From specifications to programs: Induction in the service of synthesis

Nachum Dershowitz

doi:10.1007/3-540-58520-6_48

From specifications to programs: Induction in the service of synthesis

Nachum Dershowitz^*

^*Corresponding author for this work

University of Illinois

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

The deductive synthesis of programs from formal specifications can be aided by various forms of induction: Summative, or complete, induction is the deductive technique of reasoning by cases and plays an important role in creating conditionals. Recursive, or mathematical, induction is a deductive technique for reasoning about an infinite number of cases; it is used in the creation of loops, and is often necessary for establishing properties of data types. Eduction, or analogical reasoning helps reduce the amount of work needed to generate a program, when similar programs already exist. Ampliative, or incomplete, induction is the process by which one generalizes from a finite number of instances; it can help the synthesizer guess what statement is needed and to verify the correctness of suggestions.

Original language	English
Title of host publication	Algorithmic Learning Theory - 4th International Workshop on Analogical and Inductive Inference, AII 1994 and 5th International Workshop on Algorithmic Learning Theory, ALT 1994, Proceedings
Editors	Setsuo Arikawa, Klaus P. Jantke
Publisher	Springer Verlag
Pages	6-7
Number of pages	2
ISBN (Print)	9783540585206
DOIs	https://doi.org/10.1007/3-540-58520-6_48
State	Published - 1994
Externally published	Yes
Event	4th International Workshop on Analogical and Inductive Inference, AII 1994 and 5th International Workshop on Algorithmic Learning Theory, ALT 1994 - Reinhardsbrunn Castle, Germany Duration: 10 Oct 1994 → 15 Oct 1994

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	872 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	4th International Workshop on Analogical and Inductive Inference, AII 1994 and 5th International Workshop on Algorithmic Learning Theory, ALT 1994
Country/Territory	Germany
City	Reinhardsbrunn Castle
Period	10/10/94 → 15/10/94

Access to Document

10.1007/3-540-58520-6_48

Cite this

Dershowitz, N. (1994). From specifications to programs: Induction in the service of synthesis. In S. Arikawa, & K. P. Jantke (Eds.), Algorithmic Learning Theory - 4th International Workshop on Analogical and Inductive Inference, AII 1994 and 5th International Workshop on Algorithmic Learning Theory, ALT 1994, Proceedings (pp. 6-7). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 872 LNAI). Springer Verlag. https://doi.org/10.1007/3-540-58520-6_48

Dershowitz, Nachum. / From specifications to programs : Induction in the service of synthesis. Algorithmic Learning Theory - 4th International Workshop on Analogical and Inductive Inference, AII 1994 and 5th International Workshop on Algorithmic Learning Theory, ALT 1994, Proceedings. editor / Setsuo Arikawa ; Klaus P. Jantke. Springer Verlag, 1994. pp. 6-7 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{5757c58ffb2047359238ca71ed09de32,

title = "From specifications to programs: Induction in the service of synthesis",

abstract = "The deductive synthesis of programs from formal specifications can be aided by various forms of induction: Summative, or complete, induction is the deductive technique of reasoning by cases and plays an important role in creating conditionals. Recursive, or mathematical, induction is a deductive technique for reasoning about an infinite number of cases; it is used in the creation of loops, and is often necessary for establishing properties of data types. Eduction, or analogical reasoning helps reduce the amount of work needed to generate a program, when similar programs already exist. Ampliative, or incomplete, induction is the process by which one generalizes from a finite number of instances; it can help the synthesizer guess what statement is needed and to verify the correctness of suggestions.",

author = "Nachum Dershowitz",

note = "Publisher Copyright: {\textcopyright} 1994, Springer Verlag. All Rights Reserved.; 4th International Workshop on Analogical and Inductive Inference, AII 1994 and 5th International Workshop on Algorithmic Learning Theory, ALT 1994 ; Conference date: 10-10-1994 Through 15-10-1994",

year = "1994",

doi = "10.1007/3-540-58520-6_48",

language = "אנגלית",

isbn = "9783540585206",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Verlag",

pages = "6--7",

editor = "Setsuo Arikawa and Jantke, {Klaus P.}",

booktitle = "Algorithmic Learning Theory - 4th International Workshop on Analogical and Inductive Inference, AII 1994 and 5th International Workshop on Algorithmic Learning Theory, ALT 1994, Proceedings",

address = "גרמניה",

}

Dershowitz, N 1994, From specifications to programs: Induction in the service of synthesis. in S Arikawa & KP Jantke (eds), Algorithmic Learning Theory - 4th International Workshop on Analogical and Inductive Inference, AII 1994 and 5th International Workshop on Algorithmic Learning Theory, ALT 1994, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 872 LNAI, Springer Verlag, pp. 6-7, 4th International Workshop on Analogical and Inductive Inference, AII 1994 and 5th International Workshop on Algorithmic Learning Theory, ALT 1994, Reinhardsbrunn Castle, Germany, 10/10/94. https://doi.org/10.1007/3-540-58520-6_48

From specifications to programs: Induction in the service of synthesis. / Dershowitz, Nachum.
Algorithmic Learning Theory - 4th International Workshop on Analogical and Inductive Inference, AII 1994 and 5th International Workshop on Algorithmic Learning Theory, ALT 1994, Proceedings. ed. / Setsuo Arikawa; Klaus P. Jantke. Springer Verlag, 1994. p. 6-7 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 872 LNAI).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - From specifications to programs

T2 - 4th International Workshop on Analogical and Inductive Inference, AII 1994 and 5th International Workshop on Algorithmic Learning Theory, ALT 1994

AU - Dershowitz, Nachum

PY - 1994

Y1 - 1994

N2 - The deductive synthesis of programs from formal specifications can be aided by various forms of induction: Summative, or complete, induction is the deductive technique of reasoning by cases and plays an important role in creating conditionals. Recursive, or mathematical, induction is a deductive technique for reasoning about an infinite number of cases; it is used in the creation of loops, and is often necessary for establishing properties of data types. Eduction, or analogical reasoning helps reduce the amount of work needed to generate a program, when similar programs already exist. Ampliative, or incomplete, induction is the process by which one generalizes from a finite number of instances; it can help the synthesizer guess what statement is needed and to verify the correctness of suggestions.

AB - The deductive synthesis of programs from formal specifications can be aided by various forms of induction: Summative, or complete, induction is the deductive technique of reasoning by cases and plays an important role in creating conditionals. Recursive, or mathematical, induction is a deductive technique for reasoning about an infinite number of cases; it is used in the creation of loops, and is often necessary for establishing properties of data types. Eduction, or analogical reasoning helps reduce the amount of work needed to generate a program, when similar programs already exist. Ampliative, or incomplete, induction is the process by which one generalizes from a finite number of instances; it can help the synthesizer guess what statement is needed and to verify the correctness of suggestions.

UR - http://www.scopus.com/inward/record.url?scp=85026873535&partnerID=8YFLogxK

U2 - 10.1007/3-540-58520-6_48

DO - 10.1007/3-540-58520-6_48

M3 - ???researchoutput.researchoutputtypes.contributiontobookanthology.conference???

AN - SCOPUS:85026873535

SN - 9783540585206

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 6

EP - 7

BT - Algorithmic Learning Theory - 4th International Workshop on Analogical and Inductive Inference, AII 1994 and 5th International Workshop on Algorithmic Learning Theory, ALT 1994, Proceedings

A2 - Arikawa, Setsuo

A2 - Jantke, Klaus P.

PB - Springer Verlag

Y2 - 10 October 1994 through 15 October 1994

ER -

Dershowitz N. From specifications to programs: Induction in the service of synthesis. In Arikawa S, Jantke KP, editors, Algorithmic Learning Theory - 4th International Workshop on Analogical and Inductive Inference, AII 1994 and 5th International Workshop on Algorithmic Learning Theory, ALT 1994, Proceedings. Springer Verlag. 1994. p. 6-7. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/3-540-58520-6_48

From specifications to programs: Induction in the service of synthesis

Abstract

Publication series

Conference

Access to Document

Other files and links

Fingerprint

Cite this