Hugs contains support for debugging by observations inspired by the Andy Gill's Hood library:
Andy Gill, Debugging Haskell by Observing Intermediate Data Structures, in Draft Proceedings of the 2000 Haskell Workshop.
The Haskell Object Observation Debugger http://www.haskell.org/hood/.
Hood is a portable Haskell library that implements the combinator
observe :: Observable a => String -> a -> a
The partial application
observe tag
behaves exactly like the identity function, but also records the value
of data to which it is applied.
Any observations made are reported at the end of the computation.
The tag
argument is used to label the
observed value when it is reported. Non-strict semantics is preserved
— observe
does not evaluate its second argument.
HugsHood uses the same observation model but differs in a number of ways.
It is much faster. This is because HugsHood is implemented within the Hugs evaluator and uses primitive builtin functions. Performance depends upon the volume of observations. More frequent observations incur a higher overhead. As a simple comparison, a test program which executed 1 million reductions and made 250 observations incurred a 625 percent overhead when observations were made with the Hood library but just 10 percent when using HugsHood.
Caveat: When not using observations, the modifications to the evaluator to support HugsHood imposes an overhead of about 6 percent.
It is possible to easily observe arbitrary data structures. HugsHood implements the primitive
observe :: String -> a -> a
which is unconstrained by the need to build instances of the
Observable
class for each user defined data type
whose values are being observed.
HugsHood uses an internal primitive function to display observed values.
This may be considered both an advantage and a disadvantage:
one does not need to define how to observe values,
but one cannot define special user views of data.
No modification to the program (apart from instrumentation with
observe
) is required.
The Hood library must be invoked using a special IO monadic combinator
to ensure that observations are collected and displayed.
There are a number of minor differences in the display format which are a consequence of the Hugs implementation. These are described below.
Modules that use HugsHood combinators must import the module
Hugs.Observe
.
Its only role is to provide the necessary primitive definitions, namely:
primitive observe :: String -> a -> a primitive bkpt :: String -> a -> a primitive setBkpt :: String -> Bool -> IO ()
HugsHood implements breakpoints. A program can be instrumented with the
bkpt
function. The partial application
bkpt bkpt_name
behaves exactly like the identity function, except that before it
returns its argument it checks if bkpt_name
is enabled, and if it is the user is presented with the opportunity to
view observed data.
A small set of commands is available when Hugs halts due to a breakpoint:
p
[tag_name
]
Print observations made since the computation began. If an observation tag is suppled then only the associated observations will be displayed. Otherwise all observations will be displayed.
c
[n
]
Continue with program evaluation. With no arguments,
evaluation will continue until another active breakpoint
is encountered. The optional numeric argument will skip
n
active breakpoints before stopping.
s
bkpt_name
Set a breakpoint.
r
[bkpt_name
]
Reset a named breakpoint or, if no breakpoint name is supplied, reset all breakpoints.
A breakpoint is by default disabled. It can be enabled by using the
s command in the debug breakpoint dialogue,
or by using the setBkpt
combinator.
Clearly at least one breakpoint must be enabled using
setBkpt
before a breakpoint dialogue can be triggered.
Here is a very simple program using the three combinators.
import Hugs.Observe prog n = do { setBkpt "fib" True; putStr $ show (observe "fun" f n) } f 0 = 1 f n = n * (bkpt "fib" $ observe "fun" f (n-1))
The following sample session shows how the p and c commands can be used.
Main> prog 4 Break @ fib> p >>>>>>> Observations <<<<<< fun { \ 4 -> _ } Break @ fib> c Break @ fib> p >>>>>>> Observations <<<<<< fun { \ 4 -> _ , \ 3 -> _ } Break @ fib> c 2 Break @ fib> p >>>>>>> Observations <<<<<< fun { \ 4 -> _ , \ 3 -> _ , \ 2 -> _ , \ 1 -> _ } Break @ fib> c 24 (98 reductions, 299 cells) >>>>>>> Observations <<<<<< fun { \ 4 -> 24 , \ 3 -> 6 , \ 2 -> 2 , \ 1 -> 1 , \ 0 -> 1 } 10 observations recorded
HugsHood uses a similar style of display to Hood, though there are
differences. One trivial difference is that Hood reports tags with a
leading “--
” while HugsHood does not.
Consider now more significant differences.
HugsHood (and Hood) reports lists using the cons operator.
Observe> observe "list" [1..3] [1,2,3] >>>>>>> Observations <<<<<< list (1 : 2 : 3 : [])
This is too verbose for lists of characters, so HugsHood reports strings in the usual format:
Observe> observe "string" ['a'..'d'] "abcd" >>>>>>> Observations <<<<<< string "abcd"
If only the initial part of the string is evaluated,
a trailing “...
” is reported.
Observe> take 2 $ observe "string" ['a'..'d'] "ab" >>>>>>> Observations <<<<<< string "ab..."
This is clearly ambiguous, because evaluating the expression
observe "string" "ab..."
will give the same result, but in practice the ambiguity should be easy to resolve.
The “_
” symbol is used to indicate
an unevaluated expression.
In Hood all unevaluated expressions will be displayed using
“_
”.
In HugsHood, “_
” denotes an unevaluated
expression, but not all unevaluated expressions are denoted
by “_
”.
For example the expression fst $ observe "pair" (1,2)
yields
-- pair (1, _)
in both Hugs and HugsHood.
However, fst $ observe "pair" ('a','b')
yields
pair ('a','b')
in HugsHood, and ('a', _)
in Hood.
This is because HugsHood (unlike
Hood) does not actually record evaluation steps. It merely maintains an
internal pointer to that part of the heap representing the tagged
expression. If the expression in not in weak head normal form, then it
obviously has not been evaluated and so it is reported as just
“_
”;
otherwise it displayed. Integer constants like 1
and
2
are not in WHNF,
as they must be coerced to the correct type when evaluated.
Characters though are in WHNF so it is not possible to discern whether
a character was evaluated.
Another consequence of the HugsHood implementation by pointers rather than Hood's implementation by tracing evaluation is that the strictness behaviour of a function can be masked. Consider the example:
lazy pair = let x = observe "fst" fst pair y = snd pair in (y,x)
For the expression lazy (1,2)
Hood reports
-- fst { \ (1, _) -> 1 }
while HugsHood reports
fst { \ (1,2) -> 1 }
HugsHood should not be used to deduce the strictness behaviour of a function, or it should be done only with caution.
The Hugs compiler uses an optimisation when generating code that builds expressions on the heap. If a function definition has the form
f arg1 .. argN = ..... f arg1 .. argM .....
where 1 ≤ M
≤ N
,
then the expression graph for f arg1 .. argM
is copied rather than rebuilt from individual application nodes.
This interacts with the observation algorithm so that observing functions
of the above form gives unexpected results.
For instance consider the expression
observe "fold" foldl (+) 0 [1..3]
When the root optimisation is applied to the compilation
of foldl
, we see
fold { \ primPlusInteger 6 [] -> 6 , \ { \ 3 3 -> 6 } 3 (3 : []) -> 6 , \ { \ 1 2 -> 3 } 1 (2 : 3 : []) -> 6 , \ { \ 0 1 -> 1 } 0 (1 : 2 : 3 : []) -> 6
instead of the expected
fold { \ { \ 0 1 -> 1 , \ 1 2 -> 3 , \ 3 3 -> 6 } 0 (1 : 2 : 3 : []) -> 6 }
The first form reports the arguments at each application
of foldl
,
while the second reports the arguments for just the initial application
(the one marked by observe
).
The root optimisation can be disabled using the
-R
option.
This can be done from the command line or by using
:s -R
at the Hugs prompt.
If you want to compile the prelude definitions without the root optimisation
you must invoke Hugs with the -R
option.
Testing of execution time with and without the root optimisation for a selection of 23 benchmarks from the nofib suite has been carried out. All but 5 tests resulted in an execution time penalty of less than 3% when running without root optimisation (some even showed a very minor speedup).
Please report bugs to Richard Watson, <rwatson@usq.edu.au>
In particular, if the message
Warning: observation sanity counter > 0
appears, and your program has not terminated abnormally, please report the error situation.