Symbolic Execution for Software Testing: Three Decades Later
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Chopped Symbolic Execution
Chopped Symbolic Execution David Trabish Andrea Mattavelli Noam Rinetzky Cristian Cadar Tel Aviv University Imperial College London Tel Aviv University Imperial College London Israel United Kingdom Israel United Kingdom [email protected] [email protected] [email protected] [email protected] ABSTRACT the code with symbolic values instead of concrete ones. Symbolic Symbolic execution is a powerful program analysis technique that execution engines thus replace concrete program operations with systematically explores multiple program paths. However, despite ones that manipulate symbols, and add appropriate constraints on important technical advances, symbolic execution often struggles to the symbolic values. In particular, whenever the symbolic executor reach deep parts of the code due to the well-known path explosion reaches a branch condition that depends on the symbolic inputs, it problem and constraint solving limitations. determines the feasibility of both sides of the branch, and creates In this paper, we propose chopped symbolic execution, a novel two new independent symbolic states which are added to a worklist form of symbolic execution that allows users to specify uninter- to follow each feasible side separately. This process, referred to as esting parts of the code to exclude during the analysis, thus only forking, refines the conditions on the symbolic values by adding targeting the exploration to paths of importance. However, the appropriate constraints on each path according to the conditions excluded parts are not summarily ignored, as this may lead to on the branch. Test cases are generated by finding concrete values both false positives and false negatives. Instead, they are executed for the symbolic inputs that satisfy the path conditions. -
Advanced Systems Security: Symbolic Execution
Systems and Internet Infrastructure Security Network and Security Research Center Department of Computer Science and Engineering Pennsylvania State University, University Park PA Advanced Systems Security:! Symbolic Execution Trent Jaeger Systems and Internet Infrastructure Security (SIIS) Lab Computer Science and Engineering Department Pennsylvania State University Systems and Internet Infrastructure Security (SIIS) Laboratory Page 1 Problem • Programs have flaws ‣ Can we find (and fix) them before adversaries can reach and exploit them? • Then, they become “vulnerabilities” Systems and Internet Infrastructure Security (SIIS) Laboratory Page 2 Vulnerabilities • A program vulnerability consists of three elements: ‣ A flaw ‣ Accessible to an adversary ‣ Adversary has the capability to exploit the flaw • Which one should we focus on to find and fix vulnerabilities? ‣ Different methods are used for each Systems and Internet Infrastructure Security (SIIS) Laboratory Page 3 Is It a Flaw? • Problem: Are these flaws? ‣ Failing to check the bounds on a buffer write? ‣ printf(char *n); ‣ strcpy(char *ptr, char *user_data); ‣ gets(char *ptr) • From man page: “Never use gets().” ‣ sprintf(char *s, const char *template, ...) • From gnu.org: “Warning: The sprintf function can be dangerous because it can potentially output more characters than can fit in the allocation size of the string s.” • Should you fix all of these? Systems and Internet Infrastructure Security (SIIS) Laboratory Page 4 Is It a Flaw? • Problem: Are these flaws? ‣ open( filename, O_CREAT ); -
A Scalable Concolic Testing Tool for Reliable Embedded Software
SCORE: a Scalable Concolic Testing Tool for Reliable Embedded Software Yunho Kim and Moonzoo Kim Computer Science Department Korea Advanced Institute of Science and Technology Daejeon, South Korea [email protected], [email protected] ABSTRACT cases to explore execution paths of a program, to achieve full path Current industrial testing practices often generate test cases in a coverage (or at least, coverage of paths up to some bound). manual manner, which degrades both the effectiveness and effi- A concolic testing tool extracts symbolic information from a ciency of testing. To alleviate this problem, concolic testing gen- concrete execution of a target program at runtime. In other words, erates test cases that can achieve high coverage in an automated to build a corresponding symbolic path formula, a concolic testing fashion. One main task of concolic testing is to extract symbolic in- tool monitors every update of symbolic variables and branching de- formation from a concrete execution of a target program at runtime. cisions in an execution of a target program. Thus, a design decision Thus, a design decision on how to extract symbolic information af- on how to extract symbolic information affects efficiency, effective- fects efficiency, effectiveness, and applicability of concolic testing. ness, and applicability of concolic testing. We have developed a Scalable COncolic testing tool for REliable We have developed a Scalable COncolic testing tool for REli- embedded software (SCORE) that targets embedded C programs. abile embedded software (SCORE) that targets sequential embed- SCORE instruments a target C program to extract symbolic infor- ded C programs. SCORE instruments a target C source code by mation and applies concolic testing to a target program in a scal- inserting probes to extract symbolic information at runtime. -
Test Generation Using Symbolic Execution
Test Generation Using Symbolic Execution Patrice Godefroid Microsoft Research [email protected] Abstract This paper presents a short introduction to automatic code-driven test generation using symbolic execution. It discusses some key technical challenges, solutions and milestones, but is not an exhaustive survey of this research area. 1998 ACM Subject Classification D.2.5 Testing and Debugging, D.2.4 Software/Program Veri- fication Keywords and phrases Testing, Symbolic Execution, Verification, Test Generation Digital Object Identifier 10.4230/LIPIcs.FSTTCS.2012.24 1 Automatic Code-Driven Test Generation In this paper, we discuss the problem of automatic code-driven test generation: Given a program with a known set of input parameters, automatically generate a set of input values that will exercise as many program statements as possible. Variants of this problem definition can be obtained using other code coverage criteria [48]. An optimal solution to this problem is theoretically impossible since this problem is undecidable in general (for infinite-state programs written in Turing-expressive programming languages). In practice, approximate solutions are sufficient. Although automating test generation using program analysis is an old idea (e.g., [41]), practical tools have only started to emerge during the last few years. Indeed, the expensive sophisticated program-analysis techniques required to tackle the problem, such as symbolic execution engines and constraint solvers, have only become computationally affordable in recent years thanks to the increasing computational power available on modern computers. Moreover, this steady increase in computational power has in turn enabled recent progress in the engineering of more practical software analysis techniques. Specifically, this recent progress was enabled by new advances in dynamic test generation [29], which generalizes and is more powerful than static test generation, as explained later in this paper. -
Automated Concolic Testing of Smartphone Apps
Automated Concolic Testing of Smartphone Apps Saswat Anand Mayur Naik Hongseok Yang Georgia Tech Georgia Tech University of Oxford [email protected] [email protected] [email protected] Mary Jean Harrold Georgia Tech [email protected] ABSTRACT tap on the device’s touch screen, a key press on the device’s We present an algorithm and a system for generating in- keyboard, and an 0,0 message are all instances of events. put events to exercise smartphone apps. Our approach is This paper presents an algorithm and a system for gener- based on concolic testing and generates sequences of events ating input events to exercise apps. pps can have inputs automatically and systematically. It alleviates the path- besides events! such as files on disk and secure web content. explosion problem by checking a condition on program exe- Our work is orthogonal and complementary to approaches cutions that identifies subsumption between different event that provide such inputs. sequences. We also describe our implementation of the ap- Apps are instances of a class of programs we call event- proach for Android, the most popular smartphone app plat- driven programs' programs embodying computation that form! and the results of an evaluation that demonstrates its is architected to react to a possibly unbounded sequence effectiveness on five ndroid apps. of events. 7vent-driven programs are ubiquitous and, be- sides apps! include stream-processing programs, web servers! GUIs, and embedded systems. 8ormally! we address the fol- Categories and Subject Descriptors lowing problem in the setting of event-driven programs in D.2.$ %Software Engineering&' (esting and Debugging) general, and apps in particular. -
Concolic Testing
DART and CUTE: Concolic Testing Koushik Sen University of California, Berkeley Joint work with Gul Agha, Patrice Godefroid, Nils Klarlund, Rupak Majumdar, Darko Marinov Used and adapted by Jonathan Aldrich, with permission, for 17-355/17-655 Program Analysis 3/28/2017 1 Today, QA is mostly testing “50% of my company employees are testers, and the rest spends 50% of their time testing!” Bill Gates 1995 2 Software Reliability Importance Software is pervading every aspects of life Software everywhere Software failures were estimated to cost the US economy about $60 billion annually [NIST 2002] Improvements in software testing infrastructure may save one- third of this cost Testing accounts for an estimated 50%-80% of the cost of software development [Beizer 1990] 3 Big Picture Safe Programming Languages and Type systems Model Testing Checking Runtime Static Program and Monitoring Analysis Theorem Proving Dynamic Program Analysis Model Based Software Development and Analysis 4 Big Picture Safe Programming Languages and Type systems Model Testing Checking Runtime Static Program and Monitoring Analysis Theorem Proving Dynamic Program Analysis Model Based Software Development and Analysis 5 A Familiar Program: QuickSort void quicksort (int[] a, int lo, int hi) { int i=lo, j=hi, h; int x=a[(lo+hi)/2]; // partition do { while (a[i]<x) i++; while (a[j]>x) j--; if (i<=j) { h=a[i]; a[i]=a[j]; a[j]=h; i++; j--; } } while (i<=j); // recursion if (lo<j) quicksort(a, lo, j); if (i<hi) quicksort(a, i, hi); } 6 A Familiar Program: QuickSort void quicksort -
Symstra: a Framework for Generating Object-Oriented Unit Tests Using Symbolic Execution
Symstra: A Framework for Generating Object-Oriented Unit Tests using Symbolic Execution Tao Xie1, Darko Marinov2, Wolfram Schulte3, David Notkin1 1 Dept. of Computer Science & Engineering, Univ. of Washington, Seattle, WA 98195, USA 2 Department of Computer Science, University of Illinois, Urbana-Champaign, IL 61801, USA 3 Microsoft Research, One Microsoft Way, Redmond, WA 98052, USA {taoxie,notkin}@cs.washington.edu, [email protected], [email protected] Abstract. Object-oriented unit tests consist of sequences of method invocations. Behavior of an invocation depends on the method’s arguments and the state of the receiver at the beginning of the invocation. Correspondingly, generating unit tests involves two tasks: generating method sequences that build relevant receiver- object states and generating relevant method arguments. This paper proposes Symstra, a framework that achieves both test generation tasks using symbolic execution of method sequences with symbolic arguments. The paper defines sym- bolic states of object-oriented programs and novel comparisons of states. Given a set of methods from the class under test and a bound on the length of sequences, Symstra systematically explores the object-state space of the class and prunes this exploration based on the state comparisons. Experimental results show that Symstra generates unit tests that achieve higher branch coverage faster than the existing test-generation techniques based on concrete method arguments. 1 Introduction Object-oriented unit tests are programs that test classes. Each test case consists of a fixed sequence of method invocations with fixed arguments that explores a particular aspect of the behavior of the class under test. Unit tests are becoming an important component of software development. -
Learning to Accelerate Symbolic Execution Via Code Transformation
Learning to Accelerate Symbolic Execution via Code Transformation Junjie Chen Key Laboratory of High Confidence Software Technologies (Peking University), MoE Institute of Software, EECS, Peking University, Beijing, 100871, China [email protected] Wenxiang Hu Key Laboratory of High Confidence Software Technologies (Peking University), MoE Institute of Software, EECS, Peking University, Beijing, 100871, China [email protected] Lingming Zhang Department of Computer Science, University of Texas at Dallas, 75080, USA [email protected] Dan Hao1 Key Laboratory of High Confidence Software Technologies (Peking University), MoE Institute of Software, EECS, Peking University, Beijing, 100871, China [email protected] Sarfraz Khurshid Department of Electrical and Computer Engineering, University of Texas at Austin, 78712, USA [email protected] Lu Zhang Key Laboratory of High Confidence Software Technologies (Peking University), MoE Institute of Software, EECS, Peking University, Beijing, 100871, China [email protected] Abstract Symbolic execution is an effective but expensive technique for automated test generation. Over the years, a large number of refined symbolic execution techniques have been proposed to improve its efficiency. However, the symbolic execution efficiency problem remains, and largely limits the application of symbolic execution in practice. Orthogonal to refined symbolic execution, in this paper we propose to accelerate symbolic execution through semantic-preserving code transform- ation on the target programs. During the initial stage of this direction, we adopt a particular code transformation, compiler optimization, which is initially proposed to accelerate program concrete execution by transforming the source program into another semantic-preserving tar- get program with increased efficiency (e.g., faster or smaller). -
Formally Verifying Webassembly with Kwasm
Formally Verifying WebAssembly with KWasm Towards an Automated Prover for Wasm Smart Contracts Master’s thesis in Computer Science and Engineering RIKARD HJORT Department of Computer Science and Engineering CHALMERS UNIVERSITY OF TECHNOLOGY UNIVERSITY OF GOTHENBURG Gothenburg, Sweden 2020 Master’s thesis 2020 Formally Verifying WebAssembly with KWasm Towards an Automated Prover for Wasm Smart Contracts RIKARD HJORT Department of Computer Science and Engineering Chalmers University of Technology University of Gothenburg Gothenburg, Sweden 2020 Formally Verifying WebAssembly with KWasm Towards an Automated Prover for Wasm Smart Contracts RIKARD HJORT © RIKARD HJORT, 2020. Supervisor: Thomas Sewell, Department of Computer Science and Engineering Examiner: Wolfgang Ahrendt, Department of Computer Science and Engineering Master’s Thesis 2020 Department of Computer Science and Engineering Chalmers University of Technology and University of Gothenburg SE-412 96 Gothenburg Telephone +46 31 772 1000 Cover: Conceptual rendering of the KWasm system, as the logos for K ans Web- Assembly merged together, with a symbolic execution proof tree protruding. The cover image is made by Bogdan Stanciu, with permission. The WebAssembly logo made by Carlos Baraza and is licensed under Creative Commons License CC0. The K logo is property of Runtime Verification, Inc., with permission. Typeset in LATEX Gothenburg, Sweden 2020 iv Formally Verifying WebAssembly with KWasm Towards an Automated Prover for Wasm Smart Contracts Rikard Hjort Department of Computer Science and Engineering Chalmers University of Technology and University of Gothenburg Abstract A smart contract is immutable, public bytecode which handles valuable assets. This makes it a prime target for formal methods. WebAssembly (Wasm) is emerging as bytecode format for smart contracts. -
Advanced Software Testing and Debugging (CS598) Symbolic Execution
Advanced Software Testing and Debugging (CS598) Symbolic Execution Fall 2020 Lingming Zhang Brief history • 1976: A system to generate test data and symbolically execute programs (Lori Clarke) • 1976: Symbolic execution and program testing (James King) • 2005-present: practical symbolic execution • Using SMT solvers • Heuristics to control exponential explosion • Heap modeling and reasoning about pointers • Environment modeling • Dealing with solver limitations 2 Program execution paths if (a) • Program can be viewed as binary … tree with possibly infinite depth if (b) … • Each node represents the execution of a conditional statement if(a) • Each edge represents the F T execution of a sequence of non- if(b) if(b) conditional statements F T F T • Each path in the tree represents an equivalence class of inputs 3 Example a==null F T Code under test a.Length>0 void CoverMe(int[] a) { T a==null if (a == null) F return; a[0]==123… if (a.Length > 0) a!=null && F T if (a[0] == 1234567890) a.Length<=0 throw new Exception("bug"); } a!=null && a!=null && a.Length>0 && a.Length>0 && a[0]!=1234567890 a[0]==1234567890 4 Random testing? • Random Testing Code under test • Generate random inputs void CoverMe(int[] a) { if (a == null) • Execute the program on return; those (concrete) inputs if (a.Length > 0) if (a[0] == 1234567890) • Problem: throw new Exception("bug"); • Probability of reaching error could } be astronomically small Probability of ERROR for the gray branch: 1/232 ≈ 0.000000023% 5 The spectrum of program testing/verification Verification -
Dynamic Symbolic Execution for Polymorphism
Dynamic Symbolic Execution for Polymorphism Lian Li1,2 Yi Lu Jingling Xue 1Oracle Labs, Australia Oracle Labs, Australia UNSW Australia 2 State Key Laboratory of Computer [email protected] [email protected] Architecture, Institute of Computing Technology, Chinese Academy of Sciences [email protected] Abstract represents a set of constraints that must be satisfied by any con- Symbolic execution is an important program analysis technique that crete input that results in the same execution path. provides auxiliary execution semantics to execute programs with The ability to automatically generate concrete test inputs from a symbolic rather than concrete values. There has been much recent path condition makes symbolic execution attractive for automated interest in symbolic execution for automatic test case generation testing and bug detection. A new test case is generated from an and security vulnerability detection, resulting in various tools be- existing one by mutating the path condition of that existing exe- ing deployed in academia and industry. Nevertheless, (subtype or cution and then solving the mutated path condition with an off- dynamic) polymorphism of object-oriented programAnalysiss has the-shelf constraint solver. Recent research has demonstrated that been neglected: existing symbolic execution techniques can explore symbolic execution techniques and test case generation can auto- different targets of conditional branches but not different targets matically generate test suites with high coverage [10, 54], and that of method invocations. We address the problem of how this poly- these techniques are effective in finding deep security vulnerabili- morphism can be expressed in a symbolic execution framework. ties in large and complex real-world software applications [10, 22]. -
Automated Software Testing Using Symbolic Execution
International Journal of Computer Application (2250-1797) Volume 5– No. 7, December 2015 AUTOMATED SOFTWARE TESTING USING SYMBOLIC EXECUTION Faisal Anwer#1, Mohd. Nazir#2 #1 Department of Computer Science, Aligarh Muslim University, Aligarh. faisalanwer.cs @ amu.ac.in #2 Department of Computer Science, Jamia Millia Islamia(Central University), New Delhi mnazir @ jmi.ac.in _________________________________________________________________________ Abstract Symbolic execution is one of the popular automated testing techniques for program verification and test case generation. It ensures coverage of each and every path by generating and aggregating path constraints on each branch. Although, the technique was proposed three decades ago but due to advancement in constraint solving techniques, availability of powerful computers and development of new algorithms research community has shown much interest in the recent past. Applying symbolic execution for program verification and test case generation is simple and straight forward. However, this technique is not widely recognized and accepted in software Industry for large real world software. This is mainly because of certain factors that are being perceived or visualized as current challenges before research community. Rigorous efforts are being made by researchers and practitioners in order to target these challenges. In this paper, an attempt has been made to present an overview of these challenges and state-of-the-art solutions, including a discussion on symbolic execution methods in context of software testing. Further, the paper proposes a framework for automatic and effective program testing using symbolic execution. Index Terms: Symbolic execution, Denial of Service, Environmental condition, Branch dependency, Path coverage. ________________________________________________________________________ Corresponding Author: Faisal Anwer I. INTRODUCTION Testing is one of the important activities of software development life cycle.