Download Tools for Refactoring Functional Programs

Tools for Refactoring
Functional Programs
Simon Thompson
with
Huiqing Li
Claus Reinke
www.cs.kent.ac.uk/projects/refactor-fp
Design
Models
Prototypes
Design documents
Visible artifacts
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All in the code …
Functional programs
embody their design in
their code.
This is enabled by their
high-level nature:
constructs, types …
data Message
= Message Head Body
data Head
= Head Metadata Title
data Metadata
= Metadata [Tags]
type Title = String
…
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Evolution
Successful systems are
long lived …
… and evolve
continuously.
Supporting evolution
of code and design?
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Soft-Ware
There’s no single
correct design …
… different options for
different situations.
Maintain flexibility as
the system evolves.
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Refactoring
Refactoring means changing the design or
structure of a program … without changing
its behaviour.
Modify
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Refactor
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Not just programming
Paper or presentation
moving sections about; amalgamate sections; move
inline code to a figure; animation; …
Proof
add lemma; remove, amalgamate hypotheses, …
Program
the topic of the lecture
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Splitting a function in two
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Splitting a function in two
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Splitting a function in two
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Splitting a function
module Split where
f :: [String] -> String
f ys = foldr (++) [] [ y++"\n" | y <- ys ]
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Splitting a function
module Split where
f :: [String] -> String
f ys = foldr (++) [] [ y++"\n" | y <- ys ]
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Splitting a function
module Split where
f :: [String] -> String
f ys = join [y ++ "\n" | y <- ys]
where
join = foldr (++) []
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Splitting a function
module Split where
f :: [String] -> String
f ys = join [y ++ "\n" | y <- ys]
where
join = foldr (++) []
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Splitting a function
module Split where
f :: [String] -> String
f ys = join addNL
where
join zs = foldr (++) [] zs
addNL = [y ++ "\n" | y <- ys]
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Splitting a function
module Split where
f :: [String] -> String
f ys = join addNL
where
join zs = foldr (++) [] zs
addNL = [y ++ "\n" | y <- ys]
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Splitting a function
module Split where
f :: [String] -> String
f ys = join (addNL ys)
where
join zs = foldr (++) [] zs
addNL ys = [y ++ "\n" | y <- ys]
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Splitting a function
module Split where
f :: [String] -> String
f ys = join (addNL ys)
where
join zs = foldr (++) [] zs
addNL ys = [y ++ "\n" | y <- ys]
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Splitting a function
module Split where
f :: [String] -> String
f ys = join (addNL ys)
join zs = foldr (++) [] zs
addNL ys = [y ++ "\n" | y <- ys]
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Overview
Example refactorings: what they involve.
Building the HaRe tool.
Design rationale.
Infrastructure.
Haskell and Erlang.
The Wrangler tool.
Conclusions.
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Haskell 98
Standard, lazy, strongly typed, functional
programming language.
Layout is significant … “offside rule” … and
idiosyncratic. doSwap pnt = applyTP (full_buTP (idTP `adhocTP` inMatch
`adhocTP` inExp
`adhocTP` inDecl))
where
inMatch ((HsMatch loc fun pats rhs ds)::HsMatchP)
| fun == pnt
= case pats of
(p1:p2:ps) -> do pats'<-swap p1 p2 pats
return (HsMatch loc fun pats' rhs ds)
_
-> error "Insufficient arguments to swap."
inMatch m = return m
inExp exp@((Exp (HsApp (Exp (HsApp e e1)) e2))::HsExpP)
| expToPNT e == pnt = swap e1 e2 exp
inExp e = return e
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Why refactor Haskell?
The only design artefact is (in) the code.
Semantics of functional languages support largescale transformations (?)
Building real tools to support functional
programming … heavy lifting.
Platform for research and experimentation.
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Lift / demote
fxy=…h…
where
h=…

f x y = … (h y) …
hy=…

Hide a function which is
Makes h accessible to the
clearly subsidiary to f;
other functions in the
clear up the
module and beyond.
namespace.
Free variables: which parameters of f are used in h?
Need h not to be defined at the top level, … ,
Type of h will generally change … .
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Algebraic or abstract type?
data Tr a
flatten :: Tr a -> [a]
= Leaf a |
Node a (Tr a) (Tr a)
Tr
Leaf
Node
flatten (Leaf x) = [x]
flatten (Node s t)
= flatten s ++
flatten t
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Algebraic or abstract type?
Tr
data Tr a
= Leaf a |
Node a (Tr a) (Tr a)
isLeaf = …
isNode = …
…
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isLeaf
flatten :: Tr a -> [a]
isNode
leaf
left
right
mkLeaf
mkNode
flatten t
| isleaf t = [leaf t]
| isNode t
= flatten (left t)
++ flatten (right t)
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Information required
Lexical structure of programs,
abstract syntax,
binding structure,
type system and
module system.
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Program transformations
Program optimisation source-to-source transformations
to get more efficient code
Program derivation calculating efficient code from
obviously correct specifications
Refactoring transforming code structure usually
bidirectional and conditional.
Refactoring = Transformation + Condition
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Conditions: renaming f to g
“No change to the binding structure”
1.
2.
3.
No two definitions of g at the same level.
No capture of g.
No capture by g.
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Capture of renamed identifier
hx=…h…f…g…
where
gy=…
hx=…h…g…g…
where
gy=…
fx=…
gx=…
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Capture by renamed identifier
hx=…h…f…g…
where
fy=…f…g…
hx=…h…g…g…
where
gy=…g…g…
gx=…
gx=…
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Refactoring by hand?
By hand = in a text editor
Tedious
Error-prone
• Implementing the transformation …
• … and the conditions.
Depends on compiler for type checking, …
… plus extensive testing.
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Machine support invaluable
Reliable
Low cost of do / undo,
even for large
refactorings.
Increased effectiveness
and creativity.
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Demonstration of HaRe, hosted in vim.
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The refactorings in HaRe
Move def between modules
Rename
Delete/add to exports
Delete
Clean imports
Lift / Demote
Make imports explicit
Introduce definition
Remove definition
data type to ADT
Unfold
Short-cut, warm fusion
Generalise
All module aware
Add/remove parameters
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HaRe design rationale
Integrate with existing development tools.
Work with the complete language: Haskell 98
Preserve comments and the formatting style.
Reuse existing libraries and systems.
Extensibility and scriptability.
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Information required
Lexical structure of programs,
abstract syntax,
binding structure,
type system and
module system.
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The Implementation of HaRe
Information
gathering
Pre-condition
checking
Program
transformation
Strafunski
Program
rendering
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Finding free variables ‘by hand’
instance FreeVbls HsExp where
freeVbls (HsVar v) = [v]
freeVbls (HsApp f e)
= freeVbls f ++ freeVbls e
freeVbls (HsLambda ps e)
= freeVbls e \\ concatMap paramNames ps
freeVbls (HsCase exp cases)
= freeVbls exp ++ concatMap freeVbls cases
freeVbls (HsTuple _ es)
= concatMap freeVbls es …
Boilerplate code: 1000 noise : 100 significant.
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Strafunski
Strafunski allows a user to write general (read
generic), type safe, tree traversing programs, with
ad hoc behaviour at particular points.
Top-down / bottom up, type preserving / unifying,
full
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stop
one
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Strafunski in use
Traverse the tree accumulating free variables from
components, except in the case of lambda
abstraction, local scopes, …
Strafunski allows us to work within Haskell …
Other options? Generic Haskell, Template Haskell,
AG, Scrap Your Boilerplate, …
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Rename an identifier
rename:: (Term t)=>PName->HsName->t->Maybe t
rename oldName newName = applyTP worker
where
worker = full_tdTP (idTP ‘adhocTP‘ idSite)
idSite :: PName -> Maybe PName
idSite v@(PN name orig)
| v == oldName
= return (PN newName orig)
idSite pn = return pn
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The coding effort
Transformations: straightforward in Strafunski …
… the chore is implementing conditions that the
transformation preserves meaning.
This is where much of our code lies.
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Program rendering example
-- This is an example
-- This is an example
module Main where
module Main where
sumSquares x y = sq x + sq y
where sq :: Int->Int
sq x = x ^ pow
pow = 2 :: Int
sumSquares x y = sq pow x + sq pow y
where pow = 2 :: Int
main = sumSquares 10 20
sq :: Int->Int->Int
sq pow x = x ^ pow
main = sumSquares 10 20
module Main where
sumSquares x y
= sq pow x + sq pow y where pow = 2 :: Int
sq :: Int->Int->Int
sq pow x = x ^ pow
main = sumSquares 10 20
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Token stream and AST
White space + comments only in token stream.
Modification of the AST guides the modification of
the token stream.
After a refactoring, the program source is recovered
from the token stream not the AST.
Heuristics associate comments with program
entities.
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Work in progress
‘Fold’ against definitions … find duplicate code.
All, some or one? Effect on the interface …
fx=…e…e…
Symbolic evaluation
Data refactorings
Interfaces … ‘bad smell’ detection.
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API and DSL
Combining forms
???
Refactorings
Refactoring
utilities
Strafunski
Library functions
Grammar as data
Strafunski
Haskell
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What have we learned?
Efficiency and robustness of libraries in question.
• type checking large systems,
• linking,
• editor script languages (vim, emacs).
The cost of infrastructure in building practical
tools.
Reflections on Haskell itself.
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Reflections on Haskell
Cannot hide items in an export list (cf import).
Field names for prelude types?
Scoped class instances not supported.
‘Ambiguity’ vs. name clash.
‘Tab’ is a nightmare!
Correspondence principle fails …
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Correspondence
Operations on definitions and operations on
expressions can be placed in one to one
correspondence
(R.D.Tennent, 1980)
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Correspondence
Definitions
Expressions
where
let
fxy=e
\x y -> e
fx
| g1 = e1
| g2 = e2
f x = if g1 then e1
g2 … …
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else if
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Function clauses
fx
| g1 = e1
f x = if g1 then e1
g2 …
else if
fx
| g2 = e2
Can ‘fall through’ a function
clause … no direct
correspondence in the
expression language.
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No clauses for anonymous
functions … no reason to
omit them.
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Haskell 98 vs. Erlang: generalities
Haskell 98: a lazy,
statically typed, purely
functional programming
language featuring
higher-order functions,
polymorphism, type
classes and monadic
effects.
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Erlang: a strict,
dynamically typed
functional programming
language with support
for concurrency,
communication,
distribution and faulttolerance.
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Haskell 98 vs. Erlang: example
-- Factorial In Haskell.
module Fact(fac) where
fac :: Int -> Int
fac 0 = 1
fac n | n>0 = n * fac(n-1)
%% Factorial In Erlang.
-module (fact).
-export ([fac/1]).
fac(0) -> 1;
fac(N) when N > 0 -> N * fac(N-1).
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Haskell 98 vs. Erlang: pragmatics

Type system makes
implementation complex.
 Layout and comment
preservation.
 Types also affect the
refactorings themselves.

Clearer semantics for
refactorings, but more
complex infrastructure.
Dynamic semantics of
Erlang makes refactorings
harder to pin down.
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Untyped traversals much
simpler.
 Use the layout given by
emacs.
 Use cases which cannot be
understood statically.
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Challenges of Erlang refactoring


Multiple binding occurrences of variables.
Indirect function call or function spawn:
apply (lists, rev, [[a,b,c]])




Multiple arities … multiple functions: rev/1
Concurrency
Refactoring within a design library: OTP.
Side-effects.
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Generalisation and side-effects
-module (test).
-module (test).
-export([f/0]).
-export([f/0]).
repeat(0) -> ok;
repeat(N) ->
io:format (“hello\n"),
repeat(N-1).
repeat(A, 0) -> ok;
repeat(A, N) ->
A,
repeat(A,N-1).
f( ) -> repeat(5).
f( ) -> repeat (io:format (“hello\n”), 5).
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Generalisation and side-effects
-module (test).
-module (test).
-export([f/0]).
-export([f/0]).
repeat(0) -> ok;
repeat(N) ->
io:format (“hello\n"),
repeat(N-1).
repeat(A, 0) -> ok;
repeat(A, N) ->
A(),
repeat(A,N-1).
f( ) -> repeat(5).
f( ) -> repeat (fun( )->
io:format (“hello\n”), 5).
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The Wrangler
Program source
Scanner/Parser
Parse Tree
Syntax tools
AST annotated with comments
Refactorer
AST + comments + binding structure
Program analysis and transformation
by the refactorer
Transformed AST
Pretty printer
Program source
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Teaching and learning design
Exciting prospect of using a refactoring tool as an
integral part of an elementary programming
course.
Learning a language: learn how you could modify
the programs that you have written …
… appreciate the design space, and
… the features of the language.
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Conclusions
Refactoring + functional programming: good fit.
Real win from available libraries … with work.
Substantial effort in infrastructure.
De facto vs de jure: GHC vs Haskell 98.
Correctness and verification …
Language independence …
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