Control Statements
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Layout-Sensitive Generalized Parsing
Layout-sensitive Generalized Parsing Sebastian Erdweg, Tillmann Rendel, Christian K¨astner,and Klaus Ostermann University of Marburg, Germany Abstract. The theory of context-free languages is well-understood and context-free parsers can be used as off-the-shelf tools in practice. In par- ticular, to use a context-free parser framework, a user does not need to understand its internals but can specify a language declaratively as a grammar. However, many languages in practice are not context-free. One particularly important class of such languages is layout-sensitive languages, in which the structure of code depends on indentation and whitespace. For example, Python, Haskell, F#, and Markdown use in- dentation instead of curly braces to determine the block structure of code. Their parsers (and lexers) are not declaratively specified but hand-tuned to account for layout-sensitivity. To support declarative specifications of layout-sensitive languages, we propose a parsing framework in which a user can annotate layout in a grammar. Annotations take the form of constraints on the relative posi- tioning of tokens in the parsed subtrees. For example, a user can declare that a block consists of statements that all start on the same column. We have integrated layout constraints into SDF and implemented a layout- sensitive generalized parser as an extension of generalized LR parsing. We evaluate the correctness and performance of our parser by parsing 33 290 open-source Haskell files. Layout-sensitive generalized parsing is easy to use, and its performance overhead compared to layout-insensitive parsing is small enough for practical application. 1 Introduction Most computer languages prescribe a textual syntax. -
7. Control Flow First?
Copyright (C) R.A. van Engelen, FSU Department of Computer Science, 2000-2004 Ordering Program Execution: What is Done 7. Control Flow First? Overview Categories for specifying ordering in programming languages: Expressions 1. Sequencing: the execution of statements and evaluation of Evaluation order expressions is usually in the order in which they appear in a Assignments program text Structured and unstructured flow constructs 2. Selection (or alternation): a run-time condition determines the Goto's choice among two or more statements or expressions Sequencing 3. Iteration: a statement is repeated a number of times or until a Selection run-time condition is met Iteration and iterators 4. Procedural abstraction: subroutines encapsulate collections of Recursion statements and subroutine calls can be treated as single Nondeterminacy statements 5. Recursion: subroutines which call themselves directly or indirectly to solve a problem, where the problem is typically defined in terms of simpler versions of itself 6. Concurrency: two or more program fragments executed in parallel, either on separate processors or interleaved on a single processor Note: Study Chapter 6 of the textbook except Section 7. Nondeterminacy: the execution order among alternative 6.6.2. constructs is deliberately left unspecified, indicating that any alternative will lead to a correct result Expression Syntax Expression Evaluation Ordering: Precedence An expression consists of and Associativity An atomic object, e.g. number or variable The use of infix, prefix, and postfix notation leads to ambiguity An operator applied to a collection of operands (or as to what is an operand of what arguments) which are expressions Fortran example: a+b*c**d**e/f Common syntactic forms for operators: The choice among alternative evaluation orders depends on Function call notation, e.g. -
A Survey of Hardware-Based Control Flow Integrity (CFI)
A survey of Hardware-based Control Flow Integrity (CFI) RUAN DE CLERCQ∗ and INGRID VERBAUWHEDE, KU Leuven Control Flow Integrity (CFI) is a computer security technique that detects runtime attacks by monitoring a program’s branching behavior. This work presents a detailed analysis of the security policies enforced by 21 recent hardware-based CFI architectures. The goal is to evaluate the security, limitations, hardware cost, performance, and practicality of using these policies. We show that many architectures are not suitable for widespread adoption, since they have practical issues, such as relying on accurate control flow model (which is difficult to obtain) or they implement policies which provide only limited security. CCS Concepts: • Security and privacy → Hardware-based security protocols; Information flow control; • General and reference → Surveys and overviews; Additional Key Words and Phrases: control-flow integrity, control-flow hijacking, return oriented programming, shadow stack ACM Reference format: Ruan de Clercq and Ingrid Verbauwhede. YYYY. A survey of Hardware-based Control Flow Integrity (CFI). ACM Comput. Surv. V, N, Article A (January YYYY), 27 pages. https://doi.org/10.1145/nnnnnnn.nnnnnnn 1 INTRODUCTION Today, a lot of software is written in memory unsafe languages, such as C and C++, which introduces memory corruption bugs. This makes software vulnerable to attack, since attackers exploit these bugs to make the software misbehave. Modern Operating Systems (OSs) and microprocessors are equipped with security mechanisms to protect against some classes of attacks. However, these mechanisms cannot defend against all attack classes. In particular, Code Reuse Attacks (CRAs), which re-uses pre-existing software for malicious purposes, is an important threat that is difficult to protect against. -
Parse Forest Diagnostics with Dr. Ambiguity
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by CWI's Institutional Repository Parse Forest Diagnostics with Dr. Ambiguity H. J. S. Basten and J. J. Vinju Centrum Wiskunde & Informatica (CWI) Science Park 123, 1098 XG Amsterdam, The Netherlands {Jurgen.Vinju,Bas.Basten}@cwi.nl Abstract In this paper we propose and evaluate a method for locating causes of ambiguity in context-free grammars by automatic analysis of parse forests. A parse forest is the set of parse trees of an ambiguous sentence. Deducing causes of ambiguity from observing parse forests is hard for grammar engineers because of (a) the size of the parse forests, (b) the complex shape of parse forests, and (c) the diversity of causes of ambiguity. We first analyze the diversity of ambiguities in grammars for programming lan- guages and the diversity of solutions to these ambiguities. Then we introduce DR.AMBIGUITY: a parse forest diagnostics tools that explains the causes of ambiguity by analyzing differences between parse trees and proposes solutions. We demonstrate its effectiveness using a small experiment with a grammar for Java 5. 1 Introduction This work is motivated by the use of parsers generated from general context-free gram- mars (CFGs). General parsing algorithms such as GLR and derivates [35,9,3,6,17], GLL [34,22], and Earley [16,32] support parser generation for highly non-deterministic context-free grammars. The advantages of constructing parsers using such technology are that grammars may be modular and that real programming languages (often requiring parser non-determinism) can be dealt with efficiently1. -
Control-Flow Analysis of Functional Programs
Control-flow analysis of functional programs JAN MIDTGAARD Department of Computer Science, Aarhus University We present a survey of control-flow analysis of functional programs, which has been the subject of extensive investigation throughout the past 30 years. Analyses of the control flow of functional programs have been formulated in multiple settings and have led to many different approximations, starting with the seminal works of Jones, Shivers, and Sestoft. In this paper, we survey control-flow analysis of functional programs by structuring the multitude of formulations and approximations and comparing them. Categories and Subject Descriptors: D.3.2 [Programming Languages]: Language Classifica- tions—Applicative languages; F.3.1 [Logics and Meanings of Programs]: Specifying and Ver- ifying and Reasoning about Programs General Terms: Languages, Theory, Verification Additional Key Words and Phrases: Control-flow analysis, higher-order functions 1. INTRODUCTION Since the introduction of high-level languages and compilers, much work has been devoted to approximating, at compile time, which values the variables of a given program may denote at run time. The problem has been named data-flow analysis or just flow analysis. In a language without higher-order functions, the operator of a function call is apparent from the text of the program: it is a lexically visible identifier and therefore the called function is available at compile time. One can thus base an analysis for such a language on the textual structure of the program, since it determines the exact control flow of the program, e.g., as a flow chart. On the other hand, in a language with higher-order functions, the operator of a function call may not be apparent from the text of the program: it can be the result of a computation and therefore the called function may not be available until run time. -
Formal Languages - 3
Formal Languages - 3 • Ambiguity in PLs – Problems with if-then-else constructs – Harder problems • Chomsky hierarchy for formal languages – Regular and context-free languages – Type 1: Context-sensitive languages – Type 0 languages and Turing machines Formal Languages-3, CS314 Fall 01© BGRyder 1 Dangling Else Ambiguity (Pascal) Start ::= Stmt Stmt ::= Ifstmt | Astmt Ifstmt ::= IF LogExp THEN Stmt | IF LogExp THEN Stmt ELSE Stmt Astmt ::= Id := Digit Digit ::= 0|1|2|3|4|5|6|7|8|9 LogExp::= Id = 0 Id ::= a|b|c|d|e|f|g|h|i|j|k|l|m|n|o|p|q|r|s|t|u|v|w|x|y|z How are compound if statements parsed using this grammar?? Formal Languages-3, CS314 Fall 01© BGRyder 2 1 IF x = 0 THEN IF y = 0 THEN z := 1 ELSE w := 2; Start Parse Tree 1 Stmt Ifstmt IF LogExp THEN Stmt Ifstmt Id = 0 IF LogExp THEN Stmt ELSE Stmt x Id = 0 Astmt Astmt Id := Digit y Id := Digit z 1 w 2 Formal Languages-3, CS314 Fall 01© BGRyder 3 IF x = 0 THEN IF y = 0 THEN z := 1 ELSE w := 2; Start Stmt Parse Tree 2 Ifstmt Q: which tree is correct? IF LogExp THEN Stmt ELSE Stmt Id = 0 Ifstmt Astmt IF LogExp THEN Stmt x Id := Digit Astmt Id = 0 w 2 Id := Digit y z 1 Formal Languages-3, CS314 Fall 01© BGRyder 4 2 How Solve the Dangling Else? • Algol60: use block structure if x = 0 then begin if y = 0 then z := 1 end else w := 2 • Algol68: use statement begin/end markers if x = 0 then if y = 0 then z := 1 fi else w := 2 fi • Pascal: change the if statement grammar to disallow parse tree 2; that is, always associate an else with the closest if Formal Languages-3, CS314 Fall 01© BGRyder 5 New Pascal Grammar Start ::= Stmt Stmt ::= Stmt1 | Stmt2 Stmt1 ::= IF LogExp THEN Stmt1 ELSE Stmt1 | Astmt Stmt2 ::= IF LogExp THEN Stmt | IF LogExp THEN Stmt1 ELSE Stmt2 Astmt ::= Id := Digit Digit ::= 0|1|2|3|4|5|6|7|8|9 LogExp::= Id = 0 Id ::= a|b|c|d|e|f|g|h|i|j|k|l|m|n|o|p|q|r|s|t|u|v|w|x|y|z Note: only if statements with IF..THEN..ELSE are allowed after the THEN clause of an IF-THEN-ELSE statement. -
Ordered Sets in the Calculus of Data Structures
Exercise 1: Balanced Parentheses Show that the following balanced parentheses grammar is ambiguous (by finding two parse trees for some input sequence) and find unambiguous grammar for the same language. B ::= | ( B ) | B B Remark • The same parse tree can be derived using two different derivations, e.g. B -> (B) -> (BB) -> ((B)B) -> ((B)) -> (()) B -> (B) -> (BB) -> ((B)B) -> (()B) -> (()) this correspond to different orders in which nodes in the tree are expanded • Ambiguity refers to the fact that there are actually multiple parse trees, not just multiple derivations. Towards Solution • (Note that we must preserve precisely the set of strings that can be derived) • This grammar: B ::= | A A ::= ( ) | A A | (A) solves the problem with multiple symbols generating different trees, but it is still ambiguous: string ( ) ( ) ( ) has two different parse trees Solution • Proposed solution: B ::= | B (B) • this is very smart! How to come up with it? • Clearly, rule B::= B B generates any sequence of B's. We can also encode it like this: B ::= C* C ::= (B) • Now we express sequence using recursive rule that does not create ambiguity: B ::= | C B C ::= (B) • but now, look, we "inline" C back into the rules for so we get exactly the rule B ::= | B (B) This grammar is not ambiguous and is the solution. We did not prove this fact (we only tried to find ambiguous trees but did not find any). Exercise 2: Dangling Else The dangling-else problem happens when the conditional statements are parsed using the following grammar. S ::= S ; S S ::= id := E S ::= if E then S S ::= if E then S else S Find an unambiguous grammar that accepts the same conditional statements and matches the else statement with the nearest unmatched if. -
14 a Simple Compiler - the Front End
Compilers and Compiler Generators © P.D. Terry, 2000 14 A SIMPLE COMPILER - THE FRONT END At this point it may be of interest to consider the construction of a compiler for a simple programming language, specifically that of section 8.7. In a text of this nature it is impossible to discuss a full-blown compiler, and the value of our treatment may arguably be reduced by the fact that in dealing with toy languages and toy compilers we shall be evading some of the real issues that a compiler writer has to face. However, we hope the reader will find the ensuing discussion of interest, and that it will serve as a useful preparation for the study of much larger compilers. The technique we shall follow is one of slow refinement, supplementing the discussion with numerous asides on the issues that would be raised in compiling larger languages. Clearly, we could opt to develop a completely hand-crafted compiler, or simply to use a tool like Coco/R. We shall discuss both approaches. Even when a compiler is constructed by hand, having an attributed grammar to describe it is very worthwhile. On the source diskette can be found a great deal of code, illustrating different stages of development of our system. Although some of this code is listed in appendices, its volume precludes printing all of it. Some of it has deliberately been written in a way that allows for simple modification when attempting the exercises, and is thus not really of "production quality". For example, in order to allow components such as the symbol table handler and code generator to be used either with hand-crafted or with Coco/R generated systems, some compromises in design have been necessary. -
Disambiguation Filters for Scannerless Generalized LR Parsers
Disambiguation Filters for Scannerless Generalized LR Parsers Mark G. J. van den Brand1,4, Jeroen Scheerder2, Jurgen J. Vinju1, and Eelco Visser3 1 Centrum voor Wiskunde en Informatica (CWI) Kruislaan 413, 1098 SJ Amsterdam, The Netherlands {Mark.van.den.Brand,Jurgen.Vinju}@cwi.nl 2 Department of Philosophy, Utrecht University Heidelberglaan 8, 3584 CS Utrecht, The Netherlands [email protected] 3 Institute of Information and Computing Sciences, Utrecht University P.O. Box 80089, 3508TB Utrecht, The Netherlands [email protected] 4 LORIA-INRIA 615 rue du Jardin Botanique, BP 101, F-54602 Villers-l`es-Nancy Cedex, France Abstract. In this paper we present the fusion of generalized LR pars- ing and scannerless parsing. This combination supports syntax defini- tions in which all aspects (lexical and context-free) of the syntax of a language are defined explicitly in one formalism. Furthermore, there are no restrictions on the class of grammars, thus allowing a natural syntax tree structure. Ambiguities that arise through the use of unrestricted grammars are handled by explicit disambiguation constructs, instead of implicit defaults that are taken by traditional scanner and parser gener- ators. Hence, a syntax definition becomes a full declarative description of a language. Scannerless generalized LR parsing is a viable technique that has been applied in various industrial and academic projects. 1 Introduction Since the introduction of efficient deterministic parsing techniques, parsing is considered a closed topic for research, both by computer scientists and by practi- cioners in compiler construction. Tools based on deterministic parsing algorithms such as LEX & YACC [15,11] (LALR) and JavaCC (recursive descent), are con- sidered adequate for dealing with almost all modern (programming) languages. -
Introduction to Programming Languages and Syntax
Programming Languages Session 1 – Main Theme Programming Languages Overview & Syntax Dr. Jean-Claude Franchitti New York University Computer Science Department Courant Institute of Mathematical Sciences Adapted from course textbook resources Programming Language Pragmatics (3rd Edition) Michael L. Scott, Copyright © 2009 Elsevier 1 Agenda 11 InstructorInstructor andand CourseCourse IntroductionIntroduction 22 IntroductionIntroduction toto ProgrammingProgramming LanguagesLanguages 33 ProgrammingProgramming LanguageLanguage SyntaxSyntax 44 ConclusionConclusion 2 Who am I? - Profile - ¾ 27 years of experience in the Information Technology Industry, including thirteen years of experience working for leading IT consulting firms such as Computer Sciences Corporation ¾ PhD in Computer Science from University of Colorado at Boulder ¾ Past CEO and CTO ¾ Held senior management and technical leadership roles in many large IT Strategy and Modernization projects for fortune 500 corporations in the insurance, banking, investment banking, pharmaceutical, retail, and information management industries ¾ Contributed to several high-profile ARPA and NSF research projects ¾ Played an active role as a member of the OMG, ODMG, and X3H2 standards committees and as a Professor of Computer Science at Columbia initially and New York University since 1997 ¾ Proven record of delivering business solutions on time and on budget ¾ Original designer and developer of jcrew.com and the suite of products now known as IBM InfoSphere DataStage ¾ Creator of the Enterprise -
Obfuscating C++ Programs Via Control Flow Flattening
Annales Univ. Sci. Budapest., Sect. Comp. 30 (2009) 3-19 OBFUSCATING C++ PROGRAMS VIA CONTROL FLOW FLATTENING T. L¶aszl¶oand A.¶ Kiss (Szeged, Hungary) Abstract. Protecting a software from unauthorized access is an ever de- manding task. Thus, in this paper, we focus on the protection of source code by means of obfuscation and discuss the adaptation of a control flow transformation technique called control flow flattening to the C++ lan- guage. In addition to the problems of adaptation and the solutions pro- posed for them, a formal algorithm of the technique is given as well. A prototype implementation of the algorithm presents that the complexity of a program can show an increase as high as 5-fold due to the obfuscation. 1. Introduction Protecting a software from unauthorized access is an ever demanding task. Unfortunately, it is impossible to guarantee complete safety, since with enough time given, there is no unbreakable code. Thus, the goal is usually to make the job of the attacker as di±cult as possible. Systems can be protected at several levels, e.g., hardware, operating system or source code. In this paper, we focus on the protection of source code by means of obfuscation. Several code obfuscation techniques exist. Their common feature is that they change programs to make their comprehension di±cult, while keep- ing their original behaviour. The simplest technique is layout transformation [1], which scrambles identi¯ers in the code, removes comments and debug informa- tion. Another technique is data obfuscation [2], which changes data structures, 4 T. L¶aszl¶oand A.¶ Kiss e.g., by changing variable visibilities or by reordering and restructuring arrays. -
Control Flow Statements
Control Flow Statements Christopher M. Harden Contents 1 Some more types 2 1.1 Undefined and null . .2 1.2 Booleans . .2 1.2.1 Creating boolean values . .3 1.2.2 Combining boolean values . .4 2 Conditional statements 5 2.1 if statement . .5 2.1.1 Using blocks . .5 2.2 else statement . .6 2.3 Tertiary operator . .7 2.4 switch statement . .8 3 Looping constructs 10 3.1 while loop . 10 3.2 do while loop . 11 3.3 for loop . 11 3.4 Further loop control . 12 4 Try it yourself 13 1 1 Some more types 1.1 Undefined and null The undefined type has only one value, undefined. Similarly, the null type has only one value, null. Since both types have only one value, there are no operators on these types. These types exist to represent the absence of data, and their difference is only in intent. • undefined represents data that is accidentally missing. • null represents data that is intentionally missing. In general, null is to be used over undefined in your scripts. undefined is given to you by the JavaScript interpreter in certain situations, and it is useful to be able to notice these situations when they appear. Listing 1 shows the difference between the two. Listing 1: Undefined and Null 1 var name; 2 // Will say"Hello undefined" 3 a l e r t( "Hello" + name); 4 5 name= prompt( "Do not answer this question" ); 6 // Will say"Hello null" 7 a l e r t( "Hello" + name); 1.2 Booleans The Boolean type has two values, true and false.