 82
83 Example of an LR(1) parsing table action 1 GOTO 1 state c d $ S C 0 s3 s accept 2 s6 s7 5 3 s3 s4 8 4 r3 r3 5 r1 6 s6 s7 9 7 r3 8 r2 r2 9 r2 Canonical LR(1) parser: Most powerful! Has too many states and thus occupy too much space. Compiler notes #3, Tsan-sheng Hsu, IIS 83
84 LALR(1) parser Lookahead LR The method that is often used in practice. Most common syntactic constructs of programming languages can be expressed conveniently by an LALR(1) grammar. SLR(1) and LALR(1) always have the same number of states. Number of states is about 1/10 of that of LR(1). Simple observation: an LR(1) item is of the form [A α β, c] We call A α β the first component. Definition: in an LR(1) state, set of first components is called its core. Compiler notes #3, Tsan-sheng Hsu, IIS 84
85 Intuition for LALR(1) grammars In an LR(1) parser, it is a common thing that several states only differ in lookahead symbols, but have the same core. To reduce the number of states, we might want to merge states with the same core. If I 4 and I 7 are merged, then the new state is called I 4,7 After merging the states, revise the GOT O 1 table accordingly. Merging of states can never produce a shift-reduce conflict that was not present in one of the original states. I 1 = {[A α, a],...} I 2 = {[B β aγ, b],...} For I 1, we perform a reduce on a. For I 2, we perform a shift on a. Merging I 1 and I 2, the new state I 1,2 has shift-reduce conflicts. This is impossible! In the original table, I 1 and I 2 have the same core. [A α, c] I 2 and [B β aγ, d] I 1. The shift-reduce conflict already occurs in I 1 and I 2. Compiler notes #3, Tsan-sheng Hsu, IIS 85
86 LALR(1) Transition diagram d I 0 S >. S, $ S >. CC, $ C >. cc, c/d C >.d, c/d c I 3 C C > c.c, c/d C >.cc, c/d C >.d, c/d S I 2 S > C.C, $ C >.cc, $ C >.d, $ c I 1 S > S., $ C c d I 5 S > CC., $ I 6 C > c.c, $ C >.cc, $ C >.d, $ c C d C d I 8 C > cc., c/d I 9 C > cc., $ I 4 C > d., c/d I 7 C > d., $ Compiler notes #3, Tsan-sheng Hsu, IIS 86
87 Possible new conflicts from LALR(1) May produce a new reduce-reduce conflict. For example (textbook page 238), grammar: S S S aad bbf abe bae A c B c The language recognized by this grammar is {acd, ace, bcd, bce}. You may check that this grammar is LR(1) by constructing the sets of items. You will find the set of items {[A c, d], [B c, e]} is valid for the viable prefix ac, and {[A c, e], [B c, d]} is valid for the viable prefix bc. Neither of these sets generates a conflict, and their cores are the same. However, their union, which is {[A c, d/e], [B c, d/e]} generates a reduce-reduce conflict, since reductions by both A c and B c are called for on inputs d and e. Compiler notes #3, Tsan-sheng Hsu, IIS 87
88 How to construct LALR(1) parsing table Naive approach: Construct LR(1) parsing table, which takes lots of intermediate spaces. Merging states. Space efficient methods to construct an LALR(1) parsing table are known. Construction and merging on the fly. Compiler notes #3, Tsan-sheng Hsu, IIS 88
89 Summary LALR(1) LALR(1) LL(1) LR(1) SLR(1) LR(1) SLR(1) LR(0) LR(1) and LALR(1) can almost handle all programming languages, but LALR(1) is easier to write and uses much less space. LL(1) is easier to understand, but cannot handle several important common-language features. Compiler notes #3, Tsan-sheng Hsu, IIS 89
Helena Boguta, klasa 8W, rok szkolny 2018/2019
Poniższy zbiór zadań został wykonany w ramach projektu Mazowiecki program stypendialny dla uczniów szczególnie uzdolnionych - najlepsza inwestycja w człowieka w roku szkolnym 2018/2019. Składają się na
SSW1.1, HFW Fry #20, Zeno #25 Benchmark: Qtr.1. Fry #65, Zeno #67. like
SSW1.1, HFW Fry #20, Zeno #25 Benchmark: Qtr.1 I SSW1.1, HFW Fry #65, Zeno #67 Benchmark: Qtr.1 like SSW1.2, HFW Fry #47, Zeno #59 Benchmark: Qtr.1 do SSW1.2, HFW Fry #5, Zeno #4 Benchmark: Qtr.1 to SSW1.2,
Zakopane, plan miasta: Skala ok. 1: = City map (Polish Edition)
Zakopane, plan miasta: Skala ok. 1:15 000 = City map (Polish Edition) Click here if your download doesn"t start automatically Zakopane, plan miasta: Skala ok. 1:15 000 = City map (Polish Edition) Zakopane,
OpenPoland.net API Documentation
OpenPoland.net API Documentation Release 1.0 Michał Gryczka July 11, 2014 Contents 1 REST API tokens: 3 1.1 How to get a token............................................ 3 2 REST API : search for assets
Hard-Margin Support Vector Machines
Hard-Margin Support Vector Machines aaacaxicbzdlssnafiyn9vbjlepk3ay2gicupasvu4iblxuaw2hjmuwn7ddjjmxm1bkcg1/fjqsvt76fo9/gazqfvn8y+pjpozw5vx8zkpvtfxmlhcwl5zxyqrm2vrg5zw3vxmsoezi4ogkr6phieky5crvvjhriqvdom9l2xxftevuwcekj3lktmhghgniauiyutvrwxtvme34a77kbvg73gtygpjsrfati1+xc8c84bvraowbf+uwnipyehcvmkjrdx46vlykhkgykm3ujjdhcyzqkxy0chur6ax5cbg+1m4bbjptjcubuz4kuhvjoql93hkin5hxtav5x6yyqopnsyuneey5ni4keqrxbar5wqaxbik00icyo/iveiyqqvjo1u4fgzj/8f9x67bzmxnurjzmijtlybwfgcdjgfdtajwgcf2dwaj7ac3g1ho1n4814n7wwjgjmf/ys8fenfycuzq==
Tychy, plan miasta: Skala 1: (Polish Edition)
Tychy, plan miasta: Skala 1:20 000 (Polish Edition) Poland) Przedsiebiorstwo Geodezyjno-Kartograficzne (Katowice Click here if your download doesn"t start automatically Tychy, plan miasta: Skala 1:20 000
Revenue Maximization. Sept. 25, 2018
Revenue Maximization Sept. 25, 2018 Goal So Far: Ideal Auctions Dominant-Strategy Incentive Compatible (DSIC) b i = v i is a dominant strategy u i 0 x is welfare-maximizing x and p run in polynomial time
Weronika Mysliwiec, klasa 8W, rok szkolny 2018/2019
Poniższy zbiór zadań został wykonany w ramach projektu Mazowiecki program stypendialny dla uczniów szczególnie uzdolnionych - najlepsza inwestycja w człowieka w roku szkolnym 2018/2019. Tresci zadań rozwiązanych
TTIC 31210: Advanced Natural Language Processing. Kevin Gimpel Spring Lecture 9: Inference in Structured Prediction
TTIC 31210: Advanced Natural Language Processing Kevin Gimpel Spring 2019 Lecture 9: Inference in Structured Prediction 1 intro (1 lecture) Roadmap deep learning for NLP (5 lectures) structured prediction
Wojewodztwo Koszalinskie: Obiekty i walory krajoznawcze (Inwentaryzacja krajoznawcza Polski) (Polish Edition)
Wojewodztwo Koszalinskie: Obiekty i walory krajoznawcze (Inwentaryzacja krajoznawcza Polski) (Polish Edition) Robert Respondowski Click here if your download doesn"t start automatically Wojewodztwo Koszalinskie:
Karpacz, plan miasta 1:10 000: Panorama Karkonoszy, mapa szlakow turystycznych (Polish Edition)
Karpacz, plan miasta 1:10 000: Panorama Karkonoszy, mapa szlakow turystycznych (Polish Edition) J Krupski Click here if your download doesn"t start automatically Karpacz, plan miasta 1:10 000: Panorama
Stargard Szczecinski i okolice (Polish Edition)
Stargard Szczecinski i okolice (Polish Edition) Janusz Leszek Jurkiewicz Click here if your download doesn"t start automatically Stargard Szczecinski i okolice (Polish Edition) Janusz Leszek Jurkiewicz
Rachunek lambda, zima
Rachunek lambda, zima 2015-16 Wykład 2 12 października 2015 Tydzień temu: Własność Churcha-Rossera (CR) Jeśli a b i a c, to istnieje takie d, że b d i c d. Tydzień temu: Własność Churcha-Rossera (CR) Jeśli
ARNOLD. EDUKACJA KULTURYSTY (POLSKA WERSJA JEZYKOWA) BY DOUGLAS KENT HALL
Read Online and Download Ebook ARNOLD. EDUKACJA KULTURYSTY (POLSKA WERSJA JEZYKOWA) BY DOUGLAS KENT HALL DOWNLOAD EBOOK : ARNOLD. EDUKACJA KULTURYSTY (POLSKA WERSJA Click link bellow and free register
Machine Learning for Data Science (CS4786) Lecture 11. Spectral Embedding + Clustering
Machine Learning for Data Science (CS4786) Lecture 11 Spectral Embedding + Clustering MOTIVATING EXAMPLE What can you say from this network? MOTIVATING EXAMPLE How about now? THOUGHT EXPERIMENT For each
Katowice, plan miasta: Skala 1: = City map = Stadtplan (Polish Edition)
Katowice, plan miasta: Skala 1:20 000 = City map = Stadtplan (Polish Edition) Polskie Przedsiebiorstwo Wydawnictw Kartograficznych im. Eugeniusza Romera Click here if your download doesn"t start automatically
MaPlan Sp. z O.O. Click here if your download doesn"t start automatically
Mierzeja Wislana, mapa turystyczna 1:50 000: Mikoszewo, Jantar, Stegna, Sztutowo, Katy Rybackie, Przebrno, Krynica Morska, Piaski, Frombork =... = Carte touristique (Polish Edition) MaPlan Sp. z O.O Click
Machine Learning for Data Science (CS4786) Lecture11. Random Projections & Canonical Correlation Analysis
Machine Learning for Data Science (CS4786) Lecture11 5 Random Projections & Canonical Correlation Analysis The Tall, THE FAT AND THE UGLY n X d The Tall, THE FAT AND THE UGLY d X > n X d n = n d d The
Wojewodztwo Koszalinskie: Obiekty i walory krajoznawcze (Inwentaryzacja krajoznawcza Polski) (Polish Edition)
Wojewodztwo Koszalinskie: Obiekty i walory krajoznawcze (Inwentaryzacja krajoznawcza Polski) (Polish Edition) Robert Respondowski Click here if your download doesn"t start automatically Wojewodztwo Koszalinskie:
Machine Learning for Data Science (CS4786) Lecture 24. Differential Privacy and Re-useable Holdout
Machine Learning for Data Science (CS4786) Lecture 24 Differential Privacy and Re-useable Holdout Defining Privacy Defining Privacy Dataset + Defining Privacy Dataset + Learning Algorithm Distribution
www.irs.gov/form990. If "Yes," complete Schedule A Schedule B, Schedule of Contributors If "Yes," complete Schedule C, Part I If "Yes," complete Schedule C, Part II If "Yes," complete Schedule C, Part
Realizacja systemów wbudowanych (embeded systems) w strukturach PSoC (Programmable System on Chip)
Realizacja systemów wbudowanych (embeded systems) w strukturach PSoC (Programmable System on Chip) Embeded systems Architektura układów PSoC (Cypress) Możliwości bloków cyfrowych i analogowych Narzędzia
Compressing the information contained in the different indexes is crucial for performance when implementing an IR system
4.2 Compression Compressing the information contained in the different indexes is crucial for performance when implementing an IR system on current hardware it is typically much faster to read compressed
Proposal of thesis topic for mgr in. (MSE) programme in Telecommunications and Computer Science
Proposal of thesis topic for mgr in (MSE) programme 1 Topic: Monte Carlo Method used for a prognosis of a selected technological process 2 Supervisor: Dr in Małgorzata Langer 3 Auxiliary supervisor: 4
www.irs.gov/form990. If "Yes," complete Schedule A Schedule B, Schedule of Contributors If "Yes," complete Schedule C, Part I If "Yes," complete Schedule C, Part II If "Yes," complete Schedule C, Part
Installation of EuroCert software for qualified electronic signature
Installation of EuroCert software for qualified electronic signature for Microsoft Windows systems Warsaw 28.08.2019 Content 1. Downloading and running the software for the e-signature... 3 a) Installer
deep learning for NLP (5 lectures)
TTIC 31210: Advanced Natural Language Processing Kevin Gimpel Spring 2019 Lecture 6: Finish Transformers; Sequence- to- Sequence Modeling and AJenKon 1 Roadmap intro (1 lecture) deep learning for NLP (5
Pielgrzymka do Ojczyzny: Przemowienia i homilie Ojca Swietego Jana Pawla II (Jan Pawel II-- pierwszy Polak na Stolicy Piotrowej) (Polish Edition)
Pielgrzymka do Ojczyzny: Przemowienia i homilie Ojca Swietego Jana Pawla II (Jan Pawel II-- pierwszy Polak na Stolicy Piotrowej) (Polish Edition) Click here if your download doesn"t start automatically
Instrukcja konfiguracji usługi Wirtualnej Sieci Prywatnej w systemie Mac OSX
UNIWERSYTETU BIBLIOTEKA IEGO UNIWERSYTETU IEGO Instrukcja konfiguracji usługi Wirtualnej Sieci Prywatnej w systemie Mac OSX 1. Make a new connection Open the System Preferences by going to the Apple menu
Blow-Up: Photographs in the Time of Tumult; Black and White Photography Festival Zakopane Warszawa 2002 / Powiekszenie: Fotografie w czasach zgielku
Blow-Up: Photographs in the Time of Tumult; Black and White Photography Festival Zakopane Warszawa 2002 / Powiekszenie: Fotografie w czasach zgielku Juliusz and Maciej Zalewski eds. and A. D. Coleman et
Egzamin maturalny z języka angielskiego na poziomie dwujęzycznym Rozmowa wstępna (wyłącznie dla egzaminującego)
112 Informator o egzaminie maturalnym z języka angielskiego od roku szkolnego 2014/2015 2.6.4. Część ustna. Przykładowe zestawy zadań Przykładowe pytania do rozmowy wstępnej Rozmowa wstępna (wyłącznie
Miedzy legenda a historia: Szlakiem piastowskim z Poznania do Gniezna (Biblioteka Kroniki Wielkopolski) (Polish Edition)
Miedzy legenda a historia: Szlakiem piastowskim z Poznania do Gniezna (Biblioteka Kroniki Wielkopolski) (Polish Edition) Piotr Maluskiewicz Click here if your download doesn"t start automatically Miedzy
Wojewodztwo Koszalinskie: Obiekty i walory krajoznawcze (Inwentaryzacja krajoznawcza Polski) (Polish Edition)
Wojewodztwo Koszalinskie: Obiekty i walory krajoznawcze (Inwentaryzacja krajoznawcza Polski) (Polish Edition) Robert Respondowski Click here if your download doesn"t start automatically Wojewodztwo Koszalinskie:
TTIC 31210: Advanced Natural Language Processing. Kevin Gimpel Spring Lecture 8: Structured PredicCon 2
TTIC 31210: Advanced Natural Language Processing Kevin Gimpel Spring 2019 Lecture 8: Structured PredicCon 2 1 Roadmap intro (1 lecture) deep learning for NLP (5 lectures) structured predic+on (4 lectures)
Karpacz, plan miasta 1:10 000: Panorama Karkonoszy, mapa szlakow turystycznych (Polish Edition)
Karpacz, plan miasta 1:10 000: Panorama Karkonoszy, mapa szlakow turystycznych (Polish Edition) J Krupski Click here if your download doesn"t start automatically Karpacz, plan miasta 1:10 000: Panorama
Emilka szuka swojej gwiazdy / Emily Climbs (Emily, #2)
Emilka szuka swojej gwiazdy / Emily Climbs (Emily, #2) Click here if your download doesn"t start automatically Emilka szuka swojej gwiazdy / Emily Climbs (Emily, #2) Emilka szuka swojej gwiazdy / Emily
Convolution semigroups with linear Jacobi parameters
Convolution semigroups with linear Jacobi parameters Michael Anshelevich; Wojciech Młotkowski Texas A&M University; University of Wrocław February 14, 2011 Jacobi parameters. µ = measure with finite moments,
Rozpoznawanie twarzy metodą PCA Michał Bereta 1. Testowanie statystycznej istotności różnic między jakością klasyfikatorów
Rozpoznawanie twarzy metodą PCA Michał Bereta www.michalbereta.pl 1. Testowanie statystycznej istotności różnic między jakością klasyfikatorów Wiemy, że możemy porównywad klasyfikatory np. za pomocą kroswalidacji.
18. Przydatne zwroty podczas egzaminu ustnego. 19. Mo liwe pytania egzaminatora i przyk³adowe odpowiedzi egzaminowanego
18. Przydatne zwroty podczas egzaminu ustnego I m sorry, could you repeat that, please? - Przepraszam, czy mo na prosiæ o powtórzenie? I m sorry, I don t understand. - Przepraszam, nie rozumiem. Did you
DODATKOWE ĆWICZENIA EGZAMINACYJNE
I.1. X Have a nice day! Y a) Good idea b) See you soon c) The same to you I.2. X: This is my new computer. Y: Wow! Can I have a look at the Internet? X: a) Thank you b) Go ahead c) Let me try I.3. X: What
Jak zasada Pareto może pomóc Ci w nauce języków obcych?
Jak zasada Pareto może pomóc Ci w nauce języków obcych? Artykuł pobrano ze strony eioba.pl Pokazuje, jak zastosowanie zasady Pareto może usprawnić Twoją naukę angielskiego. Słynna zasada Pareto mówi o
ERASMUS + : Trail of extinct and active volcanoes, earthquakes through Europe. SURVEY TO STUDENTS.
ERASMUS + : Trail of extinct and active volcanoes, earthquakes through Europe. SURVEY TO STUDENTS. Strona 1 1. Please give one answer. I am: Students involved in project 69% 18 Student not involved in
Wojewodztwo Koszalinskie: Obiekty i walory krajoznawcze (Inwentaryzacja krajoznawcza Polski) (Polish Edition)
Wojewodztwo Koszalinskie: Obiekty i walory krajoznawcze (Inwentaryzacja krajoznawcza Polski) (Polish Edition) Robert Respondowski Click here if your download doesn"t start automatically Wojewodztwo Koszalinskie:
Knovel Math: Jakość produktu
Knovel Math: Jakość produktu Knovel jest agregatorem materiałów pełnotekstowych dostępnych w formacie PDF i interaktywnym. Narzędzia interaktywne Knovel nie są stworzone wokół specjalnych algorytmów wymagających
Surname. Other Names. For Examiner s Use Centre Number. Candidate Number. Candidate Signature
A Surname _ Other Names For Examiner s Use Centre Number Candidate Number Candidate Signature Polish Unit 1 PLSH1 General Certificate of Education Advanced Subsidiary Examination June 2014 Reading and
Wojewodztwo Koszalinskie: Obiekty i walory krajoznawcze (Inwentaryzacja krajoznawcza Polski) (Polish Edition)
Wojewodztwo Koszalinskie: Obiekty i walory krajoznawcze (Inwentaryzacja krajoznawcza Polski) (Polish Edition) Robert Respondowski Click here if your download doesn"t start automatically Wojewodztwo Koszalinskie:
Stability of Tikhonov Regularization Class 07, March 2003 Alex Rakhlin
Stability of Tikhonov Regularization 9.520 Class 07, March 2003 Alex Rakhlin Plan Review of Stability Bounds Stability of Tikhonov Regularization Algorithms Uniform Stability Review notation: S = {z 1,...,
How to translate Polygons
How to translate Polygons Translation procedure. 1) Open polygons.img in Imagine 2) Press F4 to open Memory Window 3) Find and edit tlumacz class, edit all the procedures (listed below) 4) Invent a new
Wybrzeze Baltyku, mapa turystyczna 1: (Polish Edition)
Wybrzeze Baltyku, mapa turystyczna 1:50 000 (Polish Edition) Click here if your download doesn"t start automatically Wybrzeze Baltyku, mapa turystyczna 1:50 000 (Polish Edition) Wybrzeze Baltyku, mapa
Karpacz, plan miasta 1:10 000: Panorama Karkonoszy, mapa szlakow turystycznych (Polish Edition)
Karpacz, plan miasta 1:10 000: Panorama Karkonoszy, mapa szlakow turystycznych (Polish Edition) J Krupski Click here if your download doesn"t start automatically Karpacz, plan miasta 1:10 000: Panorama
Miedzy legenda a historia: Szlakiem piastowskim z Poznania do Gniezna (Biblioteka Kroniki Wielkopolski) (Polish Edition)
Miedzy legenda a historia: Szlakiem piastowskim z Poznania do Gniezna (Biblioteka Kroniki Wielkopolski) (Polish Edition) Piotr Maluskiewicz Click here if your download doesn"t start automatically Miedzy
Wroclaw, plan nowy: Nowe ulice, 1:22500, sygnalizacja swietlna, wysokosc wiaduktow : Debica = City plan (Polish Edition)
Wroclaw, plan nowy: Nowe ulice, 1:22500, sygnalizacja swietlna, wysokosc wiaduktow : Debica = City plan (Polish Edition) Wydawnictwo "Demart" s.c Click here if your download doesn"t start automatically
SubVersion. Piotr Mikulski. SubVersion. P. Mikulski. Co to jest subversion? Zalety SubVersion. Wady SubVersion. Inne różnice SubVersion i CVS
Piotr Mikulski 2006 Subversion is a free/open-source version control system. That is, Subversion manages files and directories over time. A tree of files is placed into a central repository. The repository
JĘZYK ANGIELSKI ĆWICZENIA ORAZ REPETYTORIUM GRAMATYCZNE
MACIEJ MATASEK JĘZYK ANGIELSKI ĆWICZENIA ORAZ REPETYTORIUM GRAMATYCZNE 1 Copyright by Wydawnictwo HANDYBOOKS Poznań 2014 Wszelkie prawa zastrzeżone. Każda reprodukcja lub adaptacja całości bądź części
www.irs.gov/form990. If "Yes," complete Schedule A Schedule B, Schedule of Contributors If "Yes," complete Schedule C, Part I If "Yes," complete Schedule C, Part II If "Yes," complete Schedule C, Part
European Crime Prevention Award (ECPA) Annex I - new version 2014
European Crime Prevention Award (ECPA) Annex I - new version 2014 Załącznik nr 1 General information (Informacje ogólne) 1. Please specify your country. (Kraj pochodzenia:) 2. Is this your country s ECPA
Marzec: food, advertising, shopping and services, verb patterns, adjectives and prepositions, complaints - writing
Wymagania na podstawie Podstawy programowej kształcenia ogólnego dla szkoły podstawowej język obcy oraz polecanego podręcznika New Matura Success Intermediate * Cele z podstawy programowej: rozumienie
!850016! www.irs.gov/form8879eo. e-file www.irs.gov/form990. If "Yes," complete Schedule A Schedule B, Schedule of Contributors If "Yes," complete Schedule C, Part I If "Yes," complete Schedule C,
Gradient Coding using the Stochastic Block Model
Gradient Coding using the Stochastic Block Model Zachary Charles (UW-Madison) Joint work with Dimitris Papailiopoulos (UW-Madison) aaacaxicbvdlssnafj3uv62vqbvbzwarxjsqikaboelgzux7gcaeywtsdp1mwsxeaepd+ctuxcji1r9w5984bbpq1gmxdufcy733bcmjutn2t1fawl5zxsuvvzy2t7z3zn29lkwyguktjywrnqbjwigntuuvi51uebqhjlsdwfxebz8qiwnc79uwjv6mepxgfcoljd88uiox0m1hvlnzwzgowymjn7tjyzertmvpareju5aqkndwzs83thawe64wq1j2httvxo6eopirccxnjekrhqae6wrkuuykl08/gmnjryqwsoqurubu/t2ro1jkyrzozhipvpz3juj/xjdt0ywxu55mina8wxrldkoetukairuekzbubgfb9a0q95fawonqkjoez/7lrdi6trzbcm7pqvwrio4yoarh4aq44bzuwq1ogcba4be8g1fwzjwzl8a78tfrlrnfzd74a+pzb2h+lzm=
EPS. Erasmus Policy Statement
Wyższa Szkoła Biznesu i Przedsiębiorczości Ostrowiec Świętokrzyski College of Business and Entrepreneurship EPS Erasmus Policy Statement Deklaracja Polityki Erasmusa 2014-2020 EN The institution is located
Analysis of Movie Profitability STAT 469 IN CLASS ANALYSIS #2
Analysis of Movie Profitability STAT 469 IN CLASS ANALYSIS #2 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
Zdecyduj: Czy to jest rzeczywiście prześladowanie? Czasem coś WYDAJE SIĘ złośliwe, ale wcale takie nie jest.
Zdecyduj: Czy to jest rzeczywiście prześladowanie? Czasem coś WYDAJE SIĘ złośliwe, ale wcale takie nie jest. Miłe przezwiska? Nie wszystkie przezwiska są obraźliwe. Wiele przezwisk świadczy o tym, że osoba,
DUAL SIMILARITY OF VOLTAGE TO CURRENT AND CURRENT TO VOLTAGE TRANSFER FUNCTION OF HYBRID ACTIVE TWO- PORTS WITH CONVERSION
ELEKTRYKA 0 Zeszyt (9) Rok LX Andrzej KUKIEŁKA Politechnika Śląska w Gliwicach DUAL SIMILARITY OF VOLTAGE TO CURRENT AND CURRENT TO VOLTAGE TRANSFER FUNCTION OF HYBRID ACTIVE TWO- PORTS WITH CONVERSION
User s manual for icarwash
User s manual for icarwash BKF Myjnie Bezdotykowe Sp. z o.o. Skarbimierzyce 22 72 002 Dołuje (k. Szczecina) Skarbimierzyce, 2014.11.14 Version v0.2 Table of Contents Table of Contents Settings Login Navigation
Export Markets Enterprise Florida Inc.
Export Markets Enterprise Florida Inc. IV webinarium 5.03.2015 Współfinansowany ze środków Europejskiego Funduszu Rozwoju Regionalnego w ramach Programu Operacyjnego Współpracy Transgranicznej Republika
Zarządzanie sieciami telekomunikacyjnymi
SNMP Protocol The Simple Network Management Protocol (SNMP) is an application layer protocol that facilitates the exchange of management information between network devices. It is part of the Transmission
Linear Classification and Logistic Regression. Pascal Fua IC-CVLab
Linear Classification and Logistic Regression Pascal Fua IC-CVLab 1 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
Dolny Slask 1: , mapa turystycznosamochodowa: Plan Wroclawia (Polish Edition)
Dolny Slask 1:300 000, mapa turystycznosamochodowa: Plan Wroclawia (Polish Edition) Click here if your download doesn"t start automatically Dolny Slask 1:300 000, mapa turystyczno-samochodowa: Plan Wroclawia
ENGLISH GRAMMAR. reported speech stylistic inversion both, either, neither have & have got
ENGLISH GRAMMAR reported speech stylistic inversion both, either, neither have & have got REPORTED SPEECH, mowa zależna stosujemy, kiedy przekazujemy czyjąś wypowiedź, nie cytując jej wprost. KONSTRUKCJA:
Wojewodztwo Koszalinskie: Obiekty i walory krajoznawcze (Inwentaryzacja krajoznawcza Polski) (Polish Edition)
Wojewodztwo Koszalinskie: Obiekty i walory krajoznawcze (Inwentaryzacja krajoznawcza Polski) (Polish Edition) Robert Respondowski Click here if your download doesn"t start automatically Wojewodztwo Koszalinskie:
XML. 6.6 XPath. XPath is a syntax used for selecting parts of an XML document
6 XML 6.6 XPath What is XPath? XPath is a syntax used for selecting parts of an XML document The way XPath describes paths to elements is similar to the way an operating system describes paths to files
Wprowadzenie do programu RapidMiner, część 5 Michał Bereta
Wprowadzenie do programu RapidMiner, część 5 Michał Bereta www.michalbereta.pl 1. Przekształcenia atrybutów (ang. attribute reduction / transformation, feature extraction). Zamiast wybierad częśd atrybutów
Zmiany techniczne wprowadzone w wersji Comarch ERP Altum
Zmiany techniczne wprowadzone w wersji 2018.2 Copyright 2016 COMARCH SA Wszelkie prawa zastrzeżone Nieautoryzowane rozpowszechnianie całości lub fragmentu niniejszej publikacji w jakiejkolwiek postaci
INSTRUKCJE JAK AKTYWOWAĆ SWOJE KONTO PAYLUTION
INSTRUKCJE JAK AKTYWOWAĆ SWOJE KONTO PAYLUTION Kiedy otrzymana przez Ciebie z Jeunesse, karta płatnicza została zarejestrowana i aktywowana w Joffice, możesz przejść do aktywacji swojego konta płatniczego
Zasady rejestracji i instrukcja zarządzania kontem użytkownika portalu
Zasady rejestracji i instrukcja zarządzania kontem użytkownika portalu Rejestracja na Portalu Online Job Application jest całkowicie bezpłatna i składa się z 3 kroków: Krok 1 - Wypełnij poprawnie formularz
Testy jednostkowe - zastosowanie oprogramowania JUNIT 4.0 Zofia Kruczkiewicz
Testy jednostkowe - zastosowanie oprogramowania JUNIT 4.0 http://www.junit.org/ Zofia Kruczkiewicz 1. Aby utworzyć test dla jednej klasy, należy kliknąć prawym przyciskiem myszy w oknie Projects na wybraną
Dolny Slask 1: , mapa turystycznosamochodowa: Plan Wroclawia (Polish Edition)
Dolny Slask 1:300 000, mapa turystycznosamochodowa: Plan Wroclawia (Polish Edition) Click here if your download doesn"t start automatically Dolny Slask 1:300 000, mapa turystyczno-samochodowa: Plan Wroclawia
PSB dla masazystow. Praca Zbiorowa. Click here if your download doesn"t start automatically
PSB dla masazystow Praca Zbiorowa Click here if your download doesn"t start automatically PSB dla masazystow Praca Zbiorowa PSB dla masazystow Praca Zbiorowa Podrecznik wydany w formie kieszonkowego przewodnika,
PLSH1 (JUN14PLSH101) General Certificate of Education Advanced Subsidiary Examination June 2014. Reading and Writing TOTAL
Centre Number Surname Candidate Number For Examiner s Use Other Names Candidate Signature Examiner s Initials Section Mark Polish Unit 1 Reading and Writing General Certificate of Education Advanced Subsidiary
www.irs.gov/form990. If "Yes," complete Schedule A Schedule B, Schedule of Contributors If "Yes," complete Schedule C, Part I If "Yes," complete Schedule C, Part II If "Yes," complete Schedule C, Part
Po powtórce zaczynamy naukę kolejnych 10-15 nowych słów i wyrażeń, po czym zostawiamy je w przegródce numer 1. Systematyczność
Fiszki, metoda powtórkowa. System pięciu przegródek Pierwszego dnia nauki możemy zacząć od przyswojenia 10-15 nowych słówek. Wkładamy je wtedy do przegródki numer 1. Kolejnego dnia zaczynamy od powtórki
aforementioned device she also has to estimate the time when the patients need the infusion to be replaced and/or disconnected. Meanwhile, however, she must cope with many other tasks. If the department
Relaxation of the Cosmological Constant
Relaxation of the Cosmological Constant with Peter Graham and David E. Kaplan The Born Again Universe + Work in preparation + Work in progress aaab7nicdvbns8nafhypx7v+vt16wsycp5kioseifw8ekthwaepzbf7apztn2n0ipfrhepggifd/jzf/jzs2brudwbhm5rhvtzakro3rfjqlpewv1bxyemvjc2t7p7q719zjphi2wcisdr9qjyjlbblubn6ncmkccoweo6vc7zyg0jyrd2acoh/tgeqrz9ryqdo7sdgq9qs1t37m5ibu3v2qqvekpqyfmv3qry9mwbajnexqrbuemxp/qpxhtoc00ss0ppsn6ac7lkoao/yns3wn5mgqiykszz80zkz+n5jqwotxhnhktm1q//zy8s+vm5nowp9wmwygjzt/fgwcmitkt5oqk2rgjc2hthg7k2fdqigztqgklwfxkfmfte/qnuw3p7xgzvfhgq7gei7bg3nowdu0oqumrvaiz/dipm6t8+q8zamlp5jzhx9w3r8agjmpzw==
KONSPEKT DO LEKCJI MATEMATYKI W KLASIE 3 POLO/ A LAYER FOR CLASS 3 POLO MATHEMATICS
KONSPEKT DO LEKCJI MATEMATYKI W KLASIE 3 POLO/ A LAYER FOR CLASS 3 POLO MATHEMATICS Temat: Funkcja logarytmiczna (i wykładnicza)/ Logarithmic (and exponential) function Typ lekcji: Lekcja ćwiczeniowa/training
Arrays -II. Arrays. Outline ECE Cal Poly Pomona Electrical & Computer Engineering. Introduction
ECE 114-9 Arrays -II Dr. Z. Aliyazicioglu Electrical & Computer Engineering Electrical & Computer Engineering 1 Outline Introduction Arrays Declaring and Allocation Arrays Examples Using Arrays Passing
EGZAMIN MATURALNY Z JĘZYKA ANGIELSKIEGO
Miejsce na naklejkę z kodem szkoły dysleksja MJA-R1_1P-072 EGZAMIN MATURALNY Z JĘZYKA ANGIELSKIEGO MAJ ROK 2007 Instrukcja dla zdającego POZIOM ROZSZERZONY CZĘŚĆ I Czas pracy 120 minut 1. Sprawdź, czy
Test sprawdzający znajomość języka angielskiego
Test sprawdzający znajomość języka angielskiego Imię i Nazwisko Kandydata/Kandydatki Proszę wstawić X w pole zgodnie z prawdą: Brak znajomości języka angielskiego Znam j. angielski (Proszę wypełnić poniższy
Domy inaczej pomyślane A different type of housing CEZARY SANKOWSKI
Domy inaczej pomyślane A different type of housing CEZARY SANKOWSKI O tym, dlaczego warto budować pasywnie, komu budownictwo pasywne się opłaca, a kto się go boi, z architektem, Cezarym Sankowskim, rozmawia
DO MONTAŻU POTRZEBNE SĄ DWIE OSOBY! INSTALLATION REQUIRES TWO PEOPLE!
1 HAPPY ANIMALS B09 INSTRUKCJA MONTAŻU ASSEMBLY INSTRUCTIONS Akcesoria / Fittings K1 M M1 ZM1 Z T G1 17 szt. / pcs 13 szt. / pcs B1 13 szt. / pcs W4 13 szt. / pcs W6 14 szt. / pcs U1 1 szt. / pcs U N1
Aktualizacja Oprogramowania Firmowego (Fleszowanie) Microprocessor Firmware Upgrade (Firmware downloading)
Aktualizacja Oprogramowania Firmowego (Fleszowanie) Microprocessor Firmware Upgrade (Firmware downloading) ROGER sp.j. Gościszewo 59 82-416 Gościszewo Poland tel. 055 2720132 fax 055 2720133 www.roger.pl
METHOD 2 -DIAGNOSTIC OUTSIDE
VW MOTOMETER BOSCH METHOD 1 - OBD 2 METHOD 2 -DIAGNOSTIC OUTSIDE AFTER OPERATION YOU MUST DISCONECT ACU OR REMOVE FUSE FOR RESTART ODOMETER PO ZROBIENIU LICZNIKA ZDJĄĆ KLEMĘ LUB WYJĄĆ 2 BEZPIECZNIKI OD
y = The Chain Rule Show all work. No calculator unless otherwise stated. If asked to Explain your answer, write in complete sentences.
The Chain Rule Show all work. No calculator unless otherwise stated. If asked to Eplain your answer, write in complete sentences. 1. Find the derivative of the functions y 7 (b) (a) ( ) y t 1 + t 1 (c)
General Certificate of Education Ordinary Level ADDITIONAL MATHEMATICS 4037/12
UNIVERSITY OF CAMBRIDGE INTERNATIONAL EXAMINATIONS General Certificate of Education Ordinary Level www.xtremepapers.com *6378719168* ADDITIONAL MATHEMATICS 4037/12 Paper 1 May/June 2013 2 hours Candidates
Leba, Rowy, Ustka, Slowinski Park Narodowy, plany miast, mapa turystyczna =: Tourist map = Touristenkarte (Polish Edition)
Leba, Rowy, Ustka, Slowinski Park Narodowy, plany miast, mapa turystyczna =: Tourist map = Touristenkarte (Polish Edition) FotKart s.c Click here if your download doesn"t start automatically Leba, Rowy,
Polska Szkoła Weekendowa, Arklow, Co. Wicklow KWESTIONRIUSZ OSOBOWY DZIECKA CHILD RECORD FORM
KWESTIONRIUSZ OSOBOWY DZIECKA CHILD RECORD FORM 1. Imię i nazwisko dziecka / Child's name... 2. Adres / Address... 3. Data urodzenia / Date of birth... 4. Imię i nazwisko matki /Mother's name... 5. Adres
OSTC GLOBAL TRADING CHALLENGE MANUAL
OSTC GLOBAL TRADING CHALLENGE MANUAL Wrzesień 2014 www.ostc.com/game Po zarejestrowaniu się w grze OSTC Global Trading Challenge, zaakceptowaniu oraz uzyskaniu dostępu to produktów, użytkownik gry będzie
Steeple #3: Gödel s Silver Blaze Theorem. Selmer Bringsjord Are Humans Rational? Dec RPI Troy NY USA
Steeple #3: Gödel s Silver Blaze Theorem Selmer Bringsjord Are Humans Rational? Dec 6 2018 RPI Troy NY USA Gödels Great Theorems (OUP) by Selmer Bringsjord Introduction ( The Wager ) Brief Preliminaries
Angielski Biznes Ciekawie
Angielski Biznes Ciekawie Conditional sentences (type 2) 1. Discuss these two types of mindsets. 2. Decide how each type would act. 3. How would you act? Czy nauka gramatyki języka angielskiego jest trudna?