Slicing Functional Programs: A Suspicion 10th CREST Open Workshop - - PowerPoint PPT Presentation

Slicing Functional Programs: A Suspicion

10th CREST Open Workshop on Program Analysis and Slicing

Henrik Nilsson School of Computer Science The University of Nottingham, UK

Slicing Functional Programs: A Suspicion – p.1/6

Slicing Functional Programs?

• scSine 3.0
• scSine f

*0.2

• 0.25

+1.0

+

sciFi :: SF () Sample sciFi = proc () → do und ← arr (∗0.2) ≪ oscSine 3.0− ≺ 0 swp ← arr (+1.0) ≪ integral − ≺ −0.25 audio ← oscSine 440 − ≺ und + swp returnA− ≺ audio

Slicing Functional Programs: A Suspicion – p.2/6

Behind the Scenes

A signal function (SF) is roughly represented as: data SF a b = SF (DTime → a → (b, SF a b))

Slicing Functional Programs: A Suspicion – p.3/6

Behind the Scenes

A signal function (SF) is roughly represented as: data SF a b = SF (DTime → a → (b, SF a b))

• Top level loop repeatedly apply the system SF

to input, computing output at that point in time and next system SF .

Slicing Functional Programs: A Suspicion – p.3/6

Behind the Scenes

A signal function (SF) is roughly represented as: data SF a b = SF (DTime → a → (b, SF a b))

• Top level loop repeatedly apply the system SF

to input, computing output at that point in time and next system SF .

• Output depends on the entire SF computed

at the previous step.

Slicing Functional Programs: A Suspicion – p.3/6

Behind the Scenes

A signal function (SF) is roughly represented as: data SF a b = SF (DTime → a → (b, SF a b))

• Top level loop repeatedly apply the system SF

to input, computing output at that point in time and next system SF .

• Output depends on the entire SF computed

at the previous step. Arguably a somewhat flamboyant (even frivolous?) style of programming!

Slicing Functional Programs: A Suspicion – p.3/6

A Suspicion

Slicing Functional Programs: A Suspicion – p.4/6

A Suspicion Style matters!

Slicing Functional Programs: A Suspicion – p.4/6

Higher-order Abstractions

Higher-order abstractions are a staple of modern functional programming:

• Monads
• Arrows
• Applicative functors
• Continuation Passing Style (CPS)
• . . .

Slicing Functional Programs: A Suspicion – p.5/6

Higher-order Abstractions

Higher-order abstractions are a staple of modern functional programming:

• Monads
• Arrows
• Applicative functors
• Continuation Passing Style (CPS)
• . . .

Flamboyance to be expected!

Slicing Functional Programs: A Suspicion – p.5/6

Accounting for Style

Lost cause?

Slicing Functional Programs: A Suspicion – p.6/6

Accounting for Style

Lost cause? Maybe not: these abstractions:

• are principled
• satisfy useful mathematical laws
• capture simple ideas

Ought to be possible to exploit!

Slicing Functional Programs: A Suspicion – p.6/6

Accounting for Style

Lost cause? Maybe not: these abstractions:

• are principled
• satisfy useful mathematical laws
• capture simple ideas

Ought to be possible to exploit! Perhaps we need Stylish Slicing: extensible slicing tools capable of slicing with style!

Slicing Functional Programs: A Suspicion – p.6/6