/// <summary>
/// Add a rule node into the appropriate chains within the graph.
/// </summary>
/// <remarks>
/// The node is prepended to the watch chains for each of the two literals it
/// watches.
/// Assertions are skipped because they only require on a single package and
/// have no alternative literal that could be true, so there is no need to
/// watch changes in any literals.
/// </remarks>
/// <param name="node">The rule node to be inserted into the graph.</param>
public void Add(RuleWatchNode node)
{
if (node.GetRule().IsAssertion)
{
return;
}
foreach (var literal in new[] { node.Watch1, node.Watch2 })
{
if (!watchChains.TryGetValue(literal, out LinkedList <RuleWatchNode> watchChainNode))
{
watchChains[literal] = watchChainNode = new LinkedList <RuleWatchNode>();
}
watchChainNode.AddFirst(node);
}
}
/// <summary>
/// Set propagate learn.
/// </summary>
/// <remarks>
/// Add free decision (a positive literal) to decision queue
/// increase level and propagate decision return if no conflict.
/// in conflict case, analyze conflict rule, add resulting
/// rule to learnt rule set, make decision from learnt
/// rule (always unit) and re-propagate.
/// </remarks>
/// <returns>returns the new solver level or 0 if unsolvable.</returns>
private int SetPropagateLearn(int level, int literal, Rule rule)
{
level++;
decisions.Decide(literal, level, rule);
while (true)
{
rule = Propagate(level);
if (rule == null)
{
// return if no conflict.
break;
}
if (level == 1)
{
return(AnalyzeUnsolvable(rule));
}
// conflict
var(learnLiteral, newLevel, newRule, why) = Analyze(level, rule);
if (newLevel <= 0 || newLevel >= level)
{
throw new SolverBugException(
$"Trying to revert to invalid level {newLevel} from level {level}.");
}
else if (newRule == null)
{
throw new SolverBugException(
$"No rule was learned from analyzing {rule} at level {level}.");
}
level = newLevel;
Revert(level);
rules.Add(newRule, RuleType.Learned);
learnedWhy[newRule.ObjectId] = why;
var ruleNode = new RuleWatchNode(newRule);
ruleNode.Watch2OnHighest(decisions);
watchGraph.Add(ruleNode);
decisions.Decide(learnLiteral, level, newRule);
}
return(level);
}
