DOCSLIB.ORG

(Primitive) Data Types Scheme Is a Recent Dialect of Symbols: Lisp

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
(Primitive) Data Types Scheme Is a Recent Dialect of Symbols: Lisp Lisp & Scheme • Dynamic data structures (lists, binary trees) that grow without Lisp (List Processing Language) limit. is one of the oldest • Automatic garbage collection to programming languages still in manage memory. wide use. • Functions are treated as “first class” It was developed in the late 50s values; they may be passed as and early 60s by John arguments, returned as result McCarthy. values, stored in data structures, and created during execution. Its innovations include: • A formal semantics (written in Lisp) • Support of symbolic computations. that defines the meaning of all • A functional programming style valid programs. without emphasis on assignments • An Integrated Programming and side-effects. Environment to create, edit and • A naturally recursive programming test Lisp programs. style. • Dynamic (run-time) type checking. © © CS 538 Spring 2008 99 CS 538 Spring 2008 100 Scheme Atomic (Primitive) Data Types Scheme is a recent dialect of Symbols: Lisp. Essentially the same form as It uses lexical (static) scoping. identifiers. Similar to enumeration values in C and C++. It supports true first-class Very flexible in structure; functions. essentially any sequence of It provides program-level printable characters is allowed; access to control flow via anything that starts a valid continuation functions. number (except + or -) may not start a symbol. Valid symbols include: abc hello-world + <=! Integers: Any sequence of digits, optionally prefixed with a + or -. Usually unlimited in length. © © CS 538 Spring 2008 101 CS 538 Spring 2008 102 Reals: String: A floating point number in a A sequence of characters decimal format (123.456) or in delimited by double quotes. exponential format (1.23e45). A Double quotes and backslashes leading sign and a signed must be escaped using a exponent are allowed backslash. For example (-12.3, 10.0e-20). "Hello World" "\"Wow!\"" Rationals: Character: Rational numbers of the form A single character prefixed by #\. integer/integer (e.g., 1/3 or 9/7) For example, #\a, #\0, #\\, #\#. with an optional leading sign (-1/ Two special characters are 2, +7/8). #\space and #\newline. Complex: Complex numbers of the form Boolean: num+num i or num-num i, where True is represented as #t and num is an integer or real number. false is represented as #f. Example include 1+3i, -1.5- 2.5i, 0+1i). © © CS 538 Spring 2008 103 CS 538 Spring 2008 104 Binary Trees Binary trees are also called C A S-Expressions in Lisp and Scheme. They are of the form A B B C ( item . item ) S-Expressions are built and where item is any atomic value or any S-Expression. For example: accessed using the predefined functions cons, car and cdr. ( A . B ) (1.2 . "xyz" ) cons builds a new S-Expression ( (A . B ) . C ) from two S-Expressions that ( A . (B . C ) ) represent the left and right children. S-Expressions are linearizations of binary trees: cons(E1,E2) = (E1 . E2) car returns are left subtree of an S-Expression. A B 1.2 "xyz" car (E1 . E2) = E1 cdr returns are right subtree of an S-Expression. cdr (E1 . E2) = E2 © © CS 538 Spring 2008 105 CS 538 Spring 2008 106 Lists Function Calls In Lisp and Scheme lists are a In List and Scheme, function calls special, widely-used form of S- are represented as lists. Expressions. (A B C) means: () represents the empty or null list Evaluate A (to a function) (A) is the list containing A. By definition, (A) ≡ (A . () ) Evaluate B and C (as parameters) (A B) represents the list Call A with B and C as its containing A and B. By definition, parameters (A B) ≡ (A . (B . () ) ) Use the value returned by the call In general, (A B C ... Z) ≡ as the “meaning” of (A B C). (A . (B . (C . ... (Z . () ) ... ))) cons, car and cdr are predefined symbols bound to built-in (A B C )≡ functions that build and access lists and S-Expressions. A Literals (of type integer, real, rational, complex, string, B character and boolean) evaluate to themselves. C() © © CS 538 Spring 2008 107 CS 538 Spring 2008 108 For example (⇒ means “evaluates Thus (quote (1 2)) doesn’t try to”) to evaluate the list (1 2); it just (cons 1 2) ⇒ (1 . 2) returns it. Since quotation is so often used, (cons 1 () ) ⇒ (1) it may be abbreviated using a (car (cons 1 2)) ⇒ 1 single quote. That is (cdr (cons 1 ())) ⇒ () (quote arg) ≡ 'arg But, Thus (car (1 2)) fails during (car '(a b c)) ⇒ a execution! (cdr '( (A) (B) (C))) ⇒ Why? ( (B) (C) ) The expression (1 2) looks like a (cons 'a '1) ⇒ (a . 1) call, but 1 isn’t a function! We need some way to “quote” But, symbols and lists we don’t want ('cdr '(A B)) fails! evaluated. Why? (quote arg) is a special function that returns its argument unevaluated. © © CS 538 Spring 2008 109 CS 538 Spring 2008 110 User-defined Functions We can bind values and functions to global symbols The list using the define function. (lambda (args) (body)) The general form is evaluates to a function with (define id object) (args) as its argument list and id is not evaluated but object (body) as the function body. is. id is bound to the value No quotes are needed for object evaluates to. (args) or (body). For example, Thus (define pi 3.1415926535) (lambda (x) (+ x 1)) evaluates (define plus1 to the increment function. (lambda (x) (+ x 1)) ) Similarly, (define pi*2 (* pi 2)) ((lambda (x) (+ x 1)) 10) ⇒ Once a symbol is defined, it 11 evaluates to the value it is bound to: (plus1 12) ⇒ 13 © © CS 538 Spring 2008 111 CS 538 Spring 2008 112 Since functions are frequently Conditional Expressions in defined, we may abbreviate Scheme (define id (lambda (args) (body)) ) A predicate is a function that as returns a boolean value. By convention, in Scheme, predicate (define (id args) (body) ) names end with “?” Thus For example, (define (plus1 x) (+ x 1)) number? symbol? equal? null? list? In conditionals, #f is false, and everything else, including #t, is true. The if expression is (if pred E1 E2) First pred is evaluated. Depending on its value (#f or not), either E1 or E2 is evaluated (but not both) and returned as the value of the if expression. © © CS 538 Spring 2008 113 CS 538 Spring 2008 114 For example, Generalized Conditional (if (= 1 (+ 0 1)) 'Yes This is similar to a switch or case: 'No (cond ) (p1 e1) (p2 e2) ... (define (fact n) (else en) (if (= n 0) ) 1 Each of the predicates (p1, p2, ...) (* n (fact (- n 1))) is evaluated until one is true (≠ ) #f). Then the corresponding ) expression (e1, e2, ...) is evaluated and returned as the value of the cond. else acts like a predicate that is always true. Example: (cond ((= a 1) 2) ((= a 2) 3) (else 4) ) © © CS 538 Spring 2008 115 CS 538 Spring 2008 116.
Load more

Recommended publications
  • The Pros of Cons: Programming with Pairs and Lists
    The Pros of cons: Programming with Pairs and Lists CS251 Programming Languages Spring 2016, Lyn Turbak Department of Computer Science Wellesley College Racket Values • booleans: #t, #f • numbers: – integers: 42, 0, -273 – raonals: 2/3, -251/17 – floang point (including scien3fic notaon): 98.6, -6.125, 3.141592653589793, 6.023e23 – complex: 3+2i, 17-23i, 4.5-1.4142i Note: some are exact, the rest are inexact. See docs. • strings: "cat", "CS251", "αβγ", "To be\nor not\nto be" • characters: #\a, #\A, #\5, #\space, #\tab, #\newline • anonymous func3ons: (lambda (a b) (+ a (* b c))) What about compound data? 5-2 cons Glues Two Values into a Pair A new kind of value: • pairs (a.k.a. cons cells): (cons v1 v2) e.g., In Racket, - (cons 17 42) type Command-\ to get λ char - (cons 3.14159 #t) - (cons "CS251" (λ (x) (* 2 x)) - (cons (cons 3 4.5) (cons #f #\a)) Can glue any number of values into a cons tree! 5-3 Box-and-pointer diagrams for cons trees (cons v1 v2) v1 v2 Conven3on: put “small” values (numbers, booleans, characters) inside a box, and draw a pointers to “large” values (func3ons, strings, pairs) outside a box. (cons (cons 17 (cons "cat" #\a)) (cons #t (λ (x) (* 2 x)))) 17 #t #\a (λ (x) (* 2 x)) "cat" 5-4 Evaluaon Rules for cons Big step seman3cs: e1 ↓ v1 e2 ↓ v2 (cons) (cons e1 e2) ↓ (cons v1 v2) Small-step seman3cs: (cons e1 e2) ⇒* (cons v1 e2); first evaluate e1 to v1 step-by-step ⇒* (cons v1 v2); then evaluate e2 to v2 step-by-step 5-5 cons evaluaon example (cons (cons (+ 1 2) (< 3 4)) (cons (> 5 6) (* 7 8))) ⇒ (cons (cons 3 (< 3 4))
    [Show full text]
  • The Use of UML for Software Requirements Expression and Management
    The Use of UML for Software Requirements Expression and Management Alex Murray Ken Clark Jet Propulsion Laboratory Jet Propulsion Laboratory California Institute of Technology California Institute of Technology Pasadena, CA 91109 Pasadena, CA 91109 818-354-0111 818-393-6258 [email protected] [email protected] Abstract— It is common practice to write English-language 1. INTRODUCTION ”shall” statements to embody detailed software requirements in aerospace software applications. This paper explores the This work is being performed as part of the engineering of use of the UML language as a replacement for the English the flight software for the Laser Ranging Interferometer (LRI) language for this purpose. Among the advantages offered by the of the Gravity Recovery and Climate Experiment (GRACE) Unified Modeling Language (UML) is a high degree of clarity Follow-On (F-O) mission. However, rather than use the real and precision in the expression of domain concepts as well as project’s model to illustrate our approach in this paper, we architecture and design. Can this quality of UML be exploited have developed a separate, ”toy” model for use here, because for the definition of software requirements? this makes it easier to avoid getting bogged down in project details, and instead to focus on the technical approach to While expressing logical behavior, interface characteristics, requirements expression and management that is the subject timeliness constraints, and other constraints on software using UML is commonly done and relatively straight-forward, achiev- of this paper. ing the additional aspects of the expression and management of software requirements that stakeholders expect, especially There is one exception to this choice: we will describe our traceability, is far less so.
    [Show full text]
  • Java for Scientific Computing, Pros and Cons
    Journal of Universal Computer Science, vol. 4, no. 1 (1998), 11-15 submitted: 25/9/97, accepted: 1/11/97, appeared: 28/1/98 Springer Pub. Co. Java for Scienti c Computing, Pros and Cons Jurgen Wol v. Gudenb erg Institut fur Informatik, Universitat Wurzburg wol @informatik.uni-wuerzburg.de Abstract: In this article we brie y discuss the advantages and disadvantages of the language Java for scienti c computing. We concentrate on Java's typ e system, investi- gate its supp ort for hierarchical and generic programming and then discuss the features of its oating-p oint arithmetic. Having found the weak p oints of the language we pro- p ose workarounds using Java itself as long as p ossible. 1 Typ e System Java distinguishes b etween primitive and reference typ es. Whereas this distinc- tion seems to b e very natural and helpful { so the primitives which comprise all standard numerical data typ es have the usual value semantics and expression concept, and the reference semantics of the others allows to avoid p ointers at all{ it also causes some problems. For the reference typ es, i.e. arrays, classes and interfaces no op erators are available or may b e de ned and expressions can only b e built by metho d calls. Several variables may simultaneously denote the same ob ject. This is certainly strange in a numerical setting, but not to avoid, since classes have to b e used to intro duce higher data typ es. On the other hand, the simple hierarchy of classes with the ro ot Object clearly b elongs to the advantages of the language.
    [Show full text]
  • A Metaobject Protocol for Fault-Tolerant CORBA Applications
    A Metaobject Protocol for Fault-Tolerant CORBA Applications Marc-Olivier Killijian*, Jean-Charles Fabre*, Juan-Carlos Ruiz-Garcia*, Shigeru Chiba** *LAAS-CNRS, 7 Avenue du Colonel Roche **Institute of Information Science and 31077 Toulouse cedex, France Electronics, University of Tsukuba, Tennodai, Tsukuba, Ibaraki 305-8573, Japan Abstract The corner stone of a fault-tolerant reflective The use of metalevel architectures for the architecture is the MOP. We thus propose a special implementation of fault-tolerant systems is today very purpose MOP to address the problems of general-purpose appealing. Nevertheless, all such fault-tolerant systems ones. We show that compile-time reflection is a good have used a general-purpose metaobject protocol (MOP) approach for developing a specialized runtime MOP. or are based on restricted reflective features of some The definition and the implementation of an object-oriented language. According to our past appropriate runtime metaobject protocol for implementing experience, we define in this paper a suitable metaobject fault tolerance into CORBA applications is the main protocol, called FT-MOP for building fault-tolerant contribution of the work reported in this paper. This systems. We explain how to realize a specialized runtime MOP, called FT-MOP (Fault Tolerance - MetaObject MOP using compile-time reflection. This MOP is CORBA Protocol), is sufficiently general to be used for other aims compliant: it enables the execution and the state evolution (mobility, adaptability, migration, security). FT-MOP of CORBA objects to be controlled and enables the fault provides a mean to attach dynamically fault tolerance tolerance metalevel to be developed as CORBA software. strategies to CORBA objects as CORBA metaobjects, enabling thus these strategies to be implemented as 1 .
    [Show full text]
  • Chapter 15 Functional Programming
    Topics Chapter 15 Numbers n Natural numbers n Haskell numbers Functional Programming Lists n List notation n Lists as a data type n List operations Chapter 15: Functional Programming 2 Numbers Natural Numbers The natural numbers are the numbers 0, 1, Haskell provides a sophisticated 2, and so on, used for counting. hierarchy of type classes for describing various kinds of numbers. Introduced by the declaration data Nat = Zero | Succ Nat Although (some) numbers are provided n The constructor Succ (short for ‘successor’) as primitives data types, it is has type Nat à Nat. theoretically possible to introduce them n Example: as an element of Nat the number 7 through suitable data type declarations. would be represented by Succ(Succ(Succ(Succ(Succ(Succ(Succ Zero)))))) Chapter 15: Functional Programming 3 Chapter 15: Functional Programming 4 Natural Numbers Natural Numbers Every natural number is represented by a Multiplication ca be defined by unique value of Nat. (x) :: Nat à Nat à Nat m x Zero = Zero On the other hand, not every value of Nat m x Succ n = (m x n) + m represents a well-defined natural number. n Example: ^, Succ ^, Succ(Succ ^) Nat can be a member of the type class Eq Addition ca be defined by instance Eq Nat where Zero == Zero = True (+) :: Nat à Nat à Nat Zero == Succ n = False m + Zero = m Succ m == Zero = False m + Succ n = Succ(m + n) Succ m == Succ n = (m == n) Chapter 15: Functional Programming 5 Chapter 15: Functional Programming 6 1 Natural Numbers Haskell Numbers Nat can be a member of the type class Ord instance
    [Show full text]
  • Subtyping on Nested Polymorphic Session Types 3 Types [38]
    Subtyping on Nested Polymorphic Session Types Ankush Das1, Henry DeYoung1, Andreia Mordido2, and Frank Pfenning1 1 Carnegie Mellon University, USA 2 LASIGE, Faculdade de Ciˆencias, Universidade de Lisboa, Portugal Abstract. The importance of subtyping to enable a wider range of well- typed programs is undeniable. However, the interaction between subtyp- ing, recursion, and polymorphism is not completely understood yet. In this work, we explore subtyping in a system of nested, recursive, and polymorphic types with a coinductive interpretation, and we prove that this problem is undecidable. Our results will be broadly applicable, but to keep our study grounded in a concrete setting, we work with an extension of session types with explicit polymorphism, parametric type construc- tors, and nested types. We prove that subtyping is undecidable even for the fragment with only internal choices and nested unary recursive type constructors. Despite this negative result, we present a subtyping algo- rithm for our system and prove its soundness. We minimize the impact of the inescapable incompleteness by enabling the programmer to seed the algorithm with subtyping declarations (that are validated by the al- gorithm). We have implemented the proposed algorithm in Rast and it showed to be efficient in various example programs. 1 Introduction Subtyping is a standard feature in modern programming languages, whether functional, imperative, or object-oriented. The two principal approaches to un- derstanding the meaning of subtyping is via coercions or as subsets. Either way, subtyping allows more programs as well-typed, programs can be more concise, and types can express more informative properties of programs. When it comes to the interaction between advanced features of type systems, specifically recursive and polymorphic types, there are still some gaps in our arXiv:2103.15193v1 [cs.PL] 28 Mar 2021 understanding of subtyping.
    [Show full text]
  • Estacada City Council Estacada City Hall, Council Chambers 475 Se Main Street, Estacada, Oregon Monday, January 25, 2016 - 7:00 Pm
    CITY OF ESTACADA AGENDA MAYOR BRENT DODRILL COUNCILOR SEAN DRINKWINE COUNCILOR LANELLE KING COUNCILOR AARON GANT COUNCILOR PAULINA MENCHACA COUNCILOR JUSTIN GATES COUNCILOR DAN NEUJAHR ESTACADA CITY COUNCIL ESTACADA CITY HALL, COUNCIL CHAMBERS 475 SE MAIN STREET, ESTACADA, OREGON MONDAY, JANUARY 25, 2016 - 7:00 PM 1. CALL TO ORDER BY PRESIDING OFFICER (An invocation will be offered prior to call to order) . Pledge of Allegiance . Roll Call 2. CITIZEN AND COMMUNITY GROUP COMMENTS Instructions for providing testimony are located above the information table and the back of this agenda 3. CONSENT AGENDA Council members have the opportunity to move items from the Consent Agenda to Council Business. Council actions are taken in one motion on Consent Agenda Items. a. Approve January 11, 2016 Council minutes b. Approve January 16, 2016 Council Retreat minutes c. System Development Charge Annual Report 2015 Estacada Urban Renewal District Annual Report 2014-15 d. OLCC Annual Renewals 4. DEPARTMENT & COMMITTEE REPORTS a. Committee, Commission and Liaison b. City Manager Report c. Mayor Report 5. COUNCIL BUSINESS Items may be added from the Consent Agenda upon request of the Mayor or Councilor. a. SECOND CONSIDERATION – Ordinance Series of 2016 – 001 – An ordinance amending Section 5.04.020 D. of the Estacada Municipal Code regarding business and occupation licenses. b. 2016 Council Goals 6. CITIZEN AND COMMUNITY GROUP COMMENTS Instructions for providing testimony are located above the information table and the back of this agenda 7. COUNCIL REPORTS & COMMENTS 8. ADJOURNMENT OF MEETING Estacada City Council Meeting January 11, 2016 – Page | 1 ESTACADA CITY COUNCIL MEETING MINUTES ESTACADA CITY HALL, COUNCIL CHAMBERS 475 SE MAIN STREET, ESTACADA, OREGON MONDAY, JANUARY 11, 2016 - 7:00 PM CALL TO ORDER BY PRESIDING OFFICER The meeting was called to order at 7:00pm.
    [Show full text]
  • CONS Should Not CONS Its Arguments, Or, a Lazy Alloc Is a Smart Alloc Henry G
    CONS Should not CONS its Arguments, or, a Lazy Alloc is a Smart Alloc Henry G. Baker Nimble Computer Corporation, 16231 Meadow Ridge Way, Encino, CA 91436, (818) 501-4956 (818) 986-1360 (FAX) November, 1988; revised April and December, 1990, November, 1991. This work was supported in part by the U.S. Department of Energy Contract No. DE-AC03-88ER80663 Abstract semantics, and could profitably utilize stack allocation. One would Lazy allocation is a model for allocating objects on the execution therefore like to provide stack allocation for these objects, while stack of a high-level language which does not create dangling reserving the more expensive heap allocation for those objects that references. Our model provides safe transportation into the heap for require it. In other words, one would like an implementation which objects that may survive the deallocation of the surrounding stack retains the efficiency of stack allocation for most objects, and frame. Space for objects that do not survive the deallocation of the therefore does not saddle every program with the cost for the surrounding stack frame is reclaimed without additional effort when increased flexibility--whether the program uses that flexibility or the stack is popped. Lazy allocation thus performs a first-level not. garbage collection, and if the language supports garbage collection The problem in providing such an implementation is in determining of the heap, then our model can reduce the amortized cost of which objects obey LIFO allocation semantics and which do not. allocation in such a heap by filtering out the short-lived objects that Much research has been done on determining these objects at can be more efficiently managed in LIFO order.
    [Show full text]
  • First-Class Functions and Patterns
    First-class Functions and Patterns Corky Cartwright Stephen Wong Department of Computer Science Rice University 1 Encoding First-class Functions in Java • Java methods are not data values; they cannot be used as values. • But java classes include methods so we can implicitly pass methods (functions) by passing class instances containing the desired method code. • Moreover, Java includes a mechanism that closes over the free variables in the method definition! • Hence, first-class functions (closures) are available implicitly, but the syntax is wordy. • Example: Scheme map 2 Interfaces for Representing Functions For accurate typing, we need different interfaces for different arities. With generics, we can define parameterized interfaces for each arity. In the absence of generics, we will have to define separate interfaces for each desired typing. map example: /** The type of unary functions in Object -> Object. */ interface Lambda { Object apply(Object arg); } abstract class ObjectList { ObjectList cons(Object n) { return new ConsObjectList(n, this); } abstract ObjectList map(Lambda f); } ... 3 Representing Specific Functions • For each function that we want to use a value, we must define a class, preferably a singleton. Since the class has no fields, all instances are effectively identical. • Defining a class seems unduly heavyweight, but it works in principle. • In OO parlance, an instance of such a class is called a strategy. • Java provides a lightweight notation for singleton classes called anonymous classes. Moreover these classes can refer to fields and final method variables that are in scope. In DrJava language levels, all variables are final. final fields and variables cannot be rebound to new values after they are initially defined (immutable).
    [Show full text]
  • Floating Point Computation (Slides 1–123)
    UNIVERSITY OF CAMBRIDGE Floating Point Computation (slides 1–123) A six-lecture course D J Greaves (thanks to Alan Mycroft) Computer Laboratory, University of Cambridge http://www.cl.cam.ac.uk/teaching/current/FPComp Lent 2010–11 Floating Point Computation 1 Lent 2010–11 A Few Cautionary Tales UNIVERSITY OF CAMBRIDGE The main enemy of this course is the simple phrase “the computer calculated it, so it must be right”. We’re happy to be wary for integer programs, e.g. having unit tests to check that sorting [5,1,3,2] gives [1,2,3,5], but then we suspend our belief for programs producing real-number values, especially if they implement a “mathematical formula”. Floating Point Computation 2 Lent 2010–11 Global Warming UNIVERSITY OF CAMBRIDGE Apocryphal story – Dr X has just produced a new climate modelling program. Interviewer: what does it predict? Dr X: Oh, the expected 2–4◦C rise in average temperatures by 2100. Interviewer: is your figure robust? ... Floating Point Computation 3 Lent 2010–11 Global Warming (2) UNIVERSITY OF CAMBRIDGE Apocryphal story – Dr X has just produced a new climate modelling program. Interviewer: what does it predict? Dr X: Oh, the expected 2–4◦C rise in average temperatures by 2100. Interviewer: is your figure robust? Dr X: Oh yes, indeed it gives results in the same range even if the input data is randomly permuted . We laugh, but let’s learn from this. Floating Point Computation 4 Lent 2010–11 Global Warming (3) UNIVERSITY OF What could cause this sort or error? CAMBRIDGE the wrong mathematical model of reality (most subject areas lack • models as precise and well-understood as Newtonian gravity) a parameterised model with parameters chosen to fit expected • results (‘over-fitting’) the model being very sensitive to input or parameter values • the discretisation of the continuous model for computation • the build-up or propagation of inaccuracies caused by the finite • precision of floating-point numbers plain old programming errors • We’ll only look at the last four, but don’t forget the first two.
    [Show full text]
  • Program Verification with Why3, IV
    Program verification with Why3, IV Marc Schoolderman February 28, 2019 Meh... Last exercise How useful are the counter-examples? 2 Last exercise How useful are the counter-examples? Meh... 2 Last exercise Does this function match its specification? Formal verification Is the specification correct? Validation What if the specification itself has functions? Informal meta-argumentation Formal validation? 3 Aliasing issues Aliasing and mutability Compare this: let main (a: array int) requires { length a > 0 } = letb=a in a[0] <- 5; b[0] <- 42 and this: let main (a: array int) requires { length a > 0 } = let b = copy a in a[0] <- 5; b[0] <- 42 4 What happens now? let main () = let x = ref 5 in combine x x; assert { !x = 10 /\ !x = 0 } (* ?? *) WhyML forbids this kind of aliassing! Aliasing and function arguments This is perfectly reasonable: let combine (x y: ref int) ensures { !x = old (!x + !y) } ensures { !y = 0 } = x := !x + !y; y := 0 5 WhyML forbids this kind of aliassing! Aliasing and function arguments This is perfectly reasonable: let combine (x y: ref int) ensures { !x = old (!x + !y) } ensures { !y = 0 } = x := !x + !y; y := 0 What happens now? let main () = let x = ref 5 in combine x x; assert { !x = 10 /\ !x = 0 } (* ?? *) 5 Aliasing and function arguments This is perfectly reasonable: let combine (x y: ref int) ensures { !x = old (!x + !y) } ensures { !y = 0 } = x := !x + !y; y := 0 What happens now? let main () = let x = ref 5 in combine x x; assert { !x = 10 /\ !x = 0 } (* ?? *) WhyML forbids this kind of aliassing! 5 Then we
    [Show full text]
  • ED027743.Pdf
    DOCUMENT RESUME ED 027 743 EM 007 134 By-Fasana, Paul J., Ed.; Shank, Russell, Ed. Tutorial on Generalized Programming Language s and Systems. Instructor Edition. American Society for Information Science, Washington, D.C. Spons Agency-National Science Foundation, Washington, D.C. Pub Date Jul 68 Grant- F -NSF -GN -657 Note-65p.; Manual based on materials prepared and presented by Thomas K. Burgess and others at the Annual Convention of the American Society for Information Science (New York, October 22-26, 1967) EDRS Price MF-$0.50 HC-$3.35 Descriptors-*Computer Science, *Computer Science Education, Information Retrieval, Information Storage, *Manuals Identifiers-COBOL, FORTRAN, PL I, SNOBOL This instructor's manual is a comparative analysis and review of the various computer programing languagescurrentlyavailable andtheircapabilitiesfor performing text manipulation, information storage, and data retrieval tasks. Based on materials presented at the 1967 Convention of the American Society for Information Science,themanualdescribes FORTRAN, a language designedprimarilyfor mathematicalcomputation;SNOBOL, alist-processinglanguagedesignedfor information retrieval application; COBOL, a business oriented language; and PL/L a new language incorporating many of the desirable features of FORTRAN andCOBOL but as yet implemented only for the IBM 360 computer system. (TI) U.S. DEPARTMENT OF HEALTH, EDUCATION & WELFARE OFFICE OF EDUCATION Pek THIS DOCUMENT HAS BEEN REPRODUCED EXACTLY AS RECEIVED FROM THE N. PERSON OR ORGANIZATION ORIGINATING IT.POINTS Of VIEW OR OPINIONS rJ STATED DO NOT NECESSARILY REPRESENT OFFICIAL OFFICE OF EDUCATION TUTORIAL ON POSITION OR POLICY. GENERALIZED PROGRAMMING LANGUAGES AND SYSTEMS Instructor Edition. Edited by Paul J. Fasana Columbia University Libraries New York, N. Y. and Russell Shank The Smithsonian Institution Washington, D.
    [Show full text]