backside ollie urban dictionary

': ['lL', '[{', ']}', '=+', '-_', 'sS'], '@': ['1! the following is a O(l_max * (n + m)) dynamic programming algorithmn # for a length-n password with m candidate matches. A A's AMD AMD's AOL AOL's AWS AWS's Aachen Aachen's Aaliyah Aaliyah's Aaron Aaron's Abbas Abbas's Abbasid Abbasid's Abbott Abbott's Abby Abby's Abdul Abdul's Abe Abe's Abel Abel's cache it.n min_guesses = 1n if match.token.length < password.lengthn min_guesses = if match.token.length 1n MIN_SUBMATCH_GUESSES_SINGLE_CHARn elsen MIN_SUBMATCH_GUESSES_MULTI_CHARn estimation_functions =n bruteforce: @bruteforce_guessesn dictionary: @dictionary_guessesn spatial: @spatial_guessesn repeat: @repeat_guessesn sequence: @sequence_guessesn regex: @regex_guessesn date: @date_guessesn guesses = estimation_functions[match.pattern].call this, matchn match.guesses = Math.max guesses, min_guessesn match.guesses_log10 = @log10 match.guessesn match.guessesnn bruteforce_guesses: (match) ->n guesses = Math.pow BRUTEFORCE_CARDINALITY, match.token.lengthn if guesses Number.POSITIVE_INFINITYn guesses = Number.MAX_VALUE;n # small detail: make bruteforce matches at minimum one guess bigger than smallest allowedn # submatch guesses, such that non-bruteforce submatches over the same [i..j] take precedence.n min_guesses = if match.token.length 1n MIN_SUBMATCH_GUESSES_SINGLE_CHAR + 1n elsen MIN_SUBMATCH_GUESSES_MULTI_CHAR + 1n Math.max guesses, min_guessesnn repeat_guesses: (match) ->n match.base_guesses * match.repeat_countnn sequence_guesses: (match) ->n first_chr = match.token.charAt(0)n # lower guesses for obvious starting pointsn if first_chr in ['a', 'A', 'z', 'Z', '0', '1', '9']n base_guesses = 4n elsen if first_chr.match /d/n base_guesses = 10 # digitsn elsen # could give a higher base for uppercase,n # assigning 26 to both upper and lower sequences is more conservative.n base_guesses = 26n if not match.ascendingn # need to try a descending sequence in addition to every ascending sequence ->n # 2x guessesn base_guesses *= 2n base_guesses * match.token.lengthnn MIN_YEAR_SPACE: 20n REFERENCE_YEAR: new Date().getFullYear()nn regex_guesses: (match) ->n char_class_bases =n alpha_lower: 26n alpha_upper: 26n alpha: 52n alphanumeric: 62n digits: 10n symbols: 33n if match.regex_name of char_class_basesn Math.pow(char_class_bases[match.regex_name], match.token.length)n else switch match.regex_namen when 'recent_year'n # conservative estimate of year space: num years from REFERENCE_YEAR.n # if year is close to REFERENCE_YEAR, estimate a year space of MIN_YEAR_SPACE.n year_space = Math.abs parseInt(match.regex_match[0]) - @REFERENCE_YEARn year_space = Math.max year_space, @MIN_YEAR_SPACEn year_spacenn date_guesses: (match) ->n # base guesses: (year distance from REFERENCE_YEAR) * num_days * num_yearsn year_space = Math.max(Math.abs(match.year - @REFERENCE_YEAR), @MIN_YEAR_SPACE)n guesses = year_space * 365n # add factor of 4 for separator selection (one of ~4 choices)n guesses *= 4 if match.separatorn guessesnn KEYBOARD_AVERAGE_DEGREE: calc_average_degree(adjacency_graphs.qwerty)n # slightly different for keypad/mac keypad, but close enoughn KEYPAD_AVERAGE_DEGREE: calc_average_degree(adjacency_graphs.keypad)nn KEYBOARD_STARTING_POSITIONS: (k for k,v of adjacency_graphs.qwerty).lengthn KEYPAD_STARTING_POSITIONS: (k for k,v of adjacency_graphs.keypad).lengthnn spatial_guesses: (match) ->n if match.graph in ['qwerty', 'dvorak']n s = @KEYBOARD_STARTING_POSITIONSn d = @KEYBOARD_AVERAGE_DEGREEn elsen s = @KEYPAD_STARTING_POSITIONSn d = @KEYPAD_AVERAGE_DEGREEn guesses = 0n L = match.token.lengthn t = match.turnsn # estimate the number of possible patterns w/ length L or less with t turns or less.n for i in [2..L]n possible_turns = Math.min(t, i - 1)n for j in [1..possible_turns]n guesses += @nCk(i - 1, j - 1) * s * Math.pow(d, j)n # add extra guesses for shifted keys. ', 'sS', 'nN'], 'M': ['bB', 'hH', 'tT', 'wW', null, null], 'N': ['tT', 'rR', 'lL', 'sS', 'vV', 'wW'], 'O': ['aA', ',<', '.>', 'eE', 'qQ', ';:'], 'P': ['.>', '4$', '5%', 'yY', 'uU', 'eE'], 'Q': [';:', 'oO', 'eE', 'jJ', null, null], 'R': ['cC', '9(', '0)', 'lL', 'nN', 'tT'], 'S': ['nN', 'lL', '/? or, if there's more uppercase than lower (for eg. ', null, null], 'a': [null, '', ',<', 'oO', ';:', null], 'b': ['xX', 'dD', 'hH', 'mM', null, null], 'c': ['gG', '8*', '9(', 'rR', 'tT', 'hH'], 'd': ['iI', 'fF', 'gG', 'hH', 'bB', 'xX'], 'e': ['oO', '.>', 'pP', 'uU', 'jJ', 'qQ'], 'f': ['yY', '6^', '7&', 'gG', 'dD', 'iI'], 'g': ['fF', '7&', '8*', 'cC', 'hH', 'dD'], 'h': ['dD', 'gG', 'cC', 'tT', 'mM', 'bB'], 'i': ['uU', 'yY', 'fF', 'dD', 'xX', 'kK'], 'j': ['qQ', 'eE', 'uU', 'kK', null, null], 'k': ['jJ', 'uU', 'iI', 'xX', null, null], 'l': ['rR', '0)', '[{', '/? For tutoring please call 856.777.0840 I am a recently retired registered nurse who helps nursing students pass their NCLEX. WORDS.TXT - Free ebook download as Text File (.txt), PDF File (.pdf) or read book online for free. Her finder du nyheder og baggrund om DR, job- og medvirkende-opslag, serviceoplysninger, fakta om DR mv. Expatica is the international community’s online home away from home. ', '|']n l: ['1', '|', '7']n o: ['0']n s: ['$', '5']n t: ['+', '7']n x: ['%']n z: ['2']nnREGEXEN =n recent_year: /19dd|200d|201d/gnnDATE_MAX_YEAR = 2050nDATE_MIN_YEAR = 1000nDATE_SPLITS =n 4:[ # for length-4 strings, eg 1191 or 9111, two ways to split:n [1, 2] # 1 1 91 (2nd split starts at index 1, 3rd at index 2)n [2, 3] # 91 1 1n ]n 5:[n [1, 3] # 1 11 91n [2, 3] # 11 1 91n ]n 6:[n [1, 2] # 1 1 1991n [2, 4] # 11 11 91n [4, 5] # 1991 1 1n ]n 7:[n [1, 3] # 1 11 1991n [2, 3] # 11 1 1991n [4, 5] # 1991 1 11n [4, 6] # 1991 11 1n ]n 8:[n [2, 4] # 11 11 1991n [4, 6] # 1991 11 11n ]nnmatching =n empty: (obj) -> (k for k of obj).length 0n extend: (lst, lst2) -> lst.push.apply lst, lst2n translate: (string, chr_map) -> (chr_map[chr] or chr for chr in string.split(')).join(')n mod: (n, m) -> ((n % m) + m) % m # mod impl that works for negative numbersn sorted: (matches) ->n # sort on i primary, j secondaryn matches.sort (m1, m2) ->n (m1.i - m2.i) or (m1.j - m2.j)nn # ------------------------------------------------------------------------------n # omnimatch -- combine everything ----------------------------------------------n # ------------------------------------------------------------------------------nn omnimatch: (password) ->n matches = []n matchers = [n @dictionary_matchn @reverse_dictionary_matchn @l33t_matchn @spatial_matchn @repeat_matchn @sequence_matchn @regex_matchn @date_matchn ]n for matcher in matchersn @extend matches, matcher.call(this, password)n @sorted matchesnn #-------------------------------------------------------------------------------n # dictionary match (common passwords, english, last names, etc) ----------------n #-------------------------------------------------------------------------------nn dictionary_match: (password, _ranked_dictionaries = RANKED_DICTIONARIES) ->n # _ranked_dictionaries variable is for unit testing purposesn matches = []n len = password.lengthn password_lower = password.toLowerCase()n for dictionary_name, ranked_dict of _ranked_dictionariesn for i in [0...len]n for j in [i...len]n if password_lower[i..j] of ranked_dictn word = password_lower[i..j]n rank = ranked_dict[word]n matches.pushn pattern: 'dictionary'n i: in j: jn token: password[i..j]n matched_word: wordn rank: rankn dictionary_name: dictionary_namen reversed: falsen l33t: falsen @sorted matchesnn reverse_dictionary_match: (password, _ranked_dictionaries = RANKED_DICTIONARIES) ->n reversed_password = password.split(').reverse().join(')n matches = @dictionary_match reversed_password, _ranked_dictionariesn for match in matchesn match.token = match.token.split(').reverse().join(') # reverse backn match.reversed = truen # map coordinates back to original stringn [match.i, match.j] = [n password.length - 1 - match.jn password.length - 1 - match.in ]n @sorted matchesnn set_user_input_dictionary: (ordered_list) ->n RANKED_DICTIONARIES['user_inputs'] = build_ranked_dict ordered_list.slice()nn #-------------------------------------------------------------------------------n # dictionary match with common l33t substitutions ------------------------------n #-------------------------------------------------------------------------------nn # makes a pruned copy of l33t_table that only includes password's possible substitutionsn relevant_l33t_subtable: (password, table) ->n password_chars = {}n for chr in password.split(')n password_chars[chr] = truen subtable = {}n for letter, subs of tablen relevant_subs = (sub for sub in subs when sub of password_chars)n if relevant_subs.length > 0n subtable[letter] = relevant_subsn subtablenn # returns the list of possible 1337 replacement dictionaries for a given passwordn enumerate_l33t_subs: (table) ->n keys = (k for k of table)n subs = [[]]nn dedup = (subs) ->n deduped = []n members = {}n for sub in subsn assoc = ([k,v] for k,v in sub)n assoc.sort()n label = (k+','+v for k,v in assoc).join('-')n unless label of membersn members[label] = truen deduped.push subn dedupednn helper = (keys) ->n return if not keys.lengthn first_key = keys[0]n rest_keys = keys[1..]n next_subs = []n for l33t_chr in table[first_key]n for sub in subsn dup_l33t_index = -1n for i in [0...sub.length]n if sub[i][0] l33t_chrn dup_l33t_index = in breakn if dup_l33t_index -1n sub_extension = sub.concat [[l33t_chr, first_key]]n next_subs.push sub_extensionn elsen sub_alternative = sub.slice(0)n sub_alternative.splice(dup_l33t_index, 1)n sub_alternative.push [l33t_chr, first_key]n next_subs.push subn next_subs.push sub_alternativen subs = dedup next_subsn helper(rest_keys)nn helper(keys)n sub_dicts = [] # convert from assoc lists to dictsn for sub in subsn sub_dict = {}n for [l33t_chr, chr] in subn sub_dict[l33t_chr] = chrn sub_dicts.push sub_dictn sub_dictsnn l33t_match: (password, _ranked_dictionaries = RANKED_DICTIONARIES, _l33t_table = L33T_TABLE) ->n matches = []n for sub in @enumerate_l33t_subs @relevant_l33t_subtable(password, _l33t_table)n break if @empty sub # corner case: password has no relevant subs.n subbed_password = @translate password, subn for match in @dictionary_match(subbed_password, _ranked_dictionaries)n token = password[match.i..match.j]n if token.toLowerCase() match.matched_wordn continue # only return the matches that contain an actual substitutionn match_sub = {} # subset of mappings in sub that are in use for this matchn for subbed_chr, chr of sub when token.indexOf(subbed_chr) != -1n match_sub[subbed_chr] = chrn match.l33t = truen match.token = tokenn match.sub = match_subn match.sub_display = ('#{k} -> #{v}' for k,v of match_sub).join(', ')n matches.push matchn @sorted matches.filter (match) ->n # filter single-character l33t matches to reduce noise.n # otherwise '1' matches 'i', '4' matches 'a', both very common English wordsn # with low dictionary rank.n match.token.length > 1nn # ------------------------------------------------------------------------------n # spatial match (qwerty/dvorak/keypad) -----------------------------------------n # ------------------------------------------------------------------------------nn spatial_match: (password, _graphs = GRAPHS) ->n matches = []n for graph_name, graph of _graphsn @extend matches, @spatial_match_helper(password, graph, graph_name)n @sorted matchesnn SHIFTED_RX: /[~!@#$%^&*()_+QWERTYUIOP{}|ASDFGHJKL:'ZXCVBNM<>? In practice it rarely exceeds 5 and then # search terminates rapidly.n #n # the optimal 'minimum guesses' sequence is here defined to be the sequence thatn # minimizes the following function:n #n # g = l! ', '=+', null, null, 'zZ'], '`': [null, null, null, '1! Click here to download american-english.txt. '], '#': ['2@', null, null, '4$', 'eE', 'wW'], '$': ['3#', null, null, '5%', 'rR', 'eE'], '%': ['4$', null, null, '6^', 'tT', 'rR'], '&': ['6^', null, null, '8*', 'uU', 'yY'], '': [';:', '[{', ']}', null, null, '/? List of MAC When the "Execute p1" button is clicked the javascript function p1 is executed. ', '0', null], '3': ['2', '5', '6', '+', null, null, '. )1+/gn lazy_anchored = /^(.+? (% instead of 5, A instead of a. ', '2@', ',<', 'aA', null], '#': ['2@', null, null, '4$', '.>', ',<'], '$': ['3#', null, null, '5%', 'pP', '.>'], '%': ['4$', null, null, '6^', 'yY', 'pP'], '&': ['6^', null, null, '8*', 'gG', 'fF'], '': [null, '1! We have 171 full length hd movies with BBW HD Porn 1080p in our database available for free streaming. ', '-_', 'zZ', 'vV'], 'T': ['hH', 'cC', 'rR', 'nN', 'wW', 'mM'], 'U': ['eE', 'pP', 'yY', 'iI', 'kK', 'jJ'], 'V': ['wW', 'nN', 'sS', 'zZ', null, null], 'W': ['mM', 'tT', 'nN', 'vV', null, null], 'X': ['kK', 'iI', 'dD', 'bB', null, null], 'Y': ['pP', '5%', '6^', 'fF', 'iI', 'uU'], 'Z': ['vV', 'sS', '-_', null, null, null], '[': ['0)', null, null, ']}', '/? ', null, null]}n dvorak: {'! ', null, null, '3#', 'wW', 'qQ'], 'A': [null, 'qQ', 'wW', 'sS', 'zZ', null], 'B': ['vV', 'gG', 'hH', 'nN', null, null], 'C': ['xX', 'dD', 'fF', 'vV', null, null], 'D': ['sS', 'eE', 'rR', 'fF', 'cC', 'xX'], 'E': ['wW', '3#', '4$', 'rR', 'dD', 'sS'], 'F': ['dD', 'rR', 'tT', 'gG', 'vV', 'cC'], 'G': ['fF', 'tT', 'yY', 'hH', 'bB', 'vV'], 'H': ['gG', 'yY', 'uU', 'jJ', 'nN', 'bB'], 'I': ['uU', '8*', '9(', 'oO', 'kK', 'jJ'], 'J': ['hH', 'uU', 'iI', 'kK', 'mM', 'nN'], 'K': ['jJ', 'iI', 'oO', 'lL', ',<', 'mM'], 'L': ['kK', 'oO', 'pP', ';:', '.>', ',<'], 'M': ['nN', 'jJ', 'kK', ',<', null, null], 'N': ['bB', 'hH', 'jJ', 'mM', null, null], 'O': ['iI', '9(', '0)', 'pP', 'lL', 'kK'], 'P': ['oO', '0)', '-_', '[{', ';:', 'lL'], 'Q': [null, '1! ', ']}', null, '|', null, '-_'], '>': [',<', '3#', '4$', 'pP', 'eE', 'oO'], '? ', '2@', 'wW', 'aA', null], 'R': ['eE', '4$', '5%', 'tT', 'fF', 'dD'], 'S': ['aA', 'wW', 'eE', 'dD', 'xX', 'zZ'], 'T': ['rR', '5%', '6^', 'yY', 'gG', 'fF'], 'U': ['yY', '7&', '8*', 'iI', 'jJ', 'hH'], 'V': ['cC', 'fF', 'gG', 'bB', null, null], 'W': ['qQ', '2@', '3#', 'eE', 'sS', 'aA'], 'X': ['zZ', 'sS', 'dD', 'cC', null, null], 'Y': ['tT', '6^', '7&', 'uU', 'hH', 'gG'], 'Z': [null, 'aA', 'sS', 'xX', null, null], '[': ['pP', '-_', '=+', ']}', '', ';:'], ': [']}', null, null, null, null, null], ']': ['[{', '=+', null, '|', null, ''], '^': ['5%', null, null, '7&', 'yY', 'tT'], '_': ['0)', null, null, '=+', '[{', 'pP'], '`': [null, null, null, '1! ', null, null, '3#', 'wW', 'qQ'], '3': ['2@', null, null, '4$', 'eE', 'wW'], '4': ['3#', null, null, '5%', 'rR', 'eE'], '5': ['4$', null, null, '6^', 'tT', 'rR'], '6': ['5%', null, null, '7&', 'yY', 'tT'], '7': ['6^', null, null, '8*', 'uU', 'yY'], '8': ['7&', null, null, '9(', 'iI', 'uU'], '9': ['8*', null, null, '0)', 'oO', 'iI'], ':': ['lL', 'pP', '[{', '', '/? ', 'lL'], ': ['=+', null, null, null, null, null], ']': ['[{', null, null, null, '=+', '/? ', null, null, null], '1': [null, null, '4', '5', '2', '0', null, null], '2': ['1', '4', '5', '6', '3', '. DR3 viser bagsiden af influencer-medaljen i den nye, Kaptajn Jespersen forsøgte tidligt at få danskerne til at røre sig, Johannes Langkilde var på vej til et liv som musiker, Nye programmer på P2 skal åbne den klassiske musik for nye lyttere, Vi bruger stadig syv timer på medier hver dag – men vores vaner ændrer sig under overfladen, ’Man kan godt gøre folk klogere og samtidig underholde dem’, Vi streamer gerne de samme serier flere gange, Niklas glemmer aldrig ’Ikonet ingen husker’, Flot prishøst til DR-programmer og -medarbejdere i et 2020 præget af corona, Ny DR-serie ser på fordomme og tabuer hos unge piger, DR søger danskere, der bor i de nordiske lande, Send din bølge-video til håndbold-VM 2021, DR2 søger familier, der har lyst til at deltage i et, 'Det store Ramasjang Mysterie' søger børn i alderen 7-11 år, DR2-program har gjort videomøder til tv-format, Johannes Langkilde og Katrine Muff er ny værtsduo i, Spot: Opsang, dåselyd og nye kanaler: Medieåret 2020 i den korte udgave, fra sektionen "DR i 2020", Vi tager ansvar for indholdet og er tilmeldt Pressenævnet. if so, skip it and return.n for competing_l, competing_g of optimal.g[k]n continue if competing_l > ln return if competing_g <= gn # this sequence might be part of the final optimal sequence.n optimal.g[k][l] = gn optimal.m[k][l] = mn optimal.pi[k][l] = pinn # helper: evaluate bruteforce matches ending at k.n bruteforce_update = (k) =>n # see if a single bruteforce match spanning the k-prefix is optimal.n m = make_bruteforce_match(0, k)n update(m, 1)n for i in [1..k]n # generate k bruteforce matches, spanning from (i=1, j=k) up to (i=k, j=k).n # see if adding these new matches to any of the sequences in optimal[i-1]n # leads to new bests.n m = make_bruteforce_match(i, k)n for l, last_m of optimal.m[i-1]n l = parseInt(l)n # corner: an optimal sequence will never have two adjacent bruteforce matches.n # it is strictly better to have a single bruteforce match spanning the same region:n # same contribution to the guess product with a lower length.n # --> safe to skip those cases.n continue if last_m.pattern 'bruteforce'n # try adding m to this length-l sequence.n update(m, l + 1)nn # helper: make bruteforce match objects spanning i to j, inclusive.n make_bruteforce_match = (i, j) =>n pattern: 'bruteforce'n token: password[i..j]n i: in j: jnn # helper: step backwards through optimal.m starting at the end,n # constructing the final optimal match sequence.n unwind = (n) =>n optimal_match_sequence = []n k = n - 1n # find the final best sequence length and scoren l = undefinedn g = Infinityn for candidate_l, candidate_g of optimal.g[k]n if candidate_g < gn l = candidate_ln g = candidate_gnn while k >= 0n m = optimal.m[k][l]n optimal_match_sequence.unshift mn k = m.i - 1n l--n optimal_match_sequencenn for k in [0...n]n for m in matches_by_j[k]n if m.i > 0n for l of optimal.m[m.i - 1]n l = parseInt(l)n update(m, l + 1)n elsen update(m, 1)n bruteforce_update(k)n optimal_match_sequence = unwind(n)n optimal_l = optimal_match_sequence.lengthnn # corner: empty passwordn if password.length 0n guesses = 1n elsen guesses = optimal.g[n - 1][optimal_l]nn # final result objectn password: passwordn guesses: guessesn guesses_log10: @log10 guessesn sequence: optimal_match_sequencenn # ------------------------------------------------------------------------------n # guess estimation -- one function per match pattern ---------------------------n # ------------------------------------------------------------------------------nn estimate_guesses: (match, password) ->n return match.guesses if match.guesses? Watch BBW HD Porn 1080p HD porn videos for free on Eporner.com. ': ['0', '2', '3', null, null, null, null, null], '/': [null, null, null, null, '*', '9', '8', '7'], '0': [null, '1', '2', '3', '. ', '.>'], '<': ['mM', 'kK', 'lL', '.>', null, null], '=': ['-_', null, null, null, ']}', '[{'], '>': [',<', 'lL', ';:', '/? ', '-_', 'zZ', 'vV'], 't': ['hH', 'cC', 'rR', 'nN', 'wW', 'mM'], 'u': ['eE', 'pP', 'yY', 'iI', 'kK', 'jJ'], 'v': ['wW', 'nN', 'sS', 'zZ', null, null], 'w': ['mM', 'tT', 'nN', 'vV', null, null], 'x': ['kK', 'iI', 'dD', 'bB', null, null], 'y': ['pP', '5%', '6^', 'fF', 'iI', 'uU'], 'z': ['vV', 'sS', '-_', null, null, null], '{': ['0)', null, null, ']}', '/? and display_num != 1n display_strnnmodule.exports = time_estimatesn'. Write something about yourself. Create your own unique website with customizable templates. ', 'sS', 'nN'], 'm': ['bB', 'hH', 'tT', 'wW', null, null], 'n': ['tT', 'rR', 'lL', 'sS', 'vV', 'wW'], 'o': ['aA', ',<', '.>', 'eE', 'qQ', ';:'], 'p': ['.>', '4$', '5%', 'yY', 'uU', 'eE'], 'q': [';:', 'oO', 'eE', 'jJ', null, null], 'r': ['cC', '9(', '0)', 'lL', 'nN', 'tT'], 's': ['nN', 'lL', '/? Elite MILF Rayveness stopped by to see Swiney & give up both of her holes to. assuming at minimum D guesses per pattern type,n # D^(l-1) approximates Sum(D^i for i in [1..l-1]n #n # ------------------------------------------------------------------------------nn most_guessable_match_sequence: (password, matches, _exclude_additive=false) ->nn n = password.lengthnn # partition matches into sublists according to ending index jn matches_by_j = ([] for _ in [0...n])n for m in matchesn matches_by_j[m.j].push mn # small detail: for deterministic output, sort each sublist by i.n for lst in matches_by_jn lst.sort (m1, m2) -> m1.i - m2.inn optimal =n # optimal.m[k][l] holds final match in the best length-l match sequence covering then # password prefix up to k, inclusive.n # if there is no length-l sequence that scores better (fewer guesses) thann # a shorter match sequence spanning the same prefix, optimal.m[k][l] is undefined.n m: ({} for _ in [0...n])nn # same structure as optimal.m -- holds the product term Prod(m.guesses for m in sequence).n # optimal.pi allows for fast (non-looping) updates to the minimization function.n pi: ({} for _ in [0...n])nn # same structure as optimal.m -- holds the overall metric.n g: ({} for _ in [0...n])nn # helper: considers whether a length-l sequence ending at match m is better (fewer guesses)n # than previously encountered sequences, updating state if so.n update = (m, l) =>n k = m.jn pi = @estimate_guesses m, passwordn if l > 1n # we're considering a length-l sequence ending with match m:n # obtain the product term in the minimization function by multiplying m's guessesn # by the product of the length-(l-1) sequence ending just before m, at m.i - 1.n pi *= optimal.pi[m.i - 1][l - 1]n # calculate the minimization funcn g = @factorial(l) * pin unless _exclude_additiven g += Math.pow(MIN_GUESSES_BEFORE_GROWING_SEQUENCE, l - 1)n # update state if new best.n # first see if any competing sequences covering this prefix, with l or fewer matches,n # fare better than this sequence. 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