Logic Programming is a programming paradigm widely used for teaching Artificial
Intelligence in university courses. Prolog, probably the most popular Logic Programming
language, is based on inferences similar to theorem provers, and learning it is
propaedeutical for understanding formal specification languages.
However, after a first phase in which students learn how specifications can be translated
into executable code, a second phase is necessary for engineering the resulting program.
In this second phase, having a clear picture of the execution model is crucial.
In this paper, SLDNF-Draw, a program that visualizes the SLDNF operational semantics of
Prolog, is presented. SLDNF-Draw produces trees in LATEX, the popular typesetting
system, so that the generated trees have very high typographic quality and can be embedded
in printed documents (e.g., course handouts) as well as in animated presentations.
SLDNF Draw is completely written in Prolog, as a meta-interpreter, and does not rely on
external imperative languages for the visualization.
AbdennadherS. and
SaftM.A visualization tool for constraint handling rules. In
KusalikA.J., editor,
Proceedings of the Eleventh Workshop on Logic Programming Environments
(WLPE’01), Paphos, Cyprus, December1 (2001), 2001.
2.
AbdennadherS. and
SharafN.Visualization of CHR through source-to-source
transformation. In DovierA. and CostaV.S., editors,
Technical Communications of the 28th International Conference on Logic
Programming, ICLP 2012, September 4-8, 2012, Budapest, Hungary volume
17of LIPIcs, pages109–118. Schloss Dagstuhl - Leibniz-Zentrum
fuer Informatik, 2012.
3.
AielloL.C. and MassacciF..
Verifying security protocols as planning in logic
programming, ACM Transactions on Computational Logics2(4) (2001),
542–580.
4.
ArmandoA., CompagnaL. and LierlerY..
Automatic compilation of protocol insecurity problems into logic
programming. In AlferesJ.J. and
LeiteJ.A., editors,
Logics in Artificial Intelligence, 9th European Conference, JELIA 2004, Lisbon,
Portugal, September 27-30, 2004, Proceedings, volume 3229 of
Lecture Notes in Artificial Intelligence, pages
617–627. Springer,
2004.
5.
BlanchetB..
Automatic verification of cryptographic protocols: a logic programming
approach. In PPDP’ 03: Proceedings of the 5th ACM SIGPLAN
international conference on Principles and practice of declaritive programming,
pages 1–3, New York, NY, USA,
2003. ACM Press.
6.
ChenW., SwiftT.
and WarrenD.S..
Efficient top-down computation of queries under the well-founded
semantics, J Log Program24(3) (1995),
161–199.
7.
ClarkK.L..
Negation as Failure. In GallaireH. and
MinkerJ., editors,
Logic and Data Bases, pages 293–322,
Plenum Press, 1978.
CoelhoH., CottaJ.C. and PereiraL.M.. How To
Solve it with Prolog. Ministério da Habitação e Obras Públicas,
Laboratório Nacional de Engenharia Civil, 3rd
edition, 1982.
10.
DelzannoG. and EtalleS..
Proof theory, transformations, and logic programming for debugging
security protocols. In PettorossiA., editor,
LOPSTR, volume 2372of Lecture Notes in Computer Science, pages76–90. Springer,
2001.
11.
GansnerE.R. and
NorthS.C..
An open graph visualization system and its applications to software
engineering, Software - Practice and Experience30(11) (2000),
1203–1233.
12.
GarciaO., PerezR., SilvermanB., AustinH., BaumR.,
BradyL., CameronR., CastanedaS., ChenJ.,
DeyP., Di-CristinaG., ElmaghrabyA., FosterR., FreemanC., KirchM., LawrenceA., ManeshA., ManickamS., RamamoorthyC., RaridenR., ReichenbachU., RosenbaumS., SanerF., SeveranceF., TorsoneC., ValentineD., LandinghamH.V.,
VasquezR..
On teaching AI and expert system courses, IEEE
Transactions on Education36(1) (1993),
193–197.
GavanelliM..
SLDNF-Draw: a visualisation tool of Prolog operational
semantics. In FiumaraG., MarchiM., and ProvettiA., editors,
CILC 2007, Conferenza Italiana di Computational Logic,
2007.
HolzbaurC..
Metastructures versus attributed variables in the context of extensible
unification. In BruynoogheM. and
WirsingM., editors,
Programming Language Implementation and Logic Programming, 4th International
Symposium, PLILP’ 92, Leuven, Belgium, August 26-28, 1992, Proceedings, volume
631of Lecture Notes in Computer Science, pages260–268. 1992.
17.
JaffarJ. and MaherM..
Constraint logic programming: a survey, Journal
of Logic Programming19-20 (1994),
503–582.
18.
KowalskiR..
Algorithm = logic + control. Communications of the ACM,
22(7) (1979),
424–436.
MunakataT..
Notes on implementing sets in Prolog,
Communications of the ACM35(3) (1992),
112–120.
21.
PontelliE..
Teaching (constraint) logic programming panel at ICLP
2003, ALP Newslwtter17(1) 2004.
22.
SchimpfJ. and ShenK..
ECLiPSe - from LP to CLP, Theory and Practice of
Logic Programming12(1-2) (2012),
127–156.
23.
SomogyiZ., HendersonF. and
ConwayT..
The execution algorithm of Mercury, an efficient purely declarative logic
programming language, Journal of Logic Programming29(1-3) (1996),
17–64.
24.
StallaA., MascardiV. and MartelliM..
PrettyProlog: A Java interpreter and visualizer of Prolog
programs. In GavanelliM. and
RiguzziF., editors,
Atti del convegno CILC 09 24-esimo Convegno Italiano di Logica
Computazionale (2009), pp.
7–11.
25.
StallaA., ZanuccoD., DovierA. and MascardiV..
PrettyCLP: a light Java implementation for teaching CLP.
In FioravantiF., editor,
Proceedings of the 26th Italian Conference on Computational Logic, Pescara,
Italy, August 31 - September 2, 2011, volume 810of CEUR Workshop Proceedings, pages281–295. CEUR-WS.org,
2011.
26.
WielemakerJ.,
LagerT. and RiguzziF..
SWISH: SWI-Prolog for sharing. In EllmauthalerS. and
SchulzC., editors,
Proceedings of the International Workshop on User-Oriented Logic Programming
(IULP 2015), (2015), pp.
99–113.
27.
WielemakerJ.,
SchrijversT.,
TriskaM. and LagerT.,
SWIProlog. Theory and Practice of Logic
Programming, 12(1-2)
(2012), 67–96.
28.
WirthN.. Algorithms
+ Data Structures = Programs. Prentice Hall
PTR, Upper Saddle River, NJ, USA,
1978.
