Planet Scheme

September 02, 2014

Programming Praxis

Longest Increasing Subsequence

A sequence is a list of integers (or any other ordered type, but we’ll use integers to keep things simple). A subsequence is any, possibly non-consecutive, list drawn from the parent sequence with items in the same order as the parent sequence. An increasing subsequence is a subsequence with all the items in increasing order. A longest increasing subsequence (there may be more than one with the same length) is an increasing subsequence of a parent sequence of the greatest possible length. For instance, the sequence (3 2 6 4 5 1) has longest increasing subsequences (2 4 5) and (3 4 5).

The algorithm to find the longest increasing subsequence is similar to the algorithm for patience sorting of a previous exercise, with a small modification. When dealing the cards, each time a card is placed on a pile, a back-pointer to the top card on the previous pile is placed along with the card. Then, when all the cards are dealt, the number of piles is the length of the longest increasing subsequence, and the longest increasing subsequence can be recovered by taking the top card from the last pile and following the back-pointers to previous piles.

For instance, with sequence (3 2 6 4 5 1) the cards are dealt with 3 and 2 on the first pile, 6 and 4 on the second pile, 5 on the third pile, and 1 on the first pile, so the longest increasing subsequence has length 3. The 5 on the third pile ends the longest increasing subsequence, it points to the 4 which was on the top of the second pile when 5 was added to the third pile, and 4 points to the 2 which was on the top of the first pile when 4 was added to the second pile; even though 1 was later added to the first pile, is wasn’t yet on the pile when 4 was added to the second pile, so it’s not part of the longest increasing subsequence.

Your task is to write a program to find the longest increasing subsequence of a sequence. When you are finished, you are welcome to read or run a suggested solution, or to post your own solution or discuss the exercise in the comments below.

by programmingpraxis at September 02, 2014 09:00 AM

August 31, 2014

Jeremy Kun

A Rook Game

Problem: Two players take turns moving a rook on an 8×8 chessboard. The rook is only allowed to move south or west (but not both in a single turn), and may move any number of squares in the chosen direction on a turn. The loser is the player who first cannot move the rook. What is the optimal play […]

by Jeremy Kun at August 31, 2014 10:51 PM

August 29, 2014

Programming Praxis

Generating Palindromes

The first hundred palindromic numbers are 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 11, 22, 33, 44, 55, 66, 77, 88, 99, 101, 111, 121, 131, 141, 151, 161, 171, 181, 191, 202, 212, 222, 232, 242, 252, 262, 272, 282, 292, 303, 313, 323, 333, 343, 353, 363, 373, 383, 393, 404, 414, 424, 434, 444, 454, 464, 474, 484, 494, 505, 515, 525, 535, 545, 555, 565, 575, 585, 595, 606, 616, 626, 636, 646, 656, 666, 676, 686, 696, 707, 717, 727, 737, 747, 757, 767, 777, 787, 797, 808, 818, 828, 838, 848, 858, 868, 878, 888, 898, and 909.

Your task is to write a program that generates the palindromic numbers in order; use it to find the ten-thousandth palindromic number. When you are finished, you are welcome to read or run a suggested solution, or to post your own solution or discuss the exercise in the comments below.

by programmingpraxis at August 29, 2014 09:00 AM

Joe Marshall

A use of Newton's method

I've seen more than one book claim that computing with real numbers inevitably involves round-off errors because real numbers can have an infinite number of digits after the decimal point and no finite representation can hold them. This is false. Instead of representing a real number as a nearby rational number with an error introduced by rounding, we'll represent a real number as computer program that generates the digits. The number of digits generated is potentially infinite, but the program that generates them is definitely finite.

Here is Gosper's algorithm for computing the square root of a rational number.
(define (gosper-sqrt a b c d)
  ;;   Solve for
  ;; ax + b 
  ;; ------  = x
  ;; cx + d
  (define (newtons-method f f-prime guess)
    (let ((dy (f guess)))
      (if (< (abs dy) 1)
          (let ((dy/dx (f-prime guess)))
            (newtons-method f f-prime (- guess (/ dy dy/dx)))))))

  (define (f x)
    (+ (* c x x)
       (* (- d a) x)
       (- b)))

  (define (f-prime x)  
    (+ (* 2 c x)
       (- d a)))

  (let ((value (floor (newtons-method f f-prime b))))
    (cons-stream value
                 (gosper-sqrt (+ (* c value) d)
                              (+ (* (- a (* value c)) value) 
                                 (- b (* value d)))
                              (- a (* value c))))))

1 ]=> (cf:render (gosper-sqrt 0 17 10 0))

;; base 10, 100 digits
1 ]=> (cf:render (gosper-sqrt 0 17 10 0) 10 100)

by Joe Marshall ( at August 29, 2014 12:06 AM

August 26, 2014

Joe Marshall

Solutions in search of problems

Suppose you have a function like (define foo (lambda (x) (- (* x x x) 30))) and you want to find x such that (foo x) = 0. There are a few ways to go about this. If you can find two different x such that (foo x) is positive for one and negative for the other, then (foo x) must be zero somewhere in between. A simple binary search will find it.
(define (bisection-method f left right)
  (let* ((midpoint (average left right))
         (fmid     (f midpoint)))
    (if (< (abs fmid) 1e-8)
        (let ((fl (f left))
              (fr (f right)))
          (cond ((same-sign? fl fr) (error "Left and right not on opposite sides."))
                ((same-sign? fmid fr) (bisection-method f left midpoint))
                ((same-sign? fl fmid) (bisection-method f midpoint right))
                (else (error "shouldn't happen")))))))

(define (average l r) (/ (+ l r) 2))

(define (same-sign? l r)
  (or (and (positive? l)
           (positive? r))
      (and (negative? l)
           (negative? r))))

1 ]=> (cos 2)

;Value: -.4161468365471424

1 ]=> (cos 1)

;Value: .5403023058681398

1 ]=> (bisection-method cos 1.0 2.0)
1. 2.
1.5 2.
1.5 1.75
1.5 1.625
1.5625 1.625
1.5625 1.59375
1.5625 1.578125
1.5703125 1.578125
1.5703125 1.57421875
1.5703125 1.572265625
1.5703125 1.5712890625
1.5703125 1.57080078125
1.570556640625 1.57080078125
1.5706787109375 1.57080078125
1.57073974609375 1.57080078125
1.570770263671875 1.57080078125
1.5707855224609375 1.57080078125
1.5707931518554687 1.57080078125
1.5707931518554687 1.5707969665527344
1.5707950592041016 1.5707969665527344
1.570796012878418 1.5707969665527344
1.570796012878418 1.5707964897155762
1.570796251296997 1.5707964897155762
1.570796251296997 1.5707963705062866
1.5707963109016418 1.5707963705062866
1.5707963109016418 1.5707963407039642
;Value: 1.570796325802803
Rather than selecting the midpoint between the two prior guesses, you can pretend that your function is linear between the guesses and interpolate where the zero should be. This can converge quicker.
(define (secant-method f x1 x2)
  (display x1) (display " ") (display x2) (newline)
  (let ((f1 (f x1))
        (f2 (f x2)))
    (if (< (abs f1) 1e-8)
        (let ((x0 (/ (- (* x2 f1) (* x1 f2))
                     (- f1 f2))))
          (secant-method f x0 x1)))))

1 ]=> (secant-method cos 0.0 4.0)
0. 4.
2.418900874126076 0.
1.38220688493168 2.418900874126076
1.5895160570280047 1.38220688493168
1.5706960159120333 1.5895160570280047
1.5707963326223677 1.5706960159120333
;Value: 1.5707963326223677
If you know the derivative of f, then you can use Newton's method to find the solution.
(define (newtons-method f f-prime guess)
  (display guess) (display " ") (newline)
  (let ((dy (f guess)))
    (if (< (abs dy) 1e-8)
        (let ((dy/dx (f-prime guess)))
          (newtons-method f f-prime (- guess (/ dy dy/dx)))))))

1 ]=> (newtons-method cos (lambda (x) (- (sin x))) 2.0)
;Value: 1.5707963267948966
Here's another example. We'll find the cube root of 30 by solving (lambda (x) (- (* x x x) 30)).
(define (cube-minus-thirty x) (- (* x x x) 30))

1 ]=> (bisection-method cube-minus-thirty 0.0 4.0)
0. 4.
2. 4.
3. 4.
3. 3.5
3. 3.25
3. 3.125
3.0625 3.125
3.09375 3.125
3.09375 3.109375
3.1015625 3.109375
3.10546875 3.109375
3.10546875 3.107421875
3.1064453125 3.107421875
3.10693359375 3.107421875
3.107177734375 3.107421875
3.107177734375 3.1072998046875
3.107177734375 3.10723876953125
3.107208251953125 3.10723876953125
3.1072235107421875 3.10723876953125
3.1072311401367187 3.10723876953125
3.1072311401367187 3.1072349548339844
3.1072311401367187 3.1072330474853516
3.107232093811035 3.1072330474853516
3.107232093811035 3.1072325706481934
3.1072323322296143 3.1072325706481934
3.107232451438904 3.1072325706481934
3.107232451438904 3.1072325110435486
3.107232481241226 3.1072325110435486
3.1072324961423874 3.1072325110435486
3.107232503592968 3.1072325110435486
3.107232503592968 3.1072325073182583
3.107232505455613 3.1072325073182583
3.107232505455613 3.1072325063869357
;Value: 3.1072325059212744

1 ]=> (secant-method cube-minus-thirty 0.0 4.0)
0. 4.
1.875 0.
8.533333333333333 1.875
2.1285182547245376 8.533333333333333
2.341649751209406 2.1285182547245376
3.4857887202177547 2.341649751209406
3.0068542655016235 3.4857887202177547
3.0957153766467633 3.0068542655016235
3.1076136741672546 3.0957153766467633
3.1072310897513415 3.1076136741672546
3.1072325057801455 3.1072310897513415
;Value: 3.1072325057801455

1 ]=> (define (cube-minus-thirty-prime x) (* 3 x x))

1 ]=> (newtons-method cube-minus-thirty cube-minus-thirty-prime 4.0)
;Value: 3.107232505953859

by Joe Marshall ( at August 26, 2014 08:33 PM

Jeremy Kun

When Greedy Algorithms are Perfect: the Matroid

Greedy algorithms are by far one of the easiest and most well-understood algorithmic techniques. There is a wealth of variations, but at its core the greedy algorithm optimizes something using the natural rule, “pick what looks best” at any step. So a greedy routing algorithm would say to a routing problem: “You want to visit all […]

by Jeremy Kun at August 26, 2014 02:00 PM

Programming Praxis

Integer Logarithm

The integer logarithm function in the Standard Prelude looks like this:

(define (ilog b n)
  (let loop1 ((lo 0) (b^lo 1) (hi 1) (b^hi b))
    (if (< b^hi n) (loop1 hi b^hi (* hi 2) (* b^hi b^hi))
      (let loop2 ((lo lo) (b^lo b^lo) (hi hi) (b^hi b^hi))
        (if (<= (- hi lo) 1) (if (= b^hi n) hi lo)
          (let* ((mid (quotient (+ lo hi) 2))
                 (b^mid (* b^lo (expt b (- mid lo)))))
            (cond ((< n b^mid) (loop2 lo b^lo mid b^mid))
                  ((< b^mid n) (loop2 mid b^mid hi b^hi))
                  (else mid))))))))

It performs binary search in loop1 until n is bracketed between b^lo and b^hi, doubling at each step, then refines the binayr search in loop2, halving the bracket at each step.

Inspired by that function, Joe Marshall posed this puzzle at his Abstract Heresies web site:

You can get the most significant digit (the leftmost) of a number pretty quickly this way:

(define (leftmost-digit base n)
  (if (< n base)
      (let ((leftmost-pair (leftmost-digit (* base base) n)))
        (if (< leftmost-pair base)
            (quotient leftmost-pair base)))))

The puzzle is to adapt this code to return the position of the leftmost digit.

Your task is to write Joe’s puzzle function; you might also click through to his website to spike his stats. When you are finished, you are welcome to read or run a suggested solution, or to post your own solution or discuss the exercise in the comments below.

by programmingpraxis at August 26, 2014 09:00 AM

August 25, 2014

Jeremy Kun

Parameterizing the Vertex Cover Problem

I’m presenting a paper later this week at the Matheamtical Foundations of Computer Science 2014 in Budapest, Hungary. This conference is an interesting mix of logic and algorithms that aims to bring together researchers from these areas to discuss their work. And right away the first session on the first day focused on an area I know is important but have little experience with: fixed parameter […]

by Jeremy Kun at August 25, 2014 11:50 AM

Andy Wingo

revisiting common subexpression elimination in guile

A couple years ago I wrote about a common subexpression pass that I implemented in Guile 2.0.

To recap, Guile 2.0 has a global, interprocedural common subexpression elimination (CSE) pass.

In the context of compiler optimizations, "global" means that it works across basic block boundaries. Basic blocks are simple, linear segments of code without control-flow joins or branches. Working only within basic blocks is called "local". Working across basic blocks requires some form of understanding of how values can flow within the blocks, for example flow analysis.

"Interprocedural" means that Guile 2.0's CSE operates across closure boundaries. Guile 2.0's CSE is "context-insensitive", in the sense that any possible effect of a function is considered to occur at all call sites; there are newer CSE passes in the literature that separate effects of different call sites ("context-sensitive"), but that's not a Guile 2.0 thing. Being interprocedural was necessary for Guile 2.0, as its intermediate language could not represent (e.g.) loops directly.

The conclusion of my previous article was that although CSE could do cool things, in Guile 2.0 it was ultimately limited by the language that it operated on. Because the Tree-IL direct-style intermediate language didn't define order of evaluation, didn't give names to intermediate values, didn't have a way of explicitly representing loops and other kinds of first-order control flow, and couldn't precisely specify effects, the results, well, could have been better.

I know you all have been waiting for the last 27 months for an update, probably forgoing meaningful social interaction in the meantime because what if I posted a followup while you were gone? Be at ease, fictitious readers, because that day has finally come.

CSE over CPS

The upcoming Guile 2.2 has a more expressive language for the optimizer to work on, called continuation-passing style (CPS). CPS explicitly names all intermediate values and control-flow points, and can integrate nested functions into first-order control-flow via "contification". At the same time, the Guile 2.2 virtual machine no longer penalizes named values, which was another weak point of CSE in Guile 2.0. Additionally, the CPS intermediate language enables more fined-grained effects analysis.

All of these points mean that CSE has the possibility to work better in Guile 2.2 than in Guile 2.0, and indeed it does. The shape of the algorithm is a bit different, though, and I thought some compiler nerds might be interested in the details. I'll follow up in the next section with some things that new CSE pass can do that the old one couldn't.

So, by way of comparison, the old CSE pass was a once-through depth-first visit of the nested expression tree. As the visit proceeded, the pass built up an "environment" of available expressions -- for example, that (car a) was evaluated and bound to b, and so on. This environment could be consulted to see if a expression was already present in the environment. If so, the environment would be traversed from most-recently-added to the found expression, to see if any intervening expression invalidated the result. Control-flow joins would cause recomputation of the environment, so that it only held valid values.

This simple strategy works for nested expressions without complex control-flow. CPS, on the other hand, can have loops and other control flow that Tree-IL cannot express, so for it to build up a set of "available expressions" requires a full-on flow analysis. So that's what the pass does: a flow analysis over the labelled expressions in a function to compute the set of "available expressions" for each label. A labelled expression a is available at label b if a dominates b, and no intervening expression could have invalidated the results. An expression invalidates a result if it may write to a memory location that the result may have read. The code, such as it is, may be found here.

Once you have the set of available expressions for a function, you can proceed to the elimination phase. First, you start by creating an "eliminated variable" map, which initially maps each variable to itself, and an "equivalent expressions" table, which maps "keys" to a set of labels and bound variables. Then you visit each expression in a function, again in topologically sorted order. For each expression, you compute a "key", which is some unique representation of an expression that can be compared by structural equality. Keys that compare as equal are equivalent, and are subject to elimination.

For example, consider a call to the add primitive with variables labelled b and c as arguments. Imagine that b maps to a in the eliminated variable table. The expression as a whole would then have a key representation as the list (primcall add a c). If this key is present in the equivalent expression table, you check to see if any of the equivalent labels is available at the current label. If so, hurrah! You mark the outputs of the current label as being replaced by the outputs of the equivalent label. Otherwise you add the key to the equivalent table, associated with the current label.

This simple algorithm is enough to recursively eliminate common subexpressions. Sometimes the recursive aspect (i.e. noticing that b should be replaced by a), along with the creation of a common key, causes the technique to be called global value numbering (GVN), but CSE seems a better name to me.

The algorithm as outlined above eliminates expressions that bind values. However not all expressions do that; some are used as control-flow branches. For this reason, Guile also computes a "truthy table" with another flow analysis pass. This table computes a set of which branches have been taken to get to each program point. In the elimination phase, if a branch is reached that is equivalent to a previously taken branch, we consult the truthy table to see which continuation the previous branch may have taken. If it can be proven to have taken just one of the legs, the test is elided and replaced with a direct jump.

A few things to note before moving on. First, the "compute an analysis, then transform the function" sequence is quite common in this sort of problem. It leads to some challenges regarding space for the analysis; my last article deals with these in more detail.

Secondly, the rewriting phase assumes that a value that is available may be substituted, and that the result would be a proper CPS term. This isn't always the case; see the discussion at the end of the article on CSE in Guile 2.0 about CPS, SSA, dominators, and scope. In essence, the scope tree doesn't necessarily reflect the dominator tree, so not all transformations you might like to make are syntactically valid. In Guile 2.2's CSE pass, we work around the issue by concurrently rewriting the scope tree to reflect the dominator tree. It's something I am seeing more and more and it gives me some pause as to the suitability of CPS as an intermediate language.

Also, consider the clobbering part of analysis, where e.g. an expression that writes a value to memory has to invalidate previously read values. Currently this is implemented by traversing all available expressions. This is suboptimal and could be quadratic in the end. A better solution is to compute a dependency graph for expressions, which links together operations on the same regions of memory; see LLVM's memory dependency analysis for an idea of how to do this.

Finally, note that this algorithm is global but intraprocedural, meaning that it doesn't propagate values across closure boundaries. It's possible to extend it to be interprocedural, though it's less necessary in the presence of contification.

scalar replacement via fabricated expressions

Let's say you get to an expression at label L, (cons a b). It binds a result c. You determine you haven't seen it before, so you add (primcall cons a b) → L, c to your equivalent expressions set. Cool. We won't be able to replace a future instance of (cons a b) with c, because that doesn't preserve object identity of the newly allocated memory, but it's definitely a cool fact, yo.

What if we add an additional mapping to the table, (car c) → L, a? That way any expression at which L is available would replace (car c) with a, which would be pretty neat. To do so, you would have to add the &read effect to the cons call's effects analysis, but since the cons wasn't really up for elimination anyway it's all good.

Similarly, for (set-car! c d) we can add a mapping of (car c) → d. Again we have to add the &read effect to the set-car, but that's OK too because the write invalidated previous reads anyway.

The same sort of transformation holds for other kinds of memory that Guile knows how to allocate and mutate. Taken together, they form a sort of store-to-load forwarding and scalar replacement that can entirely eliminate certain allocations, and many accesses as well. To actually eliminate the allocations requires a bit more work, but that will be the subject of the next article.

future work

So, that's CSE in Guile 2.0. It works pretty well. In the future I think it's probably worth considering an abstract heap-style analysis of effects; in the end, the precision of CSE is limited to how precisely we can model the effects of expressions.

The trick of using CSE to implement scalar replacement is something I haven't seen elsewhere, though I doubt that it is novel. To fully remove the intermediate allocations needs a couple more tricks, which I will write about in my next nargy dispatch. Until then, happy hacking!

by Andy Wingo at August 25, 2014 09:48 AM

August 22, 2014

Joe Marshall

Small puzzle solution

Before I give my solution, I'd like to describe the leftmost digit algorithm in a bit more detail.
(define (leftmost-digit base n)
  (if (< n base)
      (let ((leftmost-pair (leftmost-digit (* base base) n)))
        (if (< leftmost-pair base)
            (quotient leftmost-pair base)))))
The idea is this: if we have a one digit number, we just return it, otherwise we recursively call leftmost-digit with the square of the base. Squaring the base will mean gobbling up pairs of digits in the recursive call, so we'll get back either a one or two digit answer from the recursion. If it is one digit, we return it, otherwise it's two digits and we divide by the base to get the left one.

For example, if our number is 12345678 and the base is 10, we'll make a recursive call with base 100. The recursive call will deal with number as if it were written 12 34 56 78 in base 100 and return the answer 12. Then we'll divide that by 10 to get the 1.

Since we're squaring the base, we're doubling the number of digits we're dealing with on each recursive call. This leads to the solution in O(log log n) time. If we instrument quotient, you can see:
(leftmost-digit 10 816305093398751331727331379663195459013258742431006753294691576)
816305093398751331727331379663195459013258742431006753294691576 / 100000000000000000000000000000000
8163050933987513317273313796631 / 10000000000000000
816305093398751 / 100000000
8163050 / 10000
816 / 100
A sixty-three digit number trimmed down to one digit with only five divisions.

So a simple solution to the puzzle is:
(define (leftmost-digit+ base n)
  (if (< n base)
      (values n 0)
      (call-with-values (lambda () (leftmost-digit+ (* base base) n))
        (lambda (leftmost-pair count)
          (if (< leftmost-pair base)
              (values leftmost-pair (* count 2))
              (values (quotient leftmost-pair base) (+ (* count 2) 1)))))))
The second value is the count of how many digits we discard. If the number is less than the base, we return it and we discarded nothing. Otherwise, we make the recursive call with the base squared and get back two values, the leftmost pair and the number of pairs it discarded. If the leftmost pair is a single digit, we return it, otherwise we divide by the base. The number of digits discarded is simply twice the number discarded by the recursive call, plus one more if we had to divide.

But I don't see an easy way to separate finding the digit from finding the position. At first it seemed straightforward to just count the digits being discarded, but you can't decide whether to increment the count at each stage without determining if the leftmost part of the recursive call contains one or two digits.

by Joe Marshall ( at August 22, 2014 10:57 PM

Grant Rettke

Lexical Scope and Statistical Computing

Any paper that references SICP must be read.

It is curious how key computational ideas have propagated to one area of application exactly and one may have expected they would do so.

by Grant at August 22, 2014 02:34 PM

Programming Praxis

Patience Sorting

This sorting algorithm derives its name from the game of Patience (that’s the British name, we call it Solitaire in the United States) because it is implemented by analogy to sorting a shuffled deck of cards:

Starting with no piles, add the next card from the deck to the first pile with top card greater than the next card from the deck. If the next card from the deck is greater than the top card of all the piles, start a new pile. When the deck is exhausted, collect the cards in order by selecting the smallest visible card at each step.

For instance, consider sorting the list (4 3 9 1 5 2 7 8 6). The first stack gets 4 and 3. Since 9 is larger than 3, it starts a second stack, 1 goes on the first stack, then 5 and 2 go on the second stack. At this point the first stack (top to bottom) consists of (1 3 4), the second stack consists of (2 5 9), and the remaining deck consists of (7 8 6). Now 7 goes on a third stack, 8 goes on a fourth stack, and 6 goes on top of the 7 in the third stack. With all the cards dealt, 1 is collected from the first stack, 2 from the second stack, 3 and 4 from the first stack, 5 from the second stack, 6 and 7 from the third stack, 8 from the fourth stack, and 9 from the second stack. The algorithm has complexity O(n log n).

Your task is to implement the patience sorting algorithm. When you are finished, you are welcome to read or run a suggested solution, or to post your own solution or discuss the exercise in the comments below.

by programmingpraxis at August 22, 2014 02:00 PM

August 21, 2014

Joe Marshall

Just a small puzzle

You can get the most significant digit (the leftmost) of a number pretty quickly this way
(define (leftmost-digit base n)
  (if (< n base)
      (let ((leftmost-pair (leftmost-digit (* base base) n)))
        (if (< leftmost-pair base)
            (quotient leftmost-pair base)))))
The puzzle is to adapt this code to return the position of the leftmost digit.

(leftmost-digit+ 10 46729885)  would return two values, 4 and 7

by Joe Marshall ( at August 21, 2014 11:43 PM

August 19, 2014

Programming Praxis

Cracker Barrel

While I was out of town last week, I ate dinner one evening at Cracker Barrel, which provides a triangle puzzle at each table so you can amuse yourself while you are waiting for your food. When my daughter challenged me to solve the problem, I failed, but I promised her that I would write a program to solve it.

As shown in the picture at right, the puzzle is a triangle with 15 holes and 14 pegs; one hole is initially vacant. The game is played by making 13 jumps; each jump removes one peg from the triangle, so at the end of 13 jumps there is one peg remaining. A jump takes a peg from a starting hole, over an occupied hole, to an empty finishing hole, removing the intermediate peg.

Your task is to write a program that solves the Cracker Barrel puzzle; find all possible solutions that start with a corner hole vacant and end with the remaining peg in the original vacant corner. When you are finished, you are welcome to read or run a suggested solution, or to post your own solution or discuss the exercise in the comments below.

by programmingpraxis at August 19, 2014 02:00 PM

August 18, 2014

Andy Wingo

on gnu and on hackers

Greetings, gentle hackfolk. 'Tis a lovely waning light as I write this here in Munich, Munich the green, Munich full of dogs and bikes, Munich the summer-fresh.

Last weekend was the GNU hackers meeting up in Garching, a village a few metro stops north of town. Garching is full of quiet backs and fruit trees and small gardens bursting with blooms and beans, as if an eddy of Chistopher Alexander whirled out and settled into this unlikely place. My French suburb could learn a thing or ten. We walked back from the hack each day, ate stolen apples and corn, and schemed the nights away.

The program of GHM this year was great. It started off with a bang, as GNUnet hackers Julian Kirsch and Christian Grothoff broke the story that the Five-Eyes countries (US, UK, Canada, Australia, NZ) regularly port-scan the entire internet, looking for vulnerabilities. They then proceed to exploit those vulnerabilities, in regular hack-a-thons, trying to own as many boxes in as many countries as they can. They then use them as launchpads for attacks and for exfiltration of information from other networks.

The presentation that broke this news also proposed a workaround based on port-knocking, Knock. Knock embeds the hash of a pre-shared key with some other information into the 32-bit initial sequence number of a TCP connection. Unlike previous incarnations of port-knocking, Knock also authenticates the first n payload bytes, so that the connection isn't vulnerable to hijacking (e.g. via GCHQ "quantum injection", where well-placed evil routers race the true destination server to provide the first response packet of a connection). Leaking the pwn-the-internet documents with Laura Poitras at the same time as the Knock unveiling was a pretty slick move!

I was also really impressed by Christian's presentation on the GNU name system. GNS is a replacement for DNS whose naming structure mirrors our social naming structure. For example, www.alice.gnu would be my friend Alice, and www.alice.bob.gnu would be Alice's friend Bob. With some integration, it can work on normal desktops and mobile devices. There are lots more details, so check for more information.

Of course, a new naming system does need some operating system support. In this regard Ludovic Courtès' update on Guix was particularly impressive. Guix is a Nix-like system whose goal is reproducible, user-controlled GNU/Linux systems. A couple years ago I didn't think much of it, but now it's actually booting on raw hardware, not just under virtualization, and things seem to be rolling forth as if on rails. Guix manages to be technically innovative at the same time as being GNU-centered, so it can play a unique role in propagating GNU work like GNS.

and yet.

But now, as the dark clouds race above and the light truly goes, we arrive to the point I really wanted to discuss. GNU has a terrible problem with gender balance, and with diversity in general. Of about 70 attendees at this recent GHM, only two were women. We talk the talk about empowering users and working for freedom but, to a first approximation, it's really just a bunch of dudes that think the exact same things.

There are many reasons for this, of course. Some people like to focus on what's called the "pipeline problem" -- that there aren't as many women coming out of computer science programs as men. While true, the proportion of women CS graduates is much higher than the proportion of women at GHM events, so something must be happening in between. And indeed, the attrition rates of women in the tech industry are higher than that of men -- often because we men make it a needlessly unpleasant place for women to be. Sometimes it's even dangerous. The incidence of sexual harassment and assault in tech, especially at events, is something terrible. Scroll down in that linked page to June, July, and August 2014, and ask yourself whether that's OK. (Hint: hell no.)

And so you would think that people who consider themselves to be working for some abstract liberatory principle, as GNU is, would be happy to take a stand against this kind of asshaberdashery. There you would be wrong. Voilà a timeline of an incident.


March 2014
Someone at the FSF asks a GHM organizer to add an anti-harassment policy to GHM. The organizer does so and puts one on the web page, copying the text from Libreplanet's web site. The policy posted is:

Offensive or overly explicit sexual language or imagery is inappropriate during the event, including presentations.

Participants violating these rules may be sanctioned or expelled from the meeting at the discretion of the organizers.

Harassment includes offensive comments related to gender, sexual orientation, disability, appearance, body size, race, religion, sexual images in public spaces, deliberate intimidation, stalking, harassing photography or recording, persistent disruption of talks or other events, repeated unsolicited physical contact, or sexual attention.

Monday, 11 August 2014
The first mention of the policy is made on the mailing list, in a mail with details about the event that also includes the line:

An anti-harrasment policy applies at GHM:

Monday, 11 August 2014
A speaker writes the list to say:

Since I do not desire to be denounced, prosecuted and finally sanctioned or expelled from the event (especially considering the physical pain and inconvenience of attending due to my very recent accident) I withdraw my intention to lecture "Introducing GNU Posh" at the GHM, as it is not compliant with the policy described in the page above.

Please remove the talk from the official schedule. Thanks.

PS: for those interested, I may perform the talk off-event in case we find a suitable place, we will see..

The resulting thread goes totes clownshoes and rages on up until the event itself.
Friday, 15 August 2014
Sheepish looks between people that flamed each other over the internet. Hallway-track discussion starts up quickly though. Disagreeing people are not rational enough to have a conversation though (myself included).
Saturday, 16 August 2014
In the morning and lunch break, people start to really discuss the issues (spontaneously). It turns out that the original mail that sparked the thread was based, to an extent, on a misunderstanding: that "offensive or overly explicit sexual language or imagery" was parsed (by a few non-native English speakers) as "offensive language or ...", which people thought was too broad. Once this misunderstanding was removed, there were still people that thought that any policy at all was unneeded, and others that were concerned that someone could say something without intending offense, but then be kicked out of the event. Arguments back and forth. Some people wonder why others can be hurt by "just words". Some discussion of rape culture as continuum between physical violence and cultural tropes. One of the presentations after lunch is by a GNU hacker. He starts his talk by stating his hope that he won't be seen as "offensive or part of rape culture or something". His microphone wasn't on, so once he gets it on he repeats the joke. I stomp out, slam the door, and tweet a few angry things. Later in the evening the presenter and I discuss the issue. He apologizes to me.
Sunday, 17 August 2014
A closed meeting for GNU maintainers to round up the state of GNU and GHM. No women present. After dealing with a number of banalities, we finally broach the topic of the harassment policy. More opposition to the policy Sunday than Saturday lunch. Eventually a proposal is made to replace "offensive" with "disparaging", and people start to consent to that. We run out of time and have to leave; resolution unclear.
Monday, 18 August 2014
GHM organizer updates the policy to remove the words "offensive or" from the beginning of the harassment policy.

I think anyone involved would agree on this timeline.


The problems seen over the last week with this anti-harassment policy are entirely to do with the men. It was a man who decided that he should withdraw his presentation because he found it offensive that he could be perceived as offensive. It was men who willfully misread the policy, comparing it to such examples as "I should have the right to offend Microsoft supporters", "if I say the wrong word I will go to jail", and who raised the ignorant, vacuous spectre of "political correctness" to argue that they should be able to say what they want, in a GNU conference, no matter who they hurt, no matter what the effects. That they are able to argue this position from a status-quo perspective is the definition of privilege.

Now, there is ignorance, and there is malice. Both must be opposed, but the former may find a cure. Although I didn't begin my contribution to the discussion in the smoothest way, linking to a an amusing article on the alchemy of intent that is probably misunderstood, it ended up that one of the main points was about intent. I know Ralph (say) and Ralph is a great person and so how could it be that anything Ralph would say could be a slur? You know he wouldn't mean it like that!

To that, we of course have to say that as GNU grows, not everyone knows that Ralph is a great person. In the end what would it mean for someone to be anti-racist but who says racist things all the time? You would have to call them racist, right? Or if you just said something one time, but refused to own up to your error, and instead persisted in repeating a really racist slur -- you would be racist right? But I know you... But the thing that you said...

But then to be honest I wonder sometimes. If someone repeats a joke trivializing rape culture, after making sure that the microphone is picking up his words -- I mean, that's a misogynist action, right? Put aside the question of whether the person is, in essence, misogynist or not. They are doing misogynist things. How do I know that this person isn't going to do it again, private apology or not?

And how do I know that this community isn't going to permit it again? That remark was made to a room of 40 dudes or so. Not one woman was present. Although there was some discussion afterwards, if people left because of the phrase, it was only two or three. How can we then say that GNU is not a misogynist community -- is not a community that tolerates misogyny?

Given all of this, what do you expect? Do you expect to grow GNU into a larger organization in the future, rich and strong and diverse? If that's not your goal, you are not my colleague. And if it is your goal, why do you put up with this kind of behavior?

The discussion on intent and offense seems to have had its effect in the removal of "offensive or" from the anti-harassment policy language. I think it's terrible, though -- if you don't trust someone who says they were offended by sexual language or imagery, why would you trust them when they report sexual harassment or assault? I can only imagine this leading to some sort of argument where the person who has had the courage to report such an incident finds himself or herself in a public witness box, justifying that the incident was offensive. "I'm sorry my words offended you, but that was not my intent, and anyway the words were not offensive." Lolnope.

There were so many other wrong things about this -- a suggestion that we the GNU cabal (lamentably, a bunch of dudes) should form a committee to make the wording less threatening to us; that we're just friends anyway; that illegal things are illegal anyway... it's as if the Code of Conduct FAQ that Ashe Dryden assembled were a Bingo card and we all lost.

Finally I don't think I trusted the organizers enough with this policy. Both organizers expressed skepticism about the policy in such terms that if I personally hadn't won the privilege lottery (white male "western" hetero already-established GNU maintainer) I wouldn't feel comfortable bringing up a concern to them.

In the future I will not be attending any conferences without strong, consciously applied codes of conduct, and I enjoin you to do the same.


Propagandhi, "Refusing to Be a Man", Less Talk, More Rock (1996)

There is no conclusion yet -- working for the better world we all know is possible is a process, as people and as a community.

To outsiders, to outsiders everywhere, please keep up the vocal criticisms. Thank you for telling your story.

To insiders, to insiders everywhere, this is your problem. The problem is you. Own it.

by Andy Wingo at August 18, 2014 09:07 PM