Abstract Small round-off errors in safety-critical systems can lead to catastrophic consequences. In this context, determining if the result computed by a floating-point program is accurate enough with respect to its ideal real-number counterpart is essential. This paper presents PRECiSA 4.0, a tool that rigorously estimates the accumulated round-off error of a floating-point program. PRECiSA 4.0 combines static analysis, optimization techniques, and theorem proving to provide a modular approach for computing a provably correct round-off error estimation. PRECiSA 4.0 adds several features to previous versions of the tool that enhance its applicability and performance. These features include support for data collections such as lists, records, and tuples; support for recursion schemas; an updated floating-point formalization that closely characterizes the IEEE-754 standard; an efficient and modular analysis of function calls that improves the performances for large programs; and a new user interface integrated into Visual Studio Code.

Abstract The Automatic Dependent Surveillance-Broadcast (ADS-B) system allows aircraft to communicate current state information, including position and velocity messages, to other aircraft in their vicinity and to ground stations. The Compact Position Reporting (CPR) algorithm is the ADS-B protocol responsible for the encoding and decoding of aircraft positions. CPR is sensitive to computer arithmetic since it relies on functions that are intrinsically unstable such as floor and modulus. In this paper, a formal verification of the CPR algorithm is presented. In contrast to previous work, the algorithm presented here encompasses the entire range of message types supported by ADS-B. The paper also presents two implementations of the CPR algorithm, one in double-precision floating-point and one in 32-bit unsigned integers, which are both formally verified against the real-number algorithm. The verification proceeds in three steps. For each implementation, a version of CPR, which is simplified and manipulated to reduce numerical instability and leverage features of the datatypes, is proposed. Then, the Prototype Verification System (PVS) is used to formally prove real conformance properties, which assert that the ideal real-number counterpart of the improved algorithm is mathematically equivalent to the standard CPR definition. Finally, the static analyzer Frama-C is used to verify software conformance properties, which say that the software implementation of the improved algorithm is correct with respect to its idealized real-number counterpart. In concert, the two properties guarantee that the implementation meets the original specification. The two implementations will be included in the revised version of the ADS-B standards document as the reference implementation of the CPR algorithm.

Automatic analysis of Alloy models is supported by the Alloy Analyzer, a tool that translates an Alloy model to a propositional formula that is then analyzed using off-the-shelf SAT solvers. The translation requires user-provided bounds on the sizes of data domains. The analysis is limited by the bounds and is therefore partial. Thus, the Alloy Analyzer may not be appropriate for the analysis of critical applications where more conclusive results are necessary. Dynamite is an extension of PVS that embeds a complete calculus for Alloy. It also includes extensions to PVS that allow one to improve the proof effort by, for instance, automatically analyzing new hypotheses with the aid of the Alloy Analyzer. Since PVS sequents may get cluttered with unnecessary formulas, we use the Alloy unsat-core extraction feature in order to refine proof sequents. An internalization of Alloy's syntax as an Alloy specification allows us to use the Alloy Analyzer for producing witnesses for proving existentially quantified formulas. Dynamite complements the partial automatic analysis offered by the Alloy Analyzer with semi-automatic verification through theorem proving. It also improves the theorem proving experience by using the Alloy Analyzer for early error detection, sequent refinement, and witness generation.

We present a novel and general technique for automated test generation that combines tight bounds with incremental SAT solving. The proposed technique uses incremental SAT to build test suites targeting a specific testing criterion, amongst various black-box and white-box criteria. As our experimental results show, the combination of tight bounds with incremental SAT, and the testing criterion driven approach implemented in our prototype tool FAJITA, enable us to effectively generate test suites for container classes with rich contracts, more efficiently than other state-of-the-art tools.