day 3
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@ -6,6 +6,7 @@
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#let tru = $"true"$
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#let fls = $"false"$
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#let star(x) = $#x^*$
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== Lecture 1
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@ -329,4 +330,164 @@ Subset of $K$: $(B, 0, 1, +, ;, overline((..)))$ is a boolean algebra. _Sub-alge
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This is only true of language without effects or concurrency.
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- Threads can be reasoned about in a partially distributive commutative lattice
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- Threads can be reasoned about in a partially distributive commutative lattice
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#image("lec2.jpg")
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#pagebreak()
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== Lecture 3
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- _what is the semantics of $K A(T)$_?
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- Examples (such as how to tell if while loops are the same)
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- Net KAT (syntax and examples)
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Two types of semantics for Kleene algebra are the denotational semantics and the operational semantics.
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Having a conversion between both representations lets you pick the best of both worlds.
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- Denotational better for describing the gist of the language
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- Operational better for implementation
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=== KAT syntax
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- $e ::= 0 | 1 | p in P | e + e | e ; e | star(e) | b in B$
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- b is read "assert b", a kind of test
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- $b ::= t in T | 0 | 1 | b or b | b and b | overline(b)$
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- split alphabet $A$ into two parts, $T union.plus P$ where $T$ describes the basic tests
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- this is embedded in the programs part
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After writing down assertion, everything after the assertion can be assumed to be true.
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If you have $alpha :equiv t_1 overline(t_2) t_3 ... overline(t_1) t_2 overline(t_3) ...$ including all basic tests $t$ and their complements this is considered a _full test_.
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For example, if $t_1 t_2 overline(t_1) overline(t_2)$, then there are 4 options for $alpha$:
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- $alpha_0 :equiv t_1 t_2$
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- $alpha_1 :equiv t_1 overline(t_2)$
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- $alpha_2 :equiv overline(t_1) t_2$
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- $alpha_3 :equiv overline(t_1) overline(t_2)$
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Any other expression is a subset of this full test, $2^T$. So the semantics of booleans is $db(b) equiv 2^(2^T)$
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Interleave programs between atoms, used to be $star(A)$, now $star((A t ; P)) ; A t$. There is an option of where to refine the $P$. So now we have:
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#rect[$db(e) : 2^star((A t ; P)) ; A t$]
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Also, $db(b) = {alpha | alpha <= b}$ (boolean satisfiability). For example, $t_1 t_2 <= t_1$ and $t_1 t_2 <= t_2$ but it doesn't $<= overline(t_2)$.
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Also $db(p) = {alpha p beta | alpha_1 beta in A t}$. With $p$ uninterpreted, we only know that $p$ can transform any $alpha$ into any $beta$
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- $db(e + f) equiv db(e) union db(f)$
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- $db(e \; f) equiv db(e) diamond.small db(f)$
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- $alpha_0 p_0 alpha_k diamond.small beta_0 ...$ the $alpha_k diamond.small beta_0$ must match.
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Otherwise the program cannot continue; this operation is undefined.
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Then it deletes the repeated atoms so it is the same.
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(Because $alpha$ and $beta$ are atoms, they are not expressions that can contain other atoms so it's based on exact matching)
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- Star is the same as before, but also using the diamond
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=== KAT Example
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For $ifthenelse(b,p,q)$ which is $b;p+overline(b);q$:
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$&db(ifthenelse(b,p,q)) \
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equiv &db(b\;p) union db(overline(b\;q)) \
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equiv & db(b) diamond.small db(p) union ... \
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equiv & {alpha | alpha <= b } diamond.small {alpha p beta | alpha beta in A t} union ... \
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equiv & {alpha p beta | alpha <= b} union {alpha q beta | alpha <= overline(b)}
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$
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The semantics of this expression has 2 types of traces.
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One where I start in b, where $p$ is executed.
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Another is where I started in a state where the condition $b$ is false, so I executed the $q$ branch.
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For $"while" b "do" p$ which is $star((b ; p)) ; overline(b)$
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$&db("while" b "do" p) \
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equiv & { beta , alpha_0 p beta , alpha_0 p alpha_1 p beta , ... | alpha_i <= b, beta <= overline(b)}$
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For traces that don't terminate: $"while true do skip" equiv 0$. (there are alternate semantics where you record infinite traces) With non-termination, your observation power is 0.
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=== Connection to Hoare triples
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For ${b} C {c}$, the validity of the Hoare triple is the same thing as the KAT equation $b C overline(c) equiv 0$ (filtering out all the postconditions that render the condition false would result in empty)
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Another one is $b C <= C c$. This is equivalent to the previous one #TODO Show this
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=== Exercise solutions
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$star(x + y) equiv star((star(x) y)) star(x)$
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Need to prove it in two steps, $<=$ and $>=$:
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- Use the fixpoint rule: $1 <= star((star(x) y)) star(x)$.
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- This is true because $1 <= star(x)$ for any $x$
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- $x star(x) star((y star(x))) <= star(x) star((y star(x)))$.
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- This uses the fact that $x star(x) <= star(x)$.
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- This is true because unfold the star to get $x star(x) <= 1 + x star(x)$
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- $star((y star(x))) star((y star(x))) <= star((y star(x))) <= star(x) star((y star(x)))$
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- $1 <= star(x)$, so add this to both sides
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- Taking the sum of the previous 3 things: $1 + (x+y) star(x) star((y star(x))) <= star(x) star((y star(x)))$
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- let $cal(x) = star(x) star((y star(x)))$. THen $1 + (x + y) cal(x) <= cal(x)$
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- Apply fix point rule here: $star((x + y)) <= star(x) star((y star(x)))$
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=== Summary
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- Soundness + Completeness (KA + BA) are all you need to prove that 2 programs are equivalent
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- Automaton model is where transitions are (atoms ; programs) and the final state is what atoms to validate. This is known as a KAT automaton.
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- Equivalece of these automata is decidable, using BDDs (Pous), matrices (Kozen) and these are all $in$ PSPACE.
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- Some of these algorithms are very efficient despite PSPACE and they use the Union-find datastructure (Hopcroft, Tarjan)
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- $O(n log_c n)$ where $c$ is the inverse of the ackermann function, so the log part is _very_ small (in fact the original conjecture was that it was linear)
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- Improvement "Coinduction up-to" on NFA, DFA, Brz. derivatives, can improve the theoretical limit (?)
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=== While loop example
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#table(
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columns: (1fr, 1fr),
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```
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while a do
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p;
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while c do
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q;
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```,
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```
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if b then
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p;
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while b or c do
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if c then
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q;
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else
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p;
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```,
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$star((b p star((c q)) overline(c))) b$,
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$b ; p ; star(((b + c) (c q + overline(c) p))) overline(b) overline(c) + overline(b)$
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)
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Show these are the same by applying denesting and sliding.
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=== Net KAT
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Net KAT is a special KAT. Think of networks as boxes the only thing they can do is get packets in, change something about the packet, and then sends the packet on.
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Packets are records of fields $f_1, ..., f_k$ mapping to values $v_1, ..., v_k$. Program actions ($p = f arrow.l n$) and tests ($f = n$) come in pairs.
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For example:
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#quote(block: true)[
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Sw - switch \
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Type - { SSH, ... } \
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Pt - port \
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Dst - destination
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$("Sw" = 2); ("Type" = "SSH"); ("Pt" <- 4) ; ("Dst" <- "10.2.10.2")$
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For any packet that comes in, it filters using the test. If they pass the test, then you can set the fields on them.
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Using KAT, you can perform network reachability.
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]
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