a glossary of terms used in Sysudoku posts and pages.

1-way – an AIC starting on a slink, which removes a candidate seen by the starting candidate. The victim is false, whether the starting candidate is true or false.

3-fill – a unit with three cells not assigned a value. Also the method of assigning a value to a 3-fill cell because it is seen by the two other missing values, or because two of the 3-fill cells are seen by the value in two other units.

4-fill – a unit with four cells not assigned a value, which can be resolved to a 3-fill because a candidate not in the unit sees two of the unassigned cells.

AIC – an alternating inference chain – a candidate chain of alternating slinks and winks.

AIC building – a late advanced stage of solving when AIC of single node types are exhausted, and AIC of mixed types are explored. At this stage, AIC are started several ending possibiities in mind, and a network of explored AIC is kept on the grid for connecting with AIC to be started.

ALS – an almost locked set – a set of cells of the same unit with one extra number, becoming locked if one number is removed.

ALS AIC – an AIC including one or more ALS nodes.

ALS node – An ALS functioning as an AIC node.

ALS value set, value group – a set of candidates of a value in an ALS. In an ALS, the value sets are strongly group linked: if one value-set is erased, all remaining are locked.

ANL, almost nice loop– an alternative inference chain closed by one extra wink or slink. If the extra link is a wink, the candidate between winks is removed. In Sysudoku posts, enclosing winks of an ANL removal are omitted. If the extra link is a slink, the candidate between slinks is confirmed.

BARN – bent almost restricted n-set. n cells containing n numbers in an overlapping box and line, with candidates of all but one of the values seeing each other (being restricted).

Basic, Sysudoku Basic – The identification of candidates, placements and links determined by the givens, in progress.

bent region – the union of cells in a box and a crossing line.

BNS-0 – bent naked *n*-set zero, *n* cells containing *n* numbers in a bent region, with no values in both remainders outsideof the intersection. Each value set has a true candidate (is locked, is toxic).

BNS-1 – bent naked *n-*set one, *n* cells containing *n* numbers in a bent region, with one value in both remainders outside of the intersection. The remainder candidates of this value includes a true candidate (are locked, is a toxic set). A BNS-1 is a BARN.

boomerang, boomer – an AIC loop starting with a slink and closing with a wink into a second candidate of the starting cell. If the cell has 3 or more candidates, an internal wink closes the loop and the re-entry candidate is removed. Boomers are normally spotted in the AIC building stage of Sysudoku Advanced.

box – A block of 3 x 3 cells to contain 9 values in the solution. Boxes are designated by compass points in Sysudoku.

box marking – box slink marking based on outside clues and slinks of like value excluding the value from cells of a box.

box slink – a slink made by the only two candidates of the same value in a box.

box/line – removals based on the fact that if a value in a box is confined to a line, it cannot be anywhere else in the line, or on the fact that if a value in a line is confined to a box, it cannot be anywhere else in the box. In Sysudoku posts, the bent region of the box/line is identifies by the box name and line number.

bv, bivalue cell – after line marking, a cell containing two candidates.

bv boomerang – a boomerang in which the starting cell is a bv. The internal slink closes the loop and the starting candidate is confirmed.

bypass, slink marking bypass – the first stage of Sysudoku Basic, in which slink marking is left implicit while clues and subsets are marked.

chute – The intersection of a line and a box.

cluster – a network of slink partners marked by two colors.

coloring, Medusa coloring – the marking of slink networks (clusters) by two opposing colors. Coloring identifies two sets of slink partner candidates, one of which is true and the other false, without having to determine which set is true.

complex 1-way – a 1-way AIC with branching winks that activate slinks to be traversed by the chain.

dublex, double line exclusion – use of markings in two lines for marking the remaining chute of a third box.

enumerating – displaying every instance of

ER – a form of weak link involving an Empty Rectangle box pattern, not a pattern completed by an ER wink.

ER wink – a wink defined by an ER inference chain. Sysudoku now marks ER inference chains as forcing chains (wink performing X-chains)

exocet – a pattern of four cells containing the same 3 or 4 candidates, and others to be eliminated by trial.

finned fish – a fish spoiled by an extra candidate (the fin), but still effective on a victim candidate in the same box as the fin.

forcing chain – an alternating inference chain starting with a weak link, it extends “seeing” across the grid in many methods.

freeform – a representation of a pattern as a graphics freeform (of connected line segments) across an X-panel.

freeform analysis – determination of possible patterns of a value enumerating their freeforms.

group – a set of candidates of the same value in a unit. Not necessarily containing all candidates in the unit of that value. A group is false if it contains no solution candidate of its value. A group is true if it contains a solution candidate. A candidate or group sees a group if every candidate sees every candidate of the group. Groups are represented by thick solid curves and enclosing curves.

hidden dublex – a dublex in which marking of the third line of the box is forced by marks, not clues.

hidden UR – hidden unique rectangle, a unique rectangle made effective by slinks between its principle candidates (see UR table in Sysudoku Tools)

kraken fish – a finned fish with a candidate outside the fin box removed by a wink chain

krakening a finned fish – determining a wink path between fin and kraken victim, allowing the victim to be removed.

line – a row or a column.

lite color, lite coloring – marking candidates which are true when a cluster color becomes known to be true. Such candidates are said to be of the color, but “lite”. Lite candidates are as effective as full color candidates in trapping and bridging. In Sysudoku, lite candidates are marked by arrow trees from full color candidates.

locked set – a group of candidates containing a true candidate.

LPO – Limited Pattern Overlay: A set of pattern overlay methods reducing possible patterns of a number

nice loop – a closed alternating inference chain. End candidates of every link are toxic sets.

nice loop coloring, nice loop cluster – Alternate node coloring in a nice loop creates a cluster with one color representing clockwise traversal, and the other representing counterclockwise traversal. The cluster is valid in multi-cluster methods.

orphan – a candidate included in no pattern of its value.

pattern – a distribution of candidates of a value that places one candidate in each unit.

pattern slicing – The division of patterns into disjoint sets based on slink partners they include.

pencil mark –a small font digit representing the presence of a candidate in a cell.

pink/olive analysis – The coloring of candidates based on membership in pattern slices.

placement – an assignment of a solution value to a cell.

sees – is a weak link with

slink – strong link: a link between candidates in which at least one partner is true. A slink is represented by a solid curve.

slink marking – the Sysudoku pencil marking that uses candidate position within the cell to mark slinks and aligned triples (diagram).

slink marking bypass – the bypass

subset – a set of *n* cells in a unit containing all of the candidates of *n* values.

suset – a pair of digit strings identifying cells and the values these cells contain. Susets define ALS and subsets.

suset enumeration scratchpad – a hand calculation algorithm for enumerating almost locked sets in Sudoku. Developed in Sysudoku and applied to finned and regular fish, ALS and locked sets. Detailed in The Guide/Sysudoku Basic.

suset enumeration scratchpad – a hand calculation algorithm for enumerating all susets in a Sudoku situation, such as fish, ALS and subsets.

Sysudoku Advanced – solving methods based on relations among completely identified candidates.

Sysudoku Basic – starting procedures in Sysudoku to find subsets and clues and slink markings, along with all candidates.

toxic set – a set of candidates determined by a pattern to have at least one true candidate. A candidate seeing the whole set is false.

trace – A recording of solving events . See the Sysudoku Trace page.

trial – A true or false test of a set of logically related candidates, trial-and-error – a Sudoku term generally applied to trying out guesses, i.e. assertions not derived logically from existing candidates.

trial trace – A trace for identifying a contradiction in the shortest chains of inferences.

true candidate – A candidate that is in the solution.

unit – a box, row or column.

value – a term used for one of the digits 1 – 9, in place of the term “number”.

value group – candidates of the same value in an ALS.

wink, weak link – a link between candidates in which both partners cannot be true. When one is proved true, the other is false. On Sysudoku grids, winks are dashed curves.

wrap – the determination that a cluster color is false. The opposing color is confirmed.

X-chain – an AIC of candidates of a single value (X).

X-panel – a set of tables showing the remaining candidates of each value, without clues.

XY railway – a set of curves on the bv map showing possible paths of XY-chains

… So my question is, what are some logic rules to get going? With the other ones the strategy is to start from the corners and sides and work inwards. So without the walls, where is the logic to start (the 4s or 2s)?

Andi, you’re at one of the few places to explain how to start. It’s in the earliest posts of September/October 2011. The beginner’s page is a prep to these posts. You start by finding some candidates which work to help you find all of them. That is basic solving, in two stages. Then with all the candidates you can do advanced strategies. In fact that is the definition of advanced strategies, the ones requiring all candidates.

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