Logic Programming

Though the semantics of nonmonotonic logic programming has been studied extensively, relatively little work has been done on operational aspects of these semantics. In this paper, we develop techniques to compute the well-founded model of a logic program. We describe a prototype implementation and show, based on experimental results, that our technique is more efficient than the standard alternating fixpoint computation. Subsequently, we develop techniques to compute the set of all stable models of a deductive database. These techniques first compute the well-founded semantics and then use an intelligent branch and bound strategy to compute the stable models. We report on our implementation, as well as on experiments that we have conducted on the efficiency of our approach. monotonic reasoning, negation by failure. Index Term-Logic programming, deductive databases, non-I 'Throughout this paper, we will consider only deductive databases, i e., logic programs without function symbols.

Kumauni language is one of the regional languages of India, which is spoken in one of the Himalayan region Kumaun. Since the language is relatively understudied, in this study an attempt has been made to develop a parsing tool for use in Kumauni language studies. The eventual aim is help develop a technique for checking grammatical structures of Kumauni sentences. For this purpose, we have taken a set of pre-existing Kumauni sentences and derived rules of grammar from them. While selecting this set of sentences, effort has been made to select those sentences which are representative of the various possible tags of parts of speeches of the language, as used currently. This has been done to ensure that the sentences constitute all possible tags. These derived rules of Kumauni grammar have been converted to a mathematical model using Earley’s algorithm suitably modified by us. The mathematical model so developed has been tested on a separate set of pre-existing Kumauni sentences and th...

Tese (doutorado) - Universidade Federal de Santa Catarina, Centro Tecnológico. Programa de Pós-Graduação em Engenharia de Produção.As Sucessivas inovações tecnológicas aplicadas ao ensino sinalizam a expectativa de processos de educação mais flexíveis e conseqüentemente a possibilidade de se poder proporcionar aprendizagem a grande contingente da população através de ensino a distancia, respeitando-se a necessidade de cada indivíduo em função da forma e conteúdo a ser aprendido. Em face desta necessidade este trabalho de pesquisa buscou contribuir com esse processo evolutivo de ensino flexível, indicando ícones representativos das características das Inteligências Múltiplas, que possibilitará o desenvolvimento de uma ferramenta capaz de identificar quais as características dominantes desse individuo. Para se chegar à indicação dos ícones representativos das características das inteligências múltiplas foram utilizados métodos da Ergonomia Informacional para sinalização de ambientes p...

This paper presents the STAR system, a system for automated narrative comprehension, developed on top of an argumentation-theoretic formulation of defeasible reasoning, and strongly following guidelines from the psychology of comprehension. We discuss the system’s use in psychological experiments on story comprehension, and our plans for its broader use in empirical studies concerning wider issues of commonsense reasoning.

Modular-E: An Elaboration Tolerant Approach to the Ramification and Qualification Problems Antonis Kakas1, Loizos Michael2, and Rob Miller3 1 University of Cyprus, PO Box 20537, CY-1678, Cyprus antonis@ ucy. ac. cy 2 Harvard University, Cambridge, MA 02138, USA ...

This paper describes the use of a mixture of abduction and induction for the problem of identifying the effects of toxins in metabolic networks. Background knowledge is used which describes network topology and functional classes of enzymes. This background knowledge, which represents the present state of understanding, is incomplete. In order to overcome this incompleteness hypotheses are entertained which consist of a mixture of specific inhibitions of enzymes (ground facts) together with general rules which predict classes of enzymes likely to be inhibited by the toxin (nonground). The foreground examples were derived from in vivo experiments involving NMR analysis of time-varying metabolite concentrations in rat urine following injections of toxin. Hypotheses about inhibition are built using Progol5.0 and predictive accuracy is assessed for both the ground and the non-ground cases.

Antonis Kakas Department of Computer Science, University of Cyprus, 75 Kallipoleos Street, PO Box 537, CY-1678 Nicosia, CYPRUS antonis@turing.cs.ucy.ac.cy http://www.ucy.ac.cy/ucy /cs/webPages/PEOPLE/faculty/kakas.htm ... Rob Miller School of Library Archive and ...

Abstract. This paper presents a framework thai integrates three aspects of agency: planning, for proactive behaviour, negotiation, for social behaviour and resource achievement, and control of operation, for reconciling rationality with reactivity. Agents are designed and programmed in a computational logic-based language where these aspects are accommodated in a declarative and modular way. We show how this framework can be applied to agent problems requiring negotiation and resource achievement and present ...

Constraints play an important role in programming languages and in OR and AI work. Here we give an axiomatic approach that accounts for examples that come up in logic programming, symbolic computation, affine geometry and elsewhere. We show that if disjunction behaves in an intuitionistic fashion, notions of canonical form for positive constraints can be systematically extended to include negative constraints. As a consequence, completeness theorems involving positive and negative constraints can be proven in a general setting for constraint propagation.

Constraint propagation algorithms implement logical inference. For efficiency, it is essential to control whether and in what order basic inference steps are taken. We provide a high-level framework that clearly differentiates between information needed for controlling propagation versus that needed for the logical semantics of complex constraints composed from primitive ones. We argue for the appropriateness of our controlled propagation framework by showing that it captures the underlying principles of manually designed propagation algorithms, such as literal watching for unit clause propagation and the lexicographic ordering constraint. We provide an implementation and benchmark results that demonstrate the practicality and efficiency of our framework.

This paper presents a reactive programming and triggering framework for the coordination of a large number of distributed agents with shared knowledge. At the heart of this framework is a highly structured shared store in the form of a constraint logic program (CLP), which is used as a knowledge base and being reacted to by agents through the use of "reactors". The biggest challenge arising from such a reactive programming framework using CLP is to develop a trigger mechanism that allows efficient "wakeup" of blocked reactors. This paper addresses the architecture of this open framework, and discusses a general methodology for doing triggering of logic conditions using views and abstractions.

Functional constraints are an important constraint class in Constraint Programming (CP) systems, in particular for Constraint Logic Programming (CLP) systems. CP systems with finite domain constraints usually employ CSP-based solvers which use local consistency, e.g. arc consistency. We introduce a new approach which is based instead on variable substitution. We obtain efficient algorithms for reducing systems involving functional and bi-functional constraints together with other nonfunctional constraints. It also solves globally any CSP where there exists a variable such that any other variable is reachable from it through a sequence of functional constraints. Our experiments show that variable elimination can significantly improve the efficiency of solving problems with functional constraints.

The CLP( ℛ ) programming language is defined, its underlying philosophy and programming methodology are discussed, important implementation issues are explored in detail, and finally, a prototype interpreter is described. CLP( ℛ ) is designed to be an instance of the Constraint Logic Programming Scheme, a family of rule-based constraint programming languages defined by Jaffar and Lassez. The domain of computation ℛ of this particular instance is the algebraic structure consisting of uninterpreted functors over real numbers. An important property of CLP( ℛ )is that the constraints are treated uniformly in the sense that they are used to specify the input parameters to a program, they are the only primitives used in the execution of a program, and they are used to describe the output of a program. Implementation of a CLP language, and of CLP( ℛ ) in particular, raises new problems in the design of a constraint-solver. For example, the constraint solver must be incremental in the sense...

In this work, we study a dynamic multi-armed bandit (MAB) problem, where the expected reward of each arm evolves over time following an auto-regressive model. We present an algorithm whose per-round regret upper bound almost matches the regret lower bound, and numerically demonstrate its efficacy in adapting to the changing environment.

This study proposes solving scheduling problems in industrial applications using the decomposition approach. The proposed model has been built using Multi-shot Answer Set Programming with Difference Logic. We tested our model with some benchmark instances and the results showed that our model is comparable to Constraint Programming to other heuristics in the literature.

The Semantic Web ontologies can contain vague axioms, which means the knowledge about them is imprecise and then query answering will not possible due to the open world assumption if the necessary information is incomplete (there is an ignorance about information). An axiom description can be very exact (crisp axiom) or exact (fuzzy axiom) if its knowledge is complete, otherwise it is inexact (vague axiom) if its knowledge is incomplete. Here, the author proposes vagueness description with meta-level logic programming to describe vague ontologies. These vagueness descriptions are inputs to vagueness reasoning procedure implemented at meta-level, which is based on extended tableau algorithm. The extended tableau algorithm is intended to answer queries even with the presence of imprecise information.

interpretation is a theory of semantics approximation which is used for the con struction of semantics-based program analysis algorithms (sometimes called "data flow analysis"), the comparison of formal semantics (e.g., construction of a denotational semantics from an operational one), the design of proof methods, etc. Automatic program analysers are used for determining statically conservative approximations of dy namic properties of programs. Such properties of the run-time behavior of programs are useful for debug ging (e.g., type inference), code optimization (e.g., compile-time garbage collection, useless occur-check elimination), program transformation (e.g., partial evaluation, parallelization), and even program cor rectness proofs (e.g., termination proof). After a few simple introductory examples, we recall the classical framework for abstract interpretation of programs. Starting from a standard operational semantics formalized as a transition system, classes of program properties are first encapsulated in collecting semantics expressed as fixpoints on partial orders representing concrete program properties. We consider invariance properties characterizing the descendant states of the initial states (corresponding to top/down or forward analyses), the ascendant states of the final states (corresponding to bottom/up or backward analyses) as well as a combination of the two. Then we choose specific approximate abstract properties to be gathered about program behaviors and express them as elements of a poset of abstract properties. The correspondence between concrete and abstract properties is established by a concretization and abstraction function that is a Galois connection formalizing the loss of information. We can then constructively derive the abstract program properties from the collecting semantics by a formal computation leading to a fixpoint expression in terms of abstract operators on the domain of abstract properties. The design of the abstract interpreter then involves the choice of a chaotic iteration strategy to solve this abstract fixpoint equation. We insist on the compositional design of this abstract interpreter, which is formalized by a series of propositions for designing Galois connections (such as Moore families, decomposition by partitioning, reduced product, down-set completion, etc.). Then we recall the convergence acceleration methods using widening and narrowing allowing for the use of very expressive infinite domains of abstract properties. We show that this classical formal framework can be applied in extenso to logic programs. For simplicity, we use a variant of SLD-resolution as the standard operational semantics. The first example is groundness analysis, which is a variant of Mellish mode analysis. It is extended to a combination of top/down and bottom/up analyses. The second example is the derivation of constraints among argument sizes, which involves an infinite abstract domain requiring the use of convergence acceleration methods. We end up with a short thematic guide to the literature on abstract interpretation of logic programs.

Model transformation by example is a novel approach in model-driven software engineering. The rationale behind the approach is to derive transformation rules from an initial set of interrelated source and target models; e.g., requirements analysis and software design models. The derived rules describe different transformation steps in a purely declarative way. Inductive Logic Programming utilizes the power of machine learning and the capability of logic programming to induce valid hypotheses from given examples. In this paper, we use Inductive Logic Programming to derive transformation rules from given examples of analysis-design pairs. As a proof concept, we applied the approach to two major software design tasks: class packaging and introducing Façade design. Various analysisdesign model pairs collected from different sources were used as case studies. The resultant performance measures show that the approach is promising.

Analysis and design phases are the most crucial part of the software development life-cycle. Reusing the artifacts of these early phases is very beneficial to improve the productivity and software quality. In this paper we analyze the literature on the automatic transformation of artifacts from the problem space (i.e., requirement analysis models) into artifacts in the solution space (i.e., architecture, design and implementation code). The goal is to assess the current state of the art with regard to the ability of automatically reusing previously developed software designs in synthesizing a new design for a given requirement. We surveyed various related areas such as model-driven development and model transformation techniques. Our analysis revealed that this topic has not been satisfactorily covered yet. Accordingly, we propose a framework consists of three stages to address uncovered limitations in current approaches.

Analysis and design phases are the most crucial part of the software development life-cycle. Reusing the artifacts of these early phases is very beneficial to improve the productivity and software quality. In this paper we analyze the literature on the automatic transformation of artifacts from the problem space (i.e., requirement analysis models) into artifacts in the solution space (i.e., architecture, design and implementation code). The goal is to assess the current state of the art with regard to the ability of automatically reusing previously developed software designs in synthesizing a new design for a given requirement. We surveyed various related areas such as model-driven development and model transformation techniques. Our analysis revealed that this topic has not been satisfactorily covered yet. Accordingly, we propose a framework consists of three stages to address uncovered limitations in current approaches.

Logic programming has been used in a broad range of fields, from artifficial intelligence applications to general purpose applications, with great success. Through its declarative semantics, by making use of logical conjunctions and disjunctions, logic programming languages present two types of implicit parallelism: and-parallelism and or-parallelism. This thesis focuses mainly in Prolog as a logic programming language, bringing out an abstract model for parallel execution of Prolog programs, leveraging the Extended Andorra Model (EAM) proposed by David H.D. Warren, which exploits the implicit parallelism in the programming language. A meta-compiler implementation for an intermediate language for the proposed model is also presented. This work also presents a survey on the state of the art relating to implemented Prolog compilers, either sequential or parallel, along with a walk-through of the current parallel programming frameworks. The main used model for Prolog compiler implement...

Type systems are widely used in programming languages as a powerful tool providing safety to programs, and forcing the programmers to write code in a clearer way. Functional logic languages have inherited Damas & Milner type system from their functional part due to its simplicity and popularity. In this paper we address a couple of aspects that can be subject of improvement. One is related to a problematic feature of functional logic languages not taken under consideration by standard systems: it is known that the use of opaque HO patterns in left-hand sides of program rules may produce undesirable effects from the point of view of types. We re-examine the problem, and propose a Damas & Milnerlike type system where certain uses of HO patterns (even opaque) are permitted while preserving type safety, as proved by a subject reduction result that uses HO-let-rewriting, a recently proposed reduction mechanism for HO functional logic programs. The other aspect is the different ways in which polymorphism of local definitions can be handled. At the same time that we formalize the type system, we have made the effort of technically clarifying the overall process of type inference in a whole program.

The features of logic programming that seem unconventional from the viewpoint of classical logic can be explained in terms of constructivistic logic. We motivate and propose a constructivistic proof theory of non-Horn logic programming. Then, we apply this formalization for establishing results of practical interest. First, we show that 'stratification can be motivated in a simple and intuitive way. Relying on similar motivations, we introduce the larger classes of 'loosely stratified' and 'constructively consistent' programs. Second, we give a formal basis for introducing quantifiers into queries and logic programs by defining 'constructively domain independent* formulas. Third, we extend the Generalized Magic Sets procedure to loosely stratified and constructively consistent programs, by relying on a 'conditional fixpoini procedure.

Processing programs as data is one of the successes of functional and logic programming. Higher-order functions, as program-processing programs are called in functional programming, and meta-programs, as they are called in logic programming, are widespread declarative programming techniques. In logic programming, there is a gap between the meta-programming practice and its theory: The formalizations of meta-programming do not explicitly address its impredicativity and are not fully adequate. This article aims at overcoming this unsatisfactory situation by discussing the relevance of impredicativity to meta-programming, by revisiting former formalizations of meta-programming, and by defining Reflective Predicate Logic, a conservative extension of first-order logic, which provides a simple formalization of meta-programming.

The conventional formalization of logic programming in classical logic explains very convincingly the basic principles of this programming style. However, it gives no easy or intuitive explanations for the treatment of negation. Logic Programming handles negation through the so-called ^Negation as Failure" inference principle which is rather unconventional from the viewpoint of classical logic. Despite its nonclassical nature, this inference principle cannot be avoided in practice. The appropriate application of Negation as Failure requires either syntactical restrictions, or significant changes in the semantics of logic programs. In this article, we defend the thesis that these syntactical restrictions or semantical changes are naturally and simply explained by observing that logic programming in fact implements no more than a constructive fragment of classical logic. Relying on a "Conditional Fixpoint Procedure", we first define a monotonic inference procedure for logic programs with negation that are consistent in this constructive fragment. Then we show how this procedure can be extended into a "Temary Fixpoint Procedure" for general programs. This fixpoint procedure defines a temary logic semantics for syntactically unrestricted logic programs. Finally, we argue that the constructive interpretation of logic programming also gives a simple and natural explanation of meta-programming. Relying on this view of meta-programming, we specify different forms of reflective reasoning, in particular default reasoning.

s are not reviewed. We are delighted to publish 12 abstracts from 2015/16 in this round and hope that JFP readers will find many interesting dissertations in this collection that they may not otherwise have seen. If a student or advisor would like to submit a dissertation abstract for publication in this series, please contact the series editor for further details. Graham Hutton PhD Abstract Editor

This paper describes the design and implementation of the programming language PC-Life. This language integrates the functional and the logic-oriented programming style and feature types supporting inheritance. This combination yields a language particularly suited to knowledge representation , especially for application in computational linguistics.

We describe Currawong, a tool to perform system software architecture optimisation. Currawong is an extensible tool which applies optimisations at the point where an application invokes framework or library code. Currawong does not require source code to perform optimisations, effectively decoupling the relationship between compilation and optimisation. We show, through examples written for the popular Android smartphone platform, that Currawong is capable of significant performance improvement to existing applications. Categories and Subject Descriptors

In modern functional logic languages like Curry or Toy, programs are possibly nonconfluent and non-terminating rewrite systems, defining possibly non-deterministic non-strict functions. Therefore, equational reasoning is not valid for deriving properties of such programs. In a previous work we showed how a mapping from CRWL -a well known logical framework for functional logic programming-into logic programming could be in principle used as logical conceptual tool for proving properties of functional logic programs. A severe problem faced in practice is that simple properties, even if they do not involve non-determinism, require difficult proofs when compared to those obtained using equational specifications and methods. In this work we improve our approach by taking into account determinism of (part of) the considered programs. This results in significant shortenings of proofs when we put in practice our methods using standard systems supporting equational reasoning like, e.g., Isabelle.

The G12 project recently started by National ICT Australia (NICTA) is an ambitious project to develop a software platform for solving large scale industrial combinatorial optimisation problems. The core design involves three languages: Zinc, Cadmium and Mercury (Group 12 of the periodic table). Zinc is a declarative modelling language for expressing problems, independent of any solving methodology. Cadmium is a mapping language for mapping Zinc models to underlying solvers and/or search strategies, including hybrid approaches. Finally, existing Mercury will be extended as a language for building extensible and hybridizable solvers. The same Zinc model, used with different Cadmium mappings, will allow us to experiment with different complete, local, or hybrid search approaches for the same problem. This talk will explain the G12 global design, the final G12 objectives, and our progress so far.

Recent functional logic languages such as Curry and Toy combine lazy functional programming with logic programming features including logic variables, non-determinism, unification, narrowing, fair search, concurrency, and residuation. In this paper, we show how to extend a conventional interpreter for a lazy functional language to handle these features by adding support for reference cells, process-like and thread-like concurrency mechanisms, and a novel form of multi-versioned store. Our interpretation scheme is practical, and can be easily extended to perform compilation. The language specified by our interpreter is designed so that programs are deterministic in a novel and useful sense.

A formal model for similarity-based fuzzy unification in multi-adjoint logic programs is presented. On this computational model, a similarity-based unification approach is constructed by simply adding axioms of fuzzy similarities and using classical crisp unification which provides a semantic framework for logic programming with different notions of similarity. Open access under CC BY-NC-ND license.

In this paper, we investigate the notion of error correction memory applied to technical texts. The main purpose is to introduce flexibility and context sensitivity in the detection and the correction of errors related to Constrained Natural Language (CNL) principles. This is realized by enhancing error detection paired with relatively generic correction patterns and contextual correction recommendations. Patterns are induced from previous corrections made by technical writers for a given type of text. The impact of such an error correction memory is also investigated from the point of view of the technical writer's cognitive activity. The notion of error correction memory is developed within the framework of the LELIE project an experiment is carried out on the case of fuzzy lexical items and negation, which are both major problems in technical writing. Language processing and knowledge representation aspects are developed together with evaluation directions.

Resum. El llenguatge de l'explicació dedicat als documents tècnics. Aquest article presenta un estudi de les explicacions tal com apareixen en documents tècnics, especialment en procediments on aquestes explicacions resulten crucials. El nostre estudi es basa en l'anàlisi d'un corpus ampli. S'hi introdueix la noció de funció explicativa amb objectius comunicatius i es presenten els esquemes d'explicació que són les realitzacions lingüístiques de les funcions. Així, es proporcionen alguns detalls sobre els patrons lingüístics que permeten la identificació d'aquests esquemes.

In this paper, we investigate the notion of error correction memory applied to technical texts. The main purpose is to introduce flexibility and context sensitivity in the detection and the correction of errors related to Constrained Natural Language (CNL) principles. This is realized by enhancing error detection paired with relatively generic correction patterns and contextual correction recommendations. Patterns are induced from previous corrections made by technical writers for a given type of text. The impact of such an error correction memory is also investigated from the point of view of the technical writer's cognitive activity. The notion of error correction memory is developed within the framework of the LELIE project an experiment is carried out on the case of fuzzy lexical items and negation, which are both major problems in technical writing. Language processing and knowledge representation aspects are developed together with evaluation directions.

TEX les are text les which are readable by other programs. Mathematical proofs written using TEX can be checked by a Python program provided they are expressed in a suciently strict proof language. Such a language can be con- structed using only a few extensions beyond the syntax of A.P. Morse's A Theory of Sets, one being the incorporation of

We discuss how over the last 30 to 50 years, Artificial Intelligence (AI) systems that focused only on data have been handicapped, and how knowledge has been critical in developing smarter, intelligent, and more effective systems. In fact, the vast progress in AI can be viewed in terms of the three waves of AI as identified by DARPA. During the first wave, handcrafted knowledge has been at the center-piece, while during the second wave, the data-driven approaches supplanted knowledge. Now we see a strong role and resurgence of knowledge fueling major breakthroughs in the third wave of AI underpinning future intelligent systems as they attempt human-like decision making, and seek to become trusted assistants and companions for humans. We find a wider availability of knowledge created from diverse sources, using manual to automated means both by repurposing as well as by extraction. Using knowledge with statistical learning is becoming increasingly indispensable to help make AI systems more transparent and auditable. We will draw a parallel with the role of knowledge and experience in human intelligence based on cognitive science, and discuss emerging neuro-symbolic or hybrid AI systems in which knowledge is the critical enabler for combining capabilities of the data-intensive statistical AI systems with those of symbolic AI systems, resulting in more capable AI systems that support more human-like intelligence.

Information Systems are coded in a variety of programming languages ranging from production object-oriented languages to scripting languages to declarative languages. It is crucial that the programmers have a good understanding of the fundamental concepts, notations and techniques that underlie these languages and issues related to evaluating and choosing from among these languages. There exist many good textbooks and Web-based resources for the study of comparative programming languages. In spite of these resources, however, students often fail to grasp the fundamentals and their application to both modern language implementation and their own problem solving skills. Modern languages are geared towards enhancing programmer productivity, sometimes at the expense of efficiency. For every language, paradigm, or style, there exists some application domain for which it is well-suited. We believe that a comprehensive set of programming exercises are needed that clearly bring out the role of each paradigm/language, especially the fact that they are complementary in nature rather than competitive.

Abstract. The present paper shows how the mechanism of tabling can be brought to fruition in abductive logic programming, but requiring an innovative usage of said tabling mechanisms. Abductive solutions tabled in one context can thereby be reused in a different abductive context consistent with them, and need not be recomputed. Given an abductive logic program P, a query to P is evaluated with respect to a program transformation of P, which does not require a metainterpreter. The transformation introduces tabled predicates ...

The problem of forward abstract interpretation of normal logic programs has not been formally addressed in the literature although negation as failure is dealt with through the built-in predicate ! in the way it is implemented in Prolog. This paper proposes a solution to this problem by deriving two generic fixed-point abstract semantics F ♭ P and F ⋄ P for forward abstract interpretation of normal logic programs. F ♭ P is intended for inferring data descriptions for edges in the program graph where an edge denotes the possibility that the control of execution transfers from its source program point to its destination program point. F ⋄ P is derived from F ♭ P and is intended for inferring data descriptions for textual program points.

On the one hand, the olive oils’ quality is fixed by the region in which it is produced, the olive variety, the year of production, the degree of maturation, the extraction and the preservation processes, i.e., the olive oils` quality is assessed by two types of analyzes, the organoleptic and the biochemical ones. On the other hand, there are no studies linking analytical parameters to sensory data due to the nonlinearity that exists between these two types of variables. The present study aims to provide an answer to these problems by modeling the causal processes used at different types of olive and olive oil production. To this end, we called at an Artificial Neural Network approach to problem solving once it provides a way to handle the various stages of ripeness of the olives and olive oil production, by allowing one to deal with incomplete, unknown or even self-contradictory information or knowledge

Gavrila Nathania Panjaitan (4233311004) Mastri Angely Br. Sitanggang (4233111061) Najwa Azzahra (4233111045) Rfki Aidil Fikri (4233111018) Sevrianna Simarmata (4232411001) KELAS: PSPM 23 D PENDIDIKAN MATEMATIKA FAKULTAS MATEMATIKA DAN ILMU PENGETAHUAN ALAM UNIVERSITAS NEGERI MEDAN 2025 i Puji dan syukur kami panjatkan ke hadirat Tuhan Yang Maha Esa atas rahmat dan karunia-Nya sehingga kami dapat menyelesaikan makalah ini yang membahas analisis while loop dalam validasi input pengguna. Makalah ini disusun sebagai bagian dari mata kuliah Bahasa Pemrograman untuk memahami bagaimana struktur perulangan while dapat digunakan secara efektif dalam memastikan validitas data yang dimasukkan oleh pengguna dalam suatu program. Dalam makalah ini, kami akan mengulas konsep dasar while loop, cara penerapannya dalam validasi input, serta beberapa contoh kasus yang menunjukkan bagaimana teknik ini digunakan dalam pemrograman. Pemahaman yang baik tentang perulangan while sangat penting bagi pengembang perangkat lunak, karena validasi input yang baik akan meningkatkan keandalan dan keamanan aplikasi yang dibuat. Kami menyadari bahwa dalam penyusunan makalah ini masih terdapat kekurangan, baik dalam materi maupun penyajiannya. Oleh karena itu, kami mengharapkan saran dan masukan yang membangun agar makalah ini dapat lebih baik di masa depan. Semoga makalah ini bermanfaat bagi pembaca, khususnya mahasiswa yang sedang mempelajari konsep perulangan dalam pemrograman.

Gavrila Nathania Panjaitan (4233311004) Mastri Angely Br. Sitanggang (4233111061) Najwa Azzahra (4233111045) Rfki Aidil Fikri (4233111018) Sevrianna Simarmata (4232411001) KELAS: PSPM 23 D PENDIDIKAN MATEMATIKA FAKULTAS MATEMATIKA DAN ILMU PENGETAHUAN ALAM UNIVERSITAS NEGERI MEDAN 2025 i Puji dan syukur kami panjatkan ke hadirat Tuhan Yang Maha Esa atas rahmat dan karunia-Nya sehingga kami dapat menyelesaikan makalah ini yang membahas analisis while loop dalam validasi input pengguna. Makalah ini disusun sebagai bagian dari mata kuliah Bahasa Pemrograman untuk memahami bagaimana struktur perulangan while dapat digunakan secara efektif dalam memastikan validitas data yang dimasukkan oleh pengguna dalam suatu program. Dalam makalah ini, kami akan mengulas konsep dasar while loop, cara penerapannya dalam validasi input, serta beberapa contoh kasus yang menunjukkan bagaimana teknik ini digunakan dalam pemrograman. Pemahaman yang baik tentang perulangan while sangat penting bagi pengembang perangkat lunak, karena validasi input yang baik akan meningkatkan keandalan dan keamanan aplikasi yang dibuat. Kami menyadari bahwa dalam penyusunan makalah ini masih terdapat kekurangan, baik dalam materi maupun penyajiannya. Oleh karena itu, kami mengharapkan saran dan masukan yang membangun agar makalah ini dapat lebih baik di masa depan. Semoga makalah ini bermanfaat bagi pembaca, khususnya mahasiswa yang sedang mempelajari konsep perulangan dalam pemrograman.

The purpose of this report is to provide the necessary information for running the programs IMPACTC. FTN and IMPACTB. FTN for the dynamics of a radially rotating beam with impact. In particular the report outlines the structure of the software and how to compile, run and modify the program. All programs are written in standard FORTRAN 77 and run on APOLLO DN3000 or DN560 workstations.

Puji dan syukur penulis panjatkan kepada Tuhan Yang Maha Esa, karena atas berkat dan rahmat-Nya yang diberikan kepada penulis sehingga penulis dapat menyelesaikan tugas mini riset ini dengan baik sesuai arahan dan tepat pada waktunya. Laporan ini dibuat untuk memenuhi tugas mini riset pada mata kuliah Bahasa Pemrograman. Tak lupa penulis ucapkan terimakasih kepada dosen pengampu mata kuliah Bahasa Pemrograman, Bapak Denny Haris, S.Si., M.Pd. yang telah memberikan bimbingan kepada penulis dalam menyelesaikan tugas ini. Penulis menyadari dalam penyusunan laporan ini, masih terdapat banyak kekurangan sehingga hasil yang diperoleh masih jauh dari sempurna. Oleh sebab itu, penulis mengharapkan saran dan kritik yang membangun dari pembaca. Akhir kata penulis ucapkan terima kasih, semoga laporan ini dapat memberikan manfaat dan bisa menambah pengetahuan kepada penulis dan pembaca.