t a i l r e c u r s i o n n o t o n e x a m h o w i s r e
play

T a i l r e c u r s i o n ( n o t o n e x a m - PowerPoint PPT Presentation

Sep 12, 2022 •497 likes •954 views

T a i l r e c u r s i o n ( n o t o n e x a m ) H o w i s r e c u r s i o n i m p l e m e n t e d ? Wh e n y o u c a l l f u n c t i o n B f r o m f u n c t i o n A ,

  1. T a i l r e c u r s i o n ( n o t o n e x a m )

  2. H o w i s r e c u r s i o n i m p l e m e n t e d ? Wh e n y o u c a l l f u n c t i o n B f r o m f u n c t i o n A , t h e p r o c e s s o r s t o p s e x e c u t i n g A a n d s t a r t s e x e c u t i n g B ( o b v i o u s l y ) B u t w h e n B r e t u r n s , h o w d o e s i t k n o w h o w t o g o b a c k t o A ? A n s w e r : t h e c a l l s t a c k ● B e f o r e A c a l l s B , i t w i l l p u s h a r e c o r d o f w h a t i t w a s d o i n g : t h e n e x t i n s t r u c t i o n t o b e e x e c u t e d , p l u s t h e v a l u e s o f a l l l o c a l v a r i a b l e s ● Wh e n B r e t u r n s , i t w i l l p o p t h a t r e c o r d a n d s e e i t s h o u l d r e t u r n t o A

  3. A r e c u r s i v e f u n c t i o n N e x t V a l u e 1 v o i d r e c ( i n t n ) { l i n e o f n 2 i f ( n > 0 ) { 3 S y s t e m . o u t . p r i n t l n ( n ) ; 4 r e c ( n - 1 ) ; 5 r e c ( n - 1 ) ; 6 } 7 } r e c ( 3 ) ; n = 3

  4. A r e c u r s i v e f u n c t i o n N e x t V a l u e 1 v o i d r e c ( i n t n ) { l i n e o f n 2 i f ( n > 0 ) { 3 S y s t e m . o u t . p r i n t l n ( n ) ; 4 r e c ( n - 1 ) ; 5 r e c ( n - 1 ) ; 6 } 7 } r e c ( 3 ) ; n = 3

  5. A r e c u r s i v e f u n c t i o n N e x t V a l u e 1 v o i d r e c ( i n t n ) { l i n e o f n 2 i f ( n > 0 ) { 3 S y s t e m . o u t . p r i n t l n ( n ) ; 4 r e c ( n - 1 ) ; 5 r e c ( n - 1 ) ; 6 } 7 } r e c ( 3 ) ; n = 3 P r i n t s 3 P r i n t e d : 3

  6. A r e c u r s i v e f u n c t i o n N e x t V a l u e 1 v o i d r e c ( i n t n ) { l i n e o f n 2 i f ( n > 0 ) { 3 S y s t e m . o u t . p r i n t l n ( n ) ; 4 r e c ( n - 1 ) ; 5 r e c ( n - 1 ) ; 6 } 7 } r e c ( 3 ) ; n = 3 P u s h s t a t e o n t o c a l l s t a c k P r i n t e d : 3

  7. A r e c u r s i v e f u n c t i o n N e x t V a l u e 1 v o i d r e c ( i n t n ) { l i n e o f n 2 i f ( n > 0 ) { 3 S y s t e m . o u t . p r i n t l n ( n ) ; 5 3 4 r e c ( n - 1 ) ; 5 r e c ( n - 1 ) ; 6 } 7 } r e c ( 3 ) ; n = 2 P r i n t e d : 3

  8. A r e c u r s i v e f u n c t i o n N e x t V a l u e 1 v o i d r e c ( i n t n ) { l i n e o f n 2 i f ( n > 0 ) { 3 S y s t e m . o u t . p r i n t l n ( n ) ; 5 3 4 r e c ( n - 1 ) ; 5 r e c ( n - 1 ) ; 6 } 7 } r e c ( 3 ) ; n = 2 P r i n t s 2 P r i n t e d : 3 2

  9. A r e c u r s i v e f u n c t i o n N e x t V a l u e 1 v o i d r e c ( i n t n ) { l i n e o f n 2 i f ( n > 0 ) { 3 S y s t e m . o u t . p r i n t l n ( n ) ; 5 3 4 r e c ( n - 1 ) ; 5 r e c ( n - 1 ) ; 6 } 7 } r e c ( 3 ) ; n = 2 P u s h s t a t e o n t o c a l l s t a c k P r i n t e d : 3 2

  10. A r e c u r s i v e f u n c t i o n N e x t V a l u e 1 v o i d r e c ( i n t n ) { l i n e o f n 2 i f ( n > 0 ) { 3 S y s t e m . o u t . p r i n t l n ( n ) ; 5 3 4 r e c ( n - 1 ) ; 5 2 5 r e c ( n - 1 ) ; 6 } 7 } r e c ( 3 ) ; n = 1 P r i n t e d : 3 2

  11. A r e c u r s i v e f u n c t i o n N e x t V a l u e 1 v o i d r e c ( i n t n ) { l i n e o f n 2 i f ( n > 0 ) { 3 S y s t e m . o u t . p r i n t l n ( n ) ; 5 3 4 r e c ( n - 1 ) ; 5 2 5 r e c ( n - 1 ) ; 6 } 7 } r e c ( 3 ) ; n = 1 P r i n t s 1 P r i n t e d : 3 2 1

  12. A r e c u r s i v e f u n c t i o n N e x t V a l u e 1 v o i d r e c ( i n t n ) { l i n e o f n 2 i f ( n > 0 ) { 3 S y s t e m . o u t . p r i n t l n ( n ) ; 5 3 4 r e c ( n - 1 ) ; 5 2 5 r e c ( n - 1 ) ; 6 } 7 } r e c ( 3 ) ; n = 1 P u s h s t a t e o n t o P r i n t e d : 3 2 1 c a l l s t a c k

  13. A r e c u r s i v e f u n c t i o n N e x t V a l u e 1 v o i d r e c ( i n t n ) { l i n e o f n 2 i f ( n > 0 ) { 3 S y s t e m . o u t . p r i n t l n ( n ) ; 5 3 4 r e c ( n - 1 ) ; 5 2 5 r e c ( n - 1 ) ; 6 } 1 5 7 } r e c ( 3 ) ; n = 0 P r i n t e d : 3 2 1

  14. A r e c u r s i v e f u n c t i o n N e x t V a l u e 1 v o i d r e c ( i n t n ) { l i n e o f n 2 i f ( n > 0 ) { 3 S y s t e m . o u t . p r i n t l n ( n ) ; 5 3 4 r e c ( n - 1 ) ; 5 2 5 r e c ( n - 1 ) ; 6 } 5 1 7 } r e c ( 3 ) ; n = 0 P o p s t a t e f r o m P r i n t e d : 3 2 1 c a l l s t a c k

  15. A r e c u r s i v e f u n c t i o n N e x t V a l u e 1 v o i d r e c ( i n t n ) { l i n e o f n 2 i f ( n > 0 ) { 3 S y s t e m . o u t . p r i n t l n ( n ) ; 5 3 4 r e c ( n - 1 ) ; 5 2 5 r e c ( n - 1 ) ; 6 } 7 } r e c ( 3 ) ; n = 1 P u s h s t a t e o n t o c a l l s t a c k P r i n t e d : 3 2 1

  16. A r e c u r s i v e f u n c t i o n N e x t V a l u e 1 v o i d r e c ( i n t n ) { l i n e o f n 2 i f ( n > 0 ) { 3 S y s t e m . o u t . p r i n t l n ( n ) ; 5 3 4 r e c ( n - 1 ) ; 5 2 5 r e c ( n - 1 ) ; 6 } 6 1 7 } r e c ( 3 ) ; n = 0 P r i n t e d : 3 2 1

  17. A r e c u r s i v e f u n c t i o n N e x t V a l u e 1 v o i d r e c ( i n t n ) { l i n e o f n 2 i f ( n > 0 ) { 3 S y s t e m . o u t . p r i n t l n ( n ) ; 5 3 4 r e c ( n - 1 ) ; 5 2 5 r e c ( n - 1 ) ; 6 } 6 1 7 } r e c ( 3 ) ; n = 0 P o p s t a t e f r o m P r i n t e d : 3 2 1 c a l l s t a c k

  18. A r e c u r s i v e f u n c t i o n N e x t V a l u e 1 v o i d r e c ( i n t n ) { l i n e o f n 2 i f ( n > 0 ) { 3 S y s t e m . o u t . p r i n t l n ( n ) ; 5 3 4 r e c ( n - 1 ) ; 5 2 5 r e c ( n - 1 ) ; 6 } 7 } r e c ( 3 ) ; n = 1 P o p s t a t e f r o m c a l l s t a c k P r i n t e d : 3 2 1

  19. A r e c u r s i v e f u n c t i o n N e x t V a l u e 1 v o i d r e c ( i n t n ) { l i n e o f n 2 i f ( n > 0 ) { 3 S y s t e m . o u t . p r i n t l n ( n ) ; 5 3 4 r e c ( n - 1 ) ; 5 r e c ( n - 1 ) ; 6 } 7 } r e c ( 3 ) ; n = 2 P u s h s t a t e o n t o c a l l s t a c k P r i n t e d : 3 2 1

  20. A r e c u r s i v e f u n c t i o n N e x t V a l u e 1 v o i d r e c ( i n t n ) { l i n e o f n 2 i f ( n > 0 ) { 3 S y s t e m . o u t . p r i n t l n ( n ) ; 5 3 4 r e c ( n - 1 ) ; 6 2 5 r e c ( n - 1 ) ; 6 } 7 } r e c ( 3 ) ; n = 1 P r i n t e d : 3 2 1

  21. A r e c u r s i v e f u n c t i o n N e x t V a l u e 1 v o i d r e c ( i n t n ) { l i n e o f n 2 i f ( n > 0 ) { 3 S y s t e m . o u t . p r i n t l n ( n ) ; 5 3 4 r e c ( n - 1 ) ; 6 2 5 r e c ( n - 1 ) ; 6 } 7 } r e c ( 3 ) ; n = 1 P r i n t s 1 P r i n t e d : 3 2 1 1

  22. A r e c u r s i v e f u n c t i o n 1 v o i d r e c ( i n t n ) { 2 i f ( n > 0 ) { 3 S y s t e m . o u t . p r i n t l n ( n ) ; 4 r e c ( n - 1 ) ; 5 r e c ( n - 1 ) ; 6 } 7 } H o w m u c h m e m o r y d o e s t h i s f u n c t i o n u s e ? D o n ' t f o r g e t t o i n c l u d e t h e c a l l s t a c k !

Download Presentation
Download Policy: The content available on the website is offered to you 'AS IS' for your personal information and use only. It cannot be commercialized, licensed, or distributed on other websites without prior consent from the author. To download a presentation, simply click this link. If you encounter any difficulties during the download process, it's possible that the publisher has removed the file from their server.

Recommend

2015 Schield Logistic MLE1A Excel2013 10/29/2015 V0D V0D V0D 2015 Schield Logistic MLE 1A

2015 Schield Logistic MLE1A Excel2013 10/29/2015 V0D V0D V0D 2015 Schield Logistic MLE 1A

2015 Schield Logistic MLE1A Excel2013 10/29/2015 V0D V0D V0D 2015 Schield Logistic MLE 1A Excel2013 Slides 1 2015 Schield Logistic MLE 1A Excel2013 Slides 2 Logistic Regression using Background & Goals MLE (1A) and Excel 2013

529 views • 26 slides
STAT 605 Data Science Computing Introduction to the UNIX/Linux command line Why UNIX/Linux? As a

STAT 605 Data Science Computing Introduction to the UNIX/Linux command line Why UNIX/Linux? As a

STAT 605 Data Science Computing Introduction to the UNIX/Linux command line Why UNIX/Linux? As a data scientist, you will spend most of your time dealing with data Data sets never arrive ready to analyze Cleaning data, fixing formatting,

709 views • 33 slides
Tonight we dine in shell Tonight we dine in shell Hands-On Unix System Administration DeCal

Tonight we dine in shell Tonight we dine in shell Hands-On Unix System Administration DeCal

Lecture 3 Lecture 3 Tonight we dine in shell Tonight we dine in shell Hands-On Unix System Administration DeCal 2012-09-17 Review $ 1 , $ 2 , . . . ; $ @ , $ * , $ # , $ 0 , $ ? e n v i r o n m e n t v

390 views • 25 slides
Effective Networking with Swift and iOS 8 Ben Scheirman @subdigital ChaiOne Agenda Old

Effective Networking with Swift and iOS 8 Ben Scheirman @subdigital ChaiOne Agenda Old

Effective Networking with Swift and iOS 8 Ben Scheirman @subdigital ChaiOne Agenda Old and Crusty NSURLConnection New Hotness Live Demos ! HTTP Caching Bonus Round: API Tips NSURLConnection NSURLConnection

1.19k views • 105 slides
2019 SECOND QUARTER EARNINGS CONFERENCE CALL August 6, 2019 Forward-looking Statement Except

2019 SECOND QUARTER EARNINGS CONFERENCE CALL August 6, 2019 Forward-looking Statement Except

2019 SECOND QUARTER EARNINGS CONFERENCE CALL August 6, 2019 Forward-looking Statement Except for historical information, all other information provided in this presentation consists of forward - looking statements within the meaning of the

721 views • 29 slides
LARGE CACHE DESIGN Mahdi Nazm Bojnordi Assistant Professor School of Computing University of

LARGE CACHE DESIGN Mahdi Nazm Bojnordi Assistant Professor School of Computing University of

LARGE CACHE DESIGN Mahdi Nazm Bojnordi Assistant Professor School of Computing University of Utah CS/ECE 7810: Advanced Computer Architecture Overview Upcoming deadline Feb. 3 rd : project group formation This lecture Gated Vdd/

467 views • 36 slides
COMP80122 Slides and Presentations with special thanks to Sebastian Brandt , to whom I owe most

COMP80122 Slides and Presentations with special thanks to Sebastian Brandt , to whom I owe most

COMP80122 Slides and Presentations with special thanks to Sebastian Brandt , to whom I owe most ideas for these slides: http://lat.inf.tu-dresden.de/~brandt/HowtoDesignaSlideshow.pdf Carole Goble | Uli Sattler School of Computer Science

675 views • 33 slides
Approximate Program Synthesis James Bornholt Emina Torlak Luis Ceze Dan Grossman University of

Approximate Program Synthesis James Bornholt Emina Torlak Luis Ceze Dan Grossman University of

Approximate Program Synthesis James Bornholt Emina Torlak Luis Ceze Dan Grossman University of Washington Writing approximate programs is hard Precise Implementation Writing approximate programs is hard Precise Implementation Writing

775 views • 38 slides
Taking Part-Time Programmers Seriously Jesse A. Tov Elizabeth Tov Northeastern University

Taking Part-Time Programmers Seriously Jesse A. Tov Elizabeth Tov Northeastern University

Taking Part-Time Programmers Seriously Jesse A. Tov Elizabeth Tov Northeastern University Boston College OBT 2012 need your help. Part-time programmers Part-time programmers need your help. languages and tools Terrible tools No real

404 views • 16 slides
Why Batch and User Evaluations Do Not Give the Same Results A. Turpin Curtin University of

Why Batch and User Evaluations Do Not Give the Same Results A. Turpin Curtin University of

Why Batch and User Evaluations Do Not Give the Same Results A. Turpin Curtin University of Technology Perth, Australia W. Hersh Oregon Health Sciences University Portland, Oregon Presented at SIGIR2001 New Orleans TREC ad-hoc 0.4 MAP 0.3

607 views • 18 slides
Distributed goodness-of-fit: when you can't talk much and have little in common Jayadev Acharya

Distributed goodness-of-fit: when you can't talk much and have little in common Jayadev Acharya

Distributed goodness-of-fit: when you can't talk much and have little in common Jayadev Acharya (Cornell), Clment Canonne (Stanford), Yanjun Han (Stanford), Ziteng Sun (Cornell), and Himanshu Tyagi (IISc Bangalore)

219 views • 19 slides
Accelerator Driven Subcritical Reactors Introducing GEM*STAR A Particularly Advantageous

Accelerator Driven Subcritical Reactors Introducing GEM*STAR A Particularly Advantageous

Accelerator Driven Subcritical Reactors Introducing GEM*STAR A Particularly Advantageous Example Tom Roberts Muons, Inc. Technology to revitalize the nuclear power industry through improved safety, waste management, efficiency, and

795 views • 21 slides
MILITARY MUNITIONS SUPPORT SERVICES 237 217 200 80 252 WEBINAR MAKING DECISIONS 237 217

MILITARY MUNITIONS SUPPORT SERVICES 237 217 200 80 252 WEBINAR MAKING DECISIONS 237 217

MILITARY MUNITIONS SUPPORT SERVICES 237 217 200 80 252 WEBINAR MAKING DECISIONS 237 217 200 119 174 237 217 200 27 .59 INCORPORATING GEOPHYSICS IN THE FS 255 0 163 131 239 110 112 62 102 130 255 0 163 132 65 135

532 views • 29 slides
Cyber@UC Meeting 68 Advanced Persistent Threats If Youre New! Join our Slack:

Cyber@UC Meeting 68 Advanced Persistent Threats If Youre New! Join our Slack:

Cyber@UC Meeting 68 Advanced Persistent Threats If Youre New! Join our Slack: cyberatuc.slack.com (URL changed!) SIGN IN! (Slackbot will post the link in #general every Wed@6:30) Feel free to get involved with one of our committees:

484 views • 13 slides
P. Takis Metaxas & Eni Mustafaraj {pmetaxas,emustafa}@wellesley.edu

P. Takis Metaxas & Eni Mustafaraj {pmetaxas,emustafa}@wellesley.edu

P. Takis Metaxas & Eni Mustafaraj {pmetaxas,emustafa}@wellesley.edu Wellesley College WebScience 2010, Raleigh, NC Outline of Talk (and Conclusions) Real-Dme search combined with

507 views • 17 slides
llava Java in Lisp Syntax Harold Carr (Sun Microsystems) carr@llava.org http://llava.org 1

llava Java in Lisp Syntax Harold Carr (Sun Microsystems) carr@llava.org http://llava.org 1

llava Java in Lisp Syntax Harold Carr (Sun Microsystems) carr@llava.org http://llava.org 1 ILC 2005 Harold Carr llava llava - Main Point Prefix List version of Java with macros & repl Not: Common Lisp/Scheme/* written in

488 views • 44 slides
Outline ! Program Background ! A typical C2 Architecture, Issues to study ! Multi-modeling

Outline ! Program Background ! A typical C2 Architecture, Issues to study ! Multi-modeling

Rapid Synthesis of Multi-Model Simulations for Computation Experiments in C2 Himanshu Neema, Harmon Nine, Graham Hemingway, Janos Sztipanovits, Gabor Karsai ISIS, Vanderbilt University {himanshu,hnine,hemmings,sztipaj,gabor}

415 views • 10 slides
Welcome (back) Youve watched intro VUCA, change, friction/confusion/underperformance

Welcome (back) Youve watched intro VUCA, change, friction/confusion/underperformance

6/23/2020 Welcome (back) Youve watched intro VUCA, change, friction/confusion/underperformance Sustainable competitive advantages are difficult Youve practiced in the simulation Team quiz scores Team Liaisons introduce

402 views • 5 slides
ss t r

ss t r

trt ts t tts sss rs ss t

939 views • 62 slides
Challenges for numerical relativity and gravitational-wave source modeling Emanuele Berti, Johns

Challenges for numerical relativity and gravitational-wave source modeling Emanuele Berti, Johns

Challenges for numerical relativity and gravitational-wave source modeling Emanuele Berti, Johns Hopkins University ICERM Workshop Advances and challenges in computational relativity September 14 2020 Focus of this talk: what

923 views • 60 slides
Maximilian Michels @stadtlegende max@crate.io mxm@apache.org 2 W H Y A R E W E TA L K I N G

Maximilian Michels @stadtlegende max@crate.io mxm@apache.org 2 W H Y A R E W E TA L K I N G

C R AT E D B : A S E A R C H E N G I N E O R A D ATA B A S E ? B O T H ! H O W W E B U I LT A S Q L D ATA B A S E O N T O P O F E L A S T I C S E A R C H A N D L U C E N E Maximilian Michels @stadtlegende max@crate.io

740 views • 29 slides
ACR 3413 BASIC STRUCTURAL ENGINEERING 3 Lecture 1 Univers rsit ity y Putra a Malaysia ysia

ACR 3413 BASIC STRUCTURAL ENGINEERING 3 Lecture 1 Univers rsit ity y Putra a Malaysia ysia

ACR 3413 BASIC STRUCTURAL ENGINEERING 3 Lecture 1 Univers rsit ity y Putra a Malaysia ysia - Communication - Talk to Architect, M&E Engineer and Other Consultants of their Requirements Item Verti tical Load {V} Horizon zonta tal

572 views • 40 slides
Engineering Code Obfuscation ISSISP 2017 - Tamperproofing Christian Collberg Department of

Engineering Code Obfuscation ISSISP 2017 - Tamperproofing Christian Collberg Department of

Engineering Code Obfuscation ISSISP 2017 - Tamperproofing Christian Collberg Department of Computer Science University of Arizona http://collberg.cs.arizona.edu collberg@gmail.com Supported by NSF grants 1525820 and 1318955 and by the

345 views • 12 slides
Security Analysis of India's Electronic Voting Systems Scott Wolchok, Wustrow, Halderman (UMich),

Security Analysis of India's Electronic Voting Systems Scott Wolchok, Wustrow, Halderman (UMich),

Security Analysis of India's Electronic Voting Systems Scott Wolchok, Wustrow, Halderman (UMich), Hari K. Prasad, Kankipati, Sakhamuri, Yagati (NetIndia), Rop Gonggrijp "Reaffirm it's belief in the infallibility of the EVMs" Goals

1.02k views • 53 slides

More recommend