Diagnosis in Fast-TAD (overlaid on BISTer-1) Ses Ses S1 S1 PLB PLB A A B B C DC TPG ORA TPG ORA CUT TPG b1,b2 CUT TPG b1,b2 CUT CUT c1,c2 c1,c2 b1,b2 D A S3 S3 S4 S4 CUT CUT CUT CUT d1,d2 d1,d2 a1,a2 a1,a2 a1,a2 CUT b1,b2 ORA S1 Theorem: Fast-TAD using BISTer-1 is 1-diagnosable • A f-faulty PLB Q config. as a TPG will have a GS of √ while Q configured as a CUT & performing its oper. functions will have GS of X. In all other cases GS is either a √ or a X a1,a2 CUT • In some cases, faults in A and C ( or B and D) ORA a1,a2 TPG ORA b1,b2 CUT CUT CUT CUT ORA TPG TPG ORA b1,b2 c1,c2 c1,c2 d1,d2 c1,c2 f-faulty PLB S2 S2 • Each PLB is tested in its two operational fn. d1,d2 CUT S3CUTS4 S2 may not be distinguishable – a 2nd test reqd. • Require 10.t1 time versus 16.t1 if both CUTs in a session are config. both their oper fns. Ses. PLB S1 S2 (C/A) (B/D) CUT b1,b2 ORA c1,c2 d1,d2 TPG √√ Xd1,d2 /√ X/√ a1,a2 X X/√ X/√ X A TPG B X √ X/√ X/√ B C X/√ X/√ X X √ √ X/√ X/√ CUT CUT c1,c2 b1,b2 C ORA D X/√ X/√ X √ CUT c1,c2 D ORA TPG Faulty PLB S1 (C/A) A √ B C D S2 (B/D) X X √
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Very Simple Weighted SP1 and SP2 K-plex Search on G6 Weighting: 0,1path nbrs of x times 3; 2path nbrs of x times 2; Until all degrees are weighted, then back to actual subgraph degrees H={123456789abc deg999923634438 H={123456789abc deg 999923634438 H={123456789abc deg 99962333886c H={123456789abc deg 996946334434 UNWEIGHTED Degrees H={123456789abc deg 333323334434 SP1 1 2 3 4 5 6 7 8 9 a b c 1 0 1 1 1 2 1 0 1 1 3 1 1 0 0 4 1 1 0 0 5 0 0 0 0 6 0 0 0 0 7 0 0 0 1 8 0 0 0 0 9 0 0 0 0 a 0 0 0 0 b 0 0 0 0 c 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 1 0 1 0 1 1 1 1 0 0 0 1 0 0 0 0 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 1 1 1 1 0 1 1 1 1 0 1 1 1 1 0 3 3 3 3 2 3 3 3 4 4 3 4 H=15 H=7 kplex k8 x=1 after cutting x=2 H={123456789abc deg999923634438 2,3,4 H={123456789abc deg999923634438 2,3,4 x=3 H={123456789abc deg 99962333886c H=6 H=4 2plex x=3, after cut 2368 x=1 x=4 H={123456789abc deg 996946334434 H=15 H=7 kplex k8 x=2 after cutting H=3 x=4 H={123456789abc k1 deg999923634438 H={123456789abc k1 deg999923634438 H={123456789abc deg 222623338861 H=6 H=5 kplex x=1, after cut 23468 H=6 H=5 kplex x=2, after cut 23468 H=3 H=3 0plex x=3 after cut 1 (actual subgraph degrees) H=3 0plex after cut 2346 H={123456789abc deg 333669964434 H=10 H=5 5plex x=5 after cut 34 H={123456789abc deg 333669964434 x=5 H={123456789abc deg 333669998834 x=6 H={123456789abc deg 333669998834 x=6 after cut 34 H={123456789abc deg 33312333223 H=3 H=2 1plex x=6 after cut 12 SG degs 211 H={123456789abc deg 333969934434 x=7 H={123456789abc deg 333969998834x=7 after cut 34 H={123456789abc deg 333122232234 H=3 H=3 0plex x=7 after cut 1 SG degs H={123456789abc deg 33334969cc68 x=8 H={123456789abc deg 33334969cc68 x=8 after cut 34 H={123456789abc H=3 H=3 0plex deg 333123314434x=5 after cut 1 from SG degs H={123456789abc deg 333342134433 SP2 1 2 3 4 1 0 0 0 0 2 0 0 0 0 3 0 0 0 1 4 0 0 1 0 5 0 0 0 1 6 0 0 0 1 7 1 1 0 0 8 0 0 0 0 9 0 0 1 0 a 0 0 1 0 b 0 0 1 0 c 1 1 0 0 H={123456789abc deg 33632639cc9c x=9 5 6 7 8 9 a b c 0 0 1 0 0 0 1 0 0 0 0 0 1 1 0 0 0 0 0 1 0 0 0 0 0 0 0 1 1 0 1 0 0 1 0 0 0 1 0 0 0 0 0 1 0 0 0 1 H={123456789abc deg 33632639cc9c x=a H={123456789abc deg 33632639cc9c H=10 H=8 H a kplex k 2 x=a after cut 2,3,6 0 0 0 1 0 0 0 1 1 1 1 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 H={123456789abc deg 33632336cc9c x=b H={123456789abc deg 33632639cc9c H=6 H=6 H a kplex k 0 x=b after cut 2,3,6 SP3 1 2 3 4 5 6 7 8 1 0 0 0 0 2 0 0 0 0 3 0 0 0 0 4 0 0 0 0 5 1 1 0 0 6 1 1 0 0 7 0 0 1 0 8 0 0 1 1 9 1 1 0 0 a 1 1 0 0 b 1 1 0 0 c 0 0 0 1 H={123456789abc deg 66932336ccpc x=c 1 1 0 0 1 1 0 0 0 0 1 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 1 0 1 0 0 1 0 0 0 1 0 0 9 a b c 1 1 1 0 1 1 1 0 0 0 0 0 0 0 0 1 1 1 0 0 0 0 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 SP4 1 2 3 4 1 0 0 0 0 2 0 0 0 0 3 0 0 0 0 4 0 0 0 0 5 0 0 1 0 6 0 0 1 0 7 0 0 0 0 8 1 1 0 0 9 0 0 0 1 a 0 0 0 1 b 0 0 0 1 c 0 0 0 0 5 6 7 8 0 0 0 1 0 0 0 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 1 0 1 0 9 a b c 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 0 0 0 1 1 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 H={123456789abc deg 33632639cc9c 2,3,6 H={123456789abc deg 66932336cc9c 2plex x=8 after cut12 SG degs H=10 H=8 H a kplex k 2 x=9 after Cutting H=6 H=6 H a kplex k 0 x=c after cut 2,3,6 By weighting the initial round we have gotten nearly perfect information for this example (G6). The weightings, 3 and 2, were arbitrarily chosen but worked here. In general, one should devise a formula to determine them. Also we could weight SP3 and etc. as well? If we have paid the price of constructing SPk k>1, this is a much simpler way to do it, as compared to the Clique Percolation method of Palla (next slide). G6 1 5 4 2 6 7 3 c 9 b 8 a
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Our BISTer-1 Architecture TPG A ORA B CUT TPG C CUT Sess  PLB  S1 ORA CUT D S2 S3 S4 S1 S2 S3 S4 Inference √ √ √ √ No faulty PLB X √ √ √ Fault not in PLB √ X √ √ Fault not in PLB √ √ X √ Fault not in PLB √ √ √ X Fault not in PLB X X √ √ Faulty C (CUT) √ X X √ Faulty D (CUT) √ √ X X Faulty A (CUT) X √ √ X Faulty B (CUT) X √ X √ Fault not in PLB √ X √ X Fault not in PLB A TPG ORA CUT CUT B CUT TPG ORA CUT X X X √ Faulty D √ X X X Faulty A C CUT CUT TPG ORA X X √ X Faulty C D ORA CUT CUT TPG X √ X X Faulty B X X X X Fault not in PLB
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BISTer-2 architecture B CUT A TPG C ORA F ORA 1 2 Y1 Y1 – output of the ORA comparing CUTs Y2 – output of the ORA comparing TPGs Theorem: BISTer-2 is 1-diagnosable Proof: Gross syndrome corresponding to Y1 for each faulty PLB is unique. E.g. Y1 is pass in section 2 only for faulty PLB A and no other PLB. Y2 E D CUT TPG OR1 => ORA 1 (Y1) OR2 => ORA 2 (Y2) S1 S2 S3 S4 S5 S6 A TPG OR2 TPG CUT OR1 CUT B CUT TPG OR2 TPG CUT OR1 C OR1 CUT TPG OR2 TPG CUT D CUT OR1 CUT TPG OR2 TPG E TPG CUT OR1 CUT TPG OR2 F OR2 TPG CUT OR1 CUT TPG Gross syndrome corresponding to Y1 Faulty PLB S1 S2 S3 S4 S5 S6 A X √ X X X X B X X √ X X X C X X X √ X X D X X X X √ X E X X X X X √ F √ X X X X X
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Our BISTer-1 Architecture Each PLB is a CUT in 2 unique sessn’s and a TPG in another unique session – this serves to uniquelyis identify the Theorem: BISTer-1 1-diagnosable faulty PLB which will have a X X √ in these sessions. Sess  PLB  S1 S2 S3 S4 S1 S2 S3 S4 Inference √ √ √ √ No faulty PLB X √ √ √ Fault not in PLB √ X √ √ Fault not in PLB √ √ X √ Fault not in PLB √ √ √ X Fault not in PLB X X √ √ Faulty C (CUT) √ X X √ Faulty D (CUT) √ √ X X Faulty A (CUT) X √ √ X Faulty B (CUT) X √ X √ Fault not in PLB √ X √ X Fault not in PLB A TPG ORA CUT CUT B CUT TPG ORA CUT X X X √ Faulty D √ X X X Faulty A C CUT CUT TPG ORA X X √ X Faulty C D ORA CUT CUT TPG X √ X X Faulty B X X X X Fault not in PLB
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Simple Barrier Synchronization lock(); if(count==0) release=FALSE; /* First resets release */ count++; /* Count arrivals */ unlock(); if(count==total) /* All arrived */ { count=0; /* Reset counter */ release = TRUE; /* Release processes */ } else /* Wait for more to come */ { while (!release); /* Wait for release */ } • Problem: deadlock possible if reused – Two processes: fast and slow – Slow arrives first, reads release, sees FALSE – Fast arrives, sets release to TRUE, goes on to execute other code, comes to barrier again, resets release to FALSE, starts spinning on wait for release – Slow now reads release again, sees FALSE again – Now both processors are stuck and will never leave
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BISTer-0 [M. Abramovici et. al., ITC ’99] S1 S2 S3 S4 Theorem: BISTer-0 is zero-diagnosable. A B C D TPG CUT ORA CUT Proof: The same pair of PLBs are configured as CUT TPG CUT ORA CUTs in two different sessions: PLBs A and C in S2 and S4 ORA CUT TPG CUT PLBs B and D in S1 and S3. CUT ORA CUT TPG When either PLB fails, the gross syndrome will be identical in these sessions. Faulty S1 S2 S3 S4 PLB E.g. if A fails as a CUT only, then its gross syndrome is identical to the gross syn. of √/ A √ X X C failing as a CUT only. Hence we cannot X distinguish between faulty PLBs A and C. C √/ X X √ X Thus has a complex adaptive diagnosis phase
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Changes in Prison Release Policies The major shift in parole release mechanisms over the past 25 years has been away from discretionary release and toward supervised mandatory release . Discretionary Release: In 1980, about 55% of all offenders were released from prison based on a discretionary decision by a state parole board. By 2005, only slightly more than 20 % were released from prison in this manner . Mandatory Release: During this same period, many state legislatures rewrote their parole release guidelines to create a new release mechanism, supervised mandatory release, which essentially eliminated the need for a discretionary parole board review. Once offenders completed their mandatory minimum period of incarceration, they were released from prison and placed under mandatory community supervision for a specified follow-up period. In 1980, approximately 18% of all prisoners were released in this manner, but by 2005, almost 40% of all inmates re-entered the community on supervised mandatory release.
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Three Releases Your project will be completed in three releases, with some additional follow-up afterwards. Release 1 Release 2 Release Follow-Up Release 3 3 Follow-Up •Initial Initial code code & & documentatio documentatio n n •Specification Specification ss required: required: week week of of 8/28 8/28 •Completed Completed release release due: due: week week of of 9/18 9/18 •More More thorough thorough code code & & documentation documentation •Complete Complete code code & & documentation documentation •Specifications Specifications required: required: week of of 9/18 9/18 •Specifications Specifications required: required: week week of of 10/16 10/16 •Completed Completed release release due: due: week week of of 10/16 10/16 •Completed Completed release release due: due: week week of of 11/13 11/13 3 •Peer Peer reviews: reviews: week week of of 11/27 11/27 •Faculty Faculty presentation: presentation: week week of of 12/4 12/4 •Post-mortem Post-mortem discussion: discussion: week week of of 12/11 12/11
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I. Balanced Communities • Community detection can be thought of graph clustering • Graph clustering: we cut the graph into several partitions and assume these partitions represent communities • Cut: partitioning (cut) of the graph into two (or more) sets (cutsets) – The size of the cut is the number of edges that are being cut • Minimum cut (min-cut) problem: find a graph partition such that the number of edges between the two sets is minimized Min-cut Min-cuts can be computed efficiently using the max-flow mincut theorem Min-cut often returns an imbalanced partition, with one set being a singleton 39
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BISTer-0 [M. Abramovici et. al., ITC ’99] A TPG CUT B D CUT A CUT D ORA ORA TPG CUT C B C (S2) (S1) D CUT A CUT D TPG CUT TPG B C (S3) ORA B CUT C (S4) A ORA TPG - Test Pattern Generator CUT - Cells Under Test ORA - Output Response Analyser • Exhaustive testing of CUTs • S1, S2, S3, S4 are four sessions of testing in a BISTer tile
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dist. 1 pair dist. 3 pair B CUT A TPG C OR1 Y1 F OR2 D CUT E TPG BISTer-2 Architecture (cont.) Theorem: BISTer-2 is 2-diagnosable under the assumptions: 1. No fault masking for all detailed syndromes 2. Faulty PLBs either uniformly all fail or all pass as TPG/ORA Proof: Y2 • For the case faulty PLBs fail as TPG/ORA also, possible gross syndromes (GS) are: Y1Y2 = X √ and XX • Class 1: faulty pairs corresponding to GS= X √. • 3 Class 1 pairs: (CUT,CUT)2, (CUT,OR1)1 and (OR1,CUT)1 (S1) dist. 2 Class 2 includes remaining faulty pairs (GS=XX). Class 1 pairs1• pair Class 1 BC pairs only pair Class from S1 B TPG Y1 OR1 C CUT D TPG OR1 Y1 2 1 1 A • ForS1: session , BC S1: BD GS = X X and CD GS = XS1, √ Class 1 includes CUT OR2 Y2 => Class 2 pairs => BC/CD/BD F TPG E OR2 CUT Y2 (S6) (S2) S2: GS = X √ => CD S6: GS = X √ => BC S2: GS = X X => BC/BD S6: GS = X X => BD In S1-S6 all the faulty pairs at dist. 1 & 2 will be in Class 1 and hence will be diag. CD only Class 1 pair from=> S1GS’s are distinct for all dist. 1 & 2 faulty pairs
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Correct Barrier Synchronization initially localSense = FALSE, release = FALSE localSense=!localSense; /* Toggle local sense */ lock(); count++; /* Count arrivals */ if(count==total){ /* All arrived */ count=0; /* Reset counter */ release=localSense; /* Release processes */ } unlock(); while(release!=localSense); /* Wait to be released */ • Release in first barrier acts as reset for second – When fast comes back it does not change release, it just waits for it to become FALSE – Slow eventually sees release is TRUE, stops waiting, does work, comes back, sets release to FALSE, and both go forward.
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Right Drug: Immediate vs. Timed Release • Timed release – Prolong absorption: Longer dosing intervals & less drug level fluctuation • • • • • • • Sustained-release (SR) Sustained-action (SA) Extended-release (ER, XR, XL) Timed-release (TR) Controlled-release (CR) Modified release (MR) Continuous-release (Contin)
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Definition of a Cut Let X be a set of vertices in a network that includes its source but does not include its sink, and let X, the complement of X, be the rest of the vertices including the sink. The cut induced by this partition of the vertices is the set of all the edges with a tail in X and a head in X. Capacity of a cut is defined as the sum of capacities of the edges that compose the cut.  We’ll denote a cut and its capacity by C(X,X) and c(X,X)  Note that if all the edges of a cut were deleted from the  network, there would be no directed path from source to sink Minimum cut is a cut of the smallest capacity in a given network A. Levitin Copyright © 2007 Pearson Addison-Wesley. All rights reserved. 10-35 “Introduction to the Design & Analysis of Algorithms,” 2nd ed., Ch. 10
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Protocol Size Error Detection Retransmission Media Access Asynchronous Transmission 1 Parity Continuous ARQ Full Duplex XMODEM 132 8-bit Checksum Stop-and-wait ARQ Controlled Access XMODEM-CRC 132 8-bit CRC Stop-and-wait ARQ Controlled Access XMODEM-1K 1028 8-bit CRC Stop-and-wait ARQ Controlled Access ZMODEM * 32-bit CRC Continuous ARQ Controlled Access KERMIT * 24-bit CRC Continuous ARQ Controlled Access SDLC * 16-bit CRC Continuous ARQ Controlled Access HDLC * 16-bit CRC Continuous ARQ Controlled Access Token Ring * 32-bit CRC Stop-and wait ARQ Controlled Access Ethernet * 32-bit CRC Stop-and wait ARQ Contention SLIP * None None Full Duplex PPP * 16-bit CRC Continuous ARQ Full Duplex File Transfer Protocols Synchronous Protocols * Varies depending on message length. Figure 4-8 Data Link Protocol Summary 37
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• PROVISIONAL RELEASE DATA: Provisional release data are the data that were reported to NCES in the original data collection and underwent all NCES data quality control procedures, including imputation. Institutions may have updated these data in the subsequent data collection year, however updates are not reflected in these data. • FINAL RELEASE DATA: Final release data include revisions to the provisional release data that have been made by institutions during the subsequent data collection year. The final release data can be used when the most up to date data are required; however, these data may not match tables from the First Look reports based on preliminary and provisional data. • PRELIMINARY RELEASE DATA: Preliminary release data have been edited but are subject to further NCES quality control procedures. Imputed data for nonresponding institutions are not included. These data are
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Use the 3-step pruning cut for larger branches  Use for branches that are too big to support with your hand  Reduces weight of branch before final cut.  1st cut- up from bottom, 6”12” out  2nd cut-down from top, outside 1st cut  3rd cut- final cut. Near trunk, leaving branch collar intact. 2 1 3
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Definitions • A cut (S, V - S) b is a partition of vertices into disjoint sets S and V - S • An edge crosses the 8 4 c 7 d 2 S a 11 i  7 V- S  8 cut h 1 9 e 14 4 6 10 g 2 f S  V- S (S, V - S) if one endpoint is in S and the other in V – S • A cut respects a set A of edges ⟺ no edge in A crosses the cut • An edge is a light edge crossing a cut ⟺ its weight is minimum over all edges crossing the cut – For a given cut, there can be several light edges crossing it CS 477/677 - Lecture 24 16
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Definition of a Cut X - a set of vertices in a network that includes its source but does not include its sink  Xc - the complement of X, including the sink   C(X,Xc) : the cut induced by this partition of the vertices - the set of all the edges with a tail in X and a head in Xc.  c(X,Xc) : Capacity of a cut - the sum of capacities of the edges that compose the cut.  Note that if all the edges of a cut were deleted from the network, there would be no directed path from source to sink  Minimum cut is a cut of the smallest capacity in a given network 22
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Very Simple Weighted SP1 k-plex Search on G7 Weighting: 0,1path nbrs of x times 1; 2path nbrs of x times 0; 1 2 3 H=1234567890123456789012345678901234 D g9a63444523125222223222533243446bg Cut 123: 1 2 3 H=1234567890123456789012345678901234 D 9685322452322522222322243323334367 Cut 23: 1 2 3 H=1234567890123456789012345678901234 D 6675322452322522222322223323334344 Cut 24: 1 2 3 H=1234567890123456789012345678901234 D 5454322422322422222322223323334344 SP1 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 H=561 H=77 kplx k484 20 kcore k77 21 22 23 24 H=120 H=38 kplx k82 25 kcore k38 26 27 28 29 H=55 H=26 kplx k24 30 kcore k26 31 32 33 H=15 H=12 kplx k3 34 kcore k12 Cut 2: 1 2 3 H=1234567890123456789012345678901234 H=10 H=10 kplx k0 D 4444322422322422222322223323334344 kcore k10 {1,2,3,4, 14} is a clique. {1,2,3,4,9,14} is a 3plex. 1 2 3 H=56789012356789012345678901234 D 232031200222021202533232435af Cut012:1 2 3 H=56789012356789012345678901234 D 20203120022202120253323233456 Cut03: 1 2 3 H=56789012356789012345678901234 D 20203120022202120223323233222 H=55 H=19 kplx k36 kcore k19 H=6 H=4 kplx k2 kcore k6 {24,32,33,34} is a 2plex 1 2 3 H=5678901235678901235678901 D 2330102000020000002111011 Cut01: 1 2 3 H=5678901235678901235678901 H=15 H=6 kplx k9 D 2330102000020000000111011 kcore k6 Cut0: 1 2 3 H=5678901235678901235678901 H=10 H=6 kplx k4 D 2330102000020000000111011 kcore k6 {5,6,7,11,17} is a 4plex 1 2 3 H=89023568901235678901 D 01000000000002111011 Cut0: 1 2 3 H=5678901235678901235678901 D 2330102000020000002111011 H=21 H=4 kplx k17 kcore k4 1 5 1 1 6 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 2 3 4 1 1 1 0 0 1 0 0 1 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 6 9 0 6 3 4 4 4 5 2 3 1 2 5 2 1 0 1 1 0 0 1 0 0 0 0 0 0 0 1 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 2 3 4 5 6 7 8 0 1 1 1 1 1 1 1 1 0 1 1 0 0 0 1 1 1 0 1 0 0 0 1 1 1 1 0 0 0 0 1 1 0 0 0 0 0 1 0 1 0 0 0 0 0 1 0 1 0 0 0 1 1 0 0 1 1 1 1 0 0 0 0 1 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 9 1 0 1 0 0 0 0 0 0 0 1 1 1 1 0 0 0 1 0 1 0 0 0 1 0 0 0 1 0 1 0 0 0 1 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 3 5 5 4 1 4 4 4 8 5 5 2 6 6 6 1 3 Cut0: 1 2 3 H=5678901235678901235678901 D 2330102000020000002111011 1 2 3 H=89023568901235678901 D 01000000000002010011 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 6 6 8 7 0 0 0 0 1 5 7 2 2 1 1 2 8 9 0 1 0 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 2 2 1 2 3 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 2 2 2 2 2 3 3 3 3 3 4 5 6 7 8 9 0 1 2 3 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 1 0 0 0 0 1 1 1 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 1 0 1 0 1 0 0 1 1 0 0 0 0 0 1 0 1 0 0 0 1 0 0 0 0 0 1 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 1 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 1 0 0 1 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 1 1 0 0 1 0 0 0 1 1 1 0 1 1 0 0 0 0 0 1 1 1 0 0 1 0 1 1 0 0 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 2 2 3 2 2 2 5 3 3 2 4 3 4 4 6 1 6 8 9 1 3 5 H=21 H=4 kplx k17 kcore k4 9 8 0 2 10 4 9 2 5 11 7 1 4 8 12 13 15 2 8 9 5 Cut 1 leaves 25 only. H=19 H=4 kplex k15 kcore k4 Cut0: 2 3 H=89023568901235678901 H=19 H=4 kplex k15 D 01000000000002010001 kcore k4 Cut 0 leaves {9,31} as a 0plex G7 1 2 3 H=89023568901235678901 H=17 H=2 kplex k15 D 01000000000002010011 kcore k2 Cut 0 leaves {27,30} as a 0plex 1 2 3 H=89023568901235678901 H=14 H=0 kplex k14 D 0100000000000201001kcore k0 no edges left The expected communities are mostly not detected as kplexes or kcores. 1 2 3 4 5 6 01234567890123456789012345678901234567890123456789012345678901234 [email protected]#$ (Symbols for base 65 )
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Cut examples • • • • • • 6-9-15 cut -c 10-20 /etc/passwd cut -c -10 /etc/passwd cut -c 30- /etc/passwd cut -d ":" -f 5 /etc/passwd cut -d ":" -f 2,5 /etc/passwd cut -d ":" -f 3-5 /etc/passwd 13
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Gross Requirements Plan Week 1 A. Required date Order release date B. Required date Order release date C. Required date Order release date E. Required date Order release date F. Required date Order release date G. Required date Order release date G. Required date Order release date 2 3 4 5 6 7 50 100 100 150 200 300 200 300 300 600 300 600 300 300 200 200 150 8 Lead Time 50 1 week 2 weeks 1 week 2 weeks 3 weeks 1 week 2 weeks Table 14.3 © 2011 Pearson Education, Inc. publishing as Prentice Hall 14 - 35
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Management Artifacts Release Descriptions   Release Descriptions document the contents of each release including performance against each of the evaluation criteria in the corresponding Release Spec. Release Descriptions have a Release Baseline that assert that the objectives of a release have been addressed and verified via:     Demonstration, testing, inspection, or analysis 29
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    Work release is both a type of institutional corrections & community corrections program Offenders are only released to go to work or attend school Jail-based work release may allow weekender programs & some pretrial programs, along with traditional work release Traditional work release includes: • unsupervised release where offenders leave the jail every day to go to work on their own • Supervised release where a group of offenders are transported under supervision & security to the same work site  Research is scant about the effectiveness of work release programs to reduce recidivism
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Factors influencing system release planning Factor Description Technical quality of the system If serious system faults are reported which affect the way in which many customers use the system, it may be necessary to issue a fault repair release. Minor system faults may be repaired by issuing patches (usually distributed over the Internet) that can be applied to the current release of the system. Platform changes You may have to create a new release of a software application when a new version of the operating system platform is released. Lehman’s fifth law (see Chapter 9) This ‘law’ suggests that if you add a lot of new functionality to a system; you will also introduce bugs that will limit the amount of functionality that may be included in the next release. Therefore, a system release with significant new functionality may have to be followed by a release that focuses on repairing problems and improving performance. Chapter 25 Configuration management 44
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