For applications of hardness of approximation we often need a 'decoding scheme' - for a fixed code $C$ and a given word $f$, the scheme should return some possibly random codeword $f'$ which in some sense is a decoding of $f$. The codewords $f'$ that are returned may sometimes be totally uncorrelated with $f$, and yet in some sense they are still a reasonable decodings of $f$: an example may be the case where $C$ is the long-code, $f$ is a character $f=\chi_{\{7,69\}}$, and the decoding scheme returns either $f'=\chi_{7}$ or $f'=\chi_{69}$. These are reasonable decodings of $f$, and yet their correlation with $f$ is zero.
The problem is now how to define this 'reasonable decoding scheme'. Since I failed to give a full definition in class of a reasonable decoding scheme in the case of constraint testers, let me try to compensate by giving the definition here, together with some additional explanations. I will still repeat some of the last part of today's class next week.
Let up start with the definition of a decoding scheme.
A decoding scheme for a code $C$ is a mapping $D$ that associates each string $f$ with a distribution $D(f)$ over codewords from $C$ and possibly the bottom symbol $\bot$ (the bottom symbol will basically appear when the decoding scheme gives up).
Note that in the above definition we gave the decoding scheme total freedom - it can always return just one codeword, it can return the uniform distribution over all codewords, or it can just give up and always return bottom. There are definitely many lousy decoding schemes, but in the definition of a test we'll require good ones.
We decide if a decoding scheme is good by whether the decoding it returns satisfies the constraints that we want to verify, but as noted in class someone can just try to sell us a couple of decoding schemes that always return the same strings $f',g'$, which happen to satisfy the given constraint, and have nothing to do with the original $f$ and $g$. Indeed, to make the decoding problem interesting we need to look not only on one constraint, but on a family of constraints: the decoding scheme will have to figure out $f'$ and $g'$ (given $f$ and $g$ respectively) without knowing which constraint from the family is tested.
A constraint family over codes $C_1,C_2$ is a set $\{R_\lambda\}_{\lambda\in \Lambda}$ of relations $R_\lambda$ on $C_1$ and $C_2$. Given $f\in C_1$ and $g\in C_2$, we say that they satisfy the $\lambda$-constraint in the family if $fR_\lambda g$.
We are going to look at tests over families of constraints. The testing procedure will be given an index $\lambda$ of a relation in the family, and then query some bits from the given strings $f$ and $g$. Formally,
A $q$-query constraint tester for codes $C_1,C_2$ and a family $\{R_\lambda\}_{\lambda\in \Lambda}$, is a procedure that given two strings $f,g$ and an index $\lambda$, makes $q$ queries to $f$ and $g$ and then either accepts or rejects.
We say that the tester has completeness $c$ if when $f\in C_1$, $g\in C_2$ and $fR_\lambda g$, the test accepts with probability at least $c$. The more difficult part is to define soundness. We say that a tester has soundness $s=s(\delta)$ for $\delta$-satisfaction if there are decoding schemes $D_1$ for $C_1$ and $D_2$ for $C_2$ such that the following holds: for any strings $f,g$ and any index $\lambda$, if
$\Pr[$tester accepts on $f,g,\lambda]>s$,
implies
$\Pr_{f'\sim D_1(f), g'\sim D_2(g)}[f'R_\lambda g']\geq \delta$.
As food for thought, consider the problem of testing whether $f$ and $g$ are in the Hadamard code and that additionally $f=\chi_T g$ for a given $T$. Can you devise a three query constraint tester for this problem? Can you show some non-trivial bounds on its soundness?
