Software development and maintenance are costly endeavors. The cost can be reduced if more software defects are detected earlier in the development cycle. This paper introduces the Extended Static Checker for Java (ESC/Java), an experimental compile-time program checker that finds common programming errors. The checker is powered by verification-condition generation and automatic theoremproving techniques. It provides programmers with a simple annotation language with which programmer design decisions can be expressed formally. ESC/Java examines the annotated software and warns of inconsistencies between the design decisions recorded in the annotations and the actual code, and also warns of potential runtime errors in the code. This paper gives an overview of the checker architecture and annotation language and describes our experience applying the checker to tens of thousands of lines of Java programs.

A major obstacle to finding program errors in a real system is knowing what correctness rules the system must obey. These rules are often undocumented or specified in an ad hoc manner. This paper demonstrates tech-niques that automatically extract such checking information from the source code itself, rather than the programmer, thereby avoiding the need for a priori knowledge of system rules. The cornerstone of our approach is inferring programmer "beliefs" that we then cross-check for contradictions. Beliefs are facts implied by code: a dereference of a pointer, p, implies a belief that p is non-null, a call to "unlock(1)" implies that 1 was locked, etc. For beliefs we know the programmer must hold, such as the pointer dereference above, we immediately flag contra-

The Java Modeling Language (JML) can be used to specify the detailed design of Java classes and interfaces by adding annotations to Java source files. The aim of JML is to provide a specification language that is easy to use for Java programmers and that is supported by a wide range of tools for specification type-checking, runtime debugging, static analysis, and verification. This paper

Program verification is a promising approach to improving program quality, because it can search all possible program executions for specific errors. However, the need to formally describe correct behavior or errors is a major barrier to the widespread adoption of program verification, since programmers historically have been reluctant to write formal specifications. Automating the process of formulating specifications would remove a barrier to program verification and enhance its practicality.

In this paper, we present a new algorithm for partial program verification that runs in polynomial time and space. We are interested in checking that a program satisfies a given temporal safety property. Our insight is that by accurately modeling only those branches in a program for which the property-related behavior differs along the arms of the branch, we can design an algorithm that is accurate enough to verify the program with respect to the given property, without paying the potentially exponential cost of full pathsensitive analysis. We have implemented this “property simulation ” algorithm as part of a partial verification tool called ESP. We present the results of applying ESP to the problem of verifying the file I/O behavior of a version of the GNU C compiler (gcc, 140,000 LOC). We are able to prove that all of the 646 calls to fprintf in the source code of gcc are guaranteed to print to valid, open files. Our results show that property simulation scales to large programs and is accurate enough to verify meaningful properties.

This paper describes RacerX, a static tool that uses flowsensitive, interprocedural analysis to detect both race conditions and deadlocks. It is explicitly designed to find errors in large, complex multithreaded systems. It aggressively infers checking information such as which locks protect which operations, which code contexts are multithreaded, and which shared accesses are dangerous. It tracks a set of code features which it uses to sort errors both from most to least severe. It uses novel techniques to counter the impact of analysis mistakes. The tool is fast, requiring between 2-14 minutes to analyze a 1.8 million line system. We have applied it to Linux, FreeBSD, and a large commercial code base, finding serious errors in all of them.

This paper presents a novel approach to bug-finding analysis and an implementation of that approach. Our goal is to find as many serious bugs as possible. To do so, we designed a flexible, easy-to-use extension language for specifying analyses and an efficent algorithm for executing these extensions. The language, metal, allows the users of our system to specify a broad class of analyses in terms that resemble the intuitive description of the rules that they check. The system, xgcc, executes these analyses efficiently using a context-sensitive, interprocedural analysis.

Erroneous string manipulations are a major source of software defects in C programs yielding vulnerabilities which are exploited by software viruses. We present C String Static Verifyer (CSSV), a tool that statically uncovers all string manipulation errors. Being a conservative tool, it reports all such errors at the expense of sometimes generating false alarms. Fortunately, only a small number of false alarms are reported, thereby proving that statically reducing software vulnerability is achievable. CSSV handles large programs by analyzing each procedure separately. For this, procedures' contracts are allowed which are veri ed by the tool.

Programs usually follow many implicit programming rules, most of which are too tedious to be documented by programmers. When these rules are violated by programmers who are unaware of or forget about them, defects can be easily introduced. Therefore, it is highly desirable to have tools to automatically extract such rules and also to automatically detect violations. Previous work in this direction focuses on simple function-pair based programming rules and additionally requires programmers to provide rule templates. This paper proposes a general method called PR-Miner that uses a data mining technique called frequent itemset mining to efficiently extract implicit programming rules from large software code written in an industrial programming language such as C, requiring little effort from programmers and no prior knowledge of the software. Benefiting from frequent itemset mining, PR-Miner can extract programming

We present an automatic error-detection approach that combines static checking and concrete test-case generation. Our approach consists of taking the abstract error conditions inferred using theorem proving techniques by a static checker (ESC/Java), deriving specific error conditions using a constraint solver, and producing concrete test cases (with the JCrasher tool) that are executed to determine whether an error truly exists. The combined technique has advantages over both static checking and automatic testing individually. Compared to ESC/Java, we eliminate spurious warnings and improve the ease-of-comprehension of error reports through the production of Java counterexamples. Compared to JCrasher, we eliminate the blind search of the input space, thus reducing the testing time and increasing the test quality.