Comparing metaheuristic algorithms for error detection in Java programs

Chicano, F., Ferreira M., & Alba E. (2011). Comparing Metaheuristic Algorithms for Error Detection in Java Programs. In Proceedings of Search Based Software Engineering, Szeged, Hungary, September 10-12, 2011. pp. 82–96.Model checking is a fully automatic technique for checking concurrent software properties in which the states of a concurrent system are explored in an explicit or implicit way. The main drawback of this technique is the high memory consumption, which limits the size of the programs that can be checked. In the last years, some researchers have focused on the application of guided non-complete stochastic techniques to the search of the state space of such concurrent programs. In this paper, we compare five metaheuristic algorithms for this problem. The algorithms are Simulated Annealing, Ant Colony Optimization, Particle Swarm Optimization and two variants of Genetic Algorithm. To the best of our knowledge, it is the first time that Simulated Annealing has been applied to the problem. We use in the comparison a benchmark composed of 17 Java concurrent programs. We also compare the results of these algorithms with the ones of deterministic algorithms.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech. This research has been partially funded by the Spanish Ministry of Science and Innovation and FEDER under contract TIN2008-06491-C04-01 (the M∗ project) and the Andalusian Government under contract P07-TIC-03044 (DIRICOM project)

Model Based Analysis and Test Generation for Flight Software

We describe a framework for model-based analysis and test case generation in the context of a heterogeneous model-based development paradigm that uses and combines Math- Works and UML 2.0 models and the associated code generation tools. This paradigm poses novel challenges to analysis and test case generation that, to the best of our knowledge, have not been addressed before. The framework is based on a common intermediate representation for different modeling formalisms and leverages and extends model checking and symbolic execution tools for model analysis and test case generation, respectively. We discuss the application of our framework to software models for a NASA flight mission

Program Model Checking: A Practitioner's Guide

Program model checking is a verification technology that uses state-space exploration to evaluate large numbers of potential program executions. Program model checking provides improved coverage over testing by systematically evaluating all possible test inputs and all possible interleavings of threads in a multithreaded system. Model-checking algorithms use several classes of optimizations to reduce the time and memory requirements for analysis, as well as heuristics for meaningful analysis of partial areas of the state space Our goal in this guidebook is to assemble, distill, and demonstrate emerging best practices for applying program model checking. We offer it as a starting point and introduction for those who want to apply model checking to software verification and validation. The guidebook will not discuss any specific tool in great detail, but we provide references for specific tools

Runtime exception detection in Java programs using symbolic execution

Most of the runtime failures of a software system can be revealed during test execution only, which has a very high cost. In Java programs, runtime failures are manifested as unhandled runtime exceptions. In this paper we present an approach and tool for detecting runtime exceptions in Java programs without having to execute tests on the software. We use the symbolic execution technique to implement the approach. By executing the methods of the program symbolically we can determine those execution branches that throw exceptions. Our algorithm is able to generate concrete test inputs also that cause the program to fail in runtime. We used the Symbolic PathFinder extension of the Java PathFinder as the symbolic execution engine. Besides small example codes we evaluated our algorithm on three open source systems: jEdit, ArgoUML, and log4j. We found multiple errors in the log4j system that were also reported as real bugs in its bug tracking system

Proceedings of the First NASA Formal Methods Symposium

Topics covered include: Model Checking - My 27-Year Quest to Overcome the State Explosion Problem; Applying Formal Methods to NASA Projects: Transition from Research to Practice; TLA+: Whence, Wherefore, and Whither; Formal Methods Applications in Air Transportation; Theorem Proving in Intel Hardware Design; Building a Formal Model of a Human-Interactive System: Insights into the Integration of Formal Methods and Human Factors Engineering; Model Checking for Autonomic Systems Specified with ASSL; A Game-Theoretic Approach to Branching Time Abstract-Check-Refine Process; Software Model Checking Without Source Code; Generalized Abstract Symbolic Summaries; A Comparative Study of Randomized Constraint Solvers for Random-Symbolic Testing; Component-Oriented Behavior Extraction for Autonomic System Design; Automated Verification of Design Patterns with LePUS3; A Module Language for Typing by Contracts; From Goal-Oriented Requirements to Event-B Specifications; Introduction of Virtualization Technology to Multi-Process Model Checking; Comparing Techniques for Certified Static Analysis; Towards a Framework for Generating Tests to Satisfy Complex Code Coverage in Java Pathfinder; jFuzz: A Concolic Whitebox Fuzzer for Java; Machine-Checkable Timed CSP; Stochastic Formal Correctness of Numerical Algorithms; Deductive Verification of Cryptographic Software; Coloured Petri Net Refinement Specification and Correctness Proof with Coq; Modeling Guidelines for Code Generation in the Railway Signaling Context; Tactical Synthesis Of Efficient Global Search Algorithms; Towards Co-Engineering Communicating Autonomous Cyber-Physical Systems; and Formal Methods for Automated Diagnosis of Autosub 6000

Assured Android Execution Environments

Current cybersecurity best practices, techniques, tactics and procedures are insufficient to ensure the protection of Android systems. Software tools leveraging formal methods use mathematical means to assure both a design and implementation for a system and these methods can be used to provide security assurances. The goal of this research is to determine methods of assuring isolation when executing Android software in a contained environment. Specifically, this research demonstrates security properties relevant to Android software containers can be formally captured and validated, and that an implementation can be formally verified to satisfy a corresponding specification. A three-stage methodology called The Formal Verification Cycle is presented. This cycle focuses on the iteration over a set of security properties to validate each within a specification and their verification within a software implementation. A security property can be validated when its functional language prototype (e.g. a Haskell coded version of the property) is converted and processed by a formal method (e.g. a theorem proof assistant). This validation of the property enables the definition of the property in a software specification, which can be implemented separately in an imperative programming language (e.g. the Go programming language). Once the implementation is complete another formal method can be used (e.g. symbolic execution) to verify the imperative implementation satisfies the validated specification. Successful completion of this cycle shows a given implementation is equivalent to a functional language prototype, and this cycle assures a specification for the original desired security properties was properly implemented. This research shows an application of this cycle to develop Assured Android Execution Environments