Reversible Computations in Logic Programming

[EN] In this work, we say that a computation is reversible if one can find a procedure to undo the steps of a standard (or forward) computation in a deterministic way. While logic programs are often invertible (e.g., one can use the same predicate for adding and for subtracting natural numbers), computations are not reversible in the above sense. In this paper, we present a so-called Landauer embedding for SLD resolution, the operational principle of logic programs, so that it becomes reversible. A proof-of-concept implementation of a reversible debugger for Prolog that follows the ideas in this paper has been developed and is publicly available.This work is partially supported by the EU (FEDER) and the Spanish MCI/AEI under grants TIN2016-76843-C4-1-R/PID2019-104735RB-C41, by the Generalitat Valenciana under grant Prometeo/2019/098 (DeepTrust), and by the COST Action IC1405 on Reversible Computation - extending horizons of computing.Vidal, G. (2020). Reversible Computations in Logic Programming. Springer. 246-254. https://doi.org/10.1007/978-3-030-52482-1_15S246254Apt, K.: From Logic Programming to Prolog. Prentice Hall, Upper Saddle River (1997)Ducassé, M.: Opium: an extendable trace analyzer for prolog. J. Log. Program. 39(1–3), 177–223 (1999). https://doi.org/10.1016/S0743-1066(98)10036-5Landauer, R.: Irreversibility and heat generation in the computing process. IBM J. Res. Dev. 5, 183–191 (1961)Lanese, I., Palacios, A., Vidal, G.: Causal-consistent replay debugging for message passing programs. In: Pérez, J.A., Yoshida, N. (eds.) FORTE 2019. LNCS, vol. 11535, pp. 167–184. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-21759-4_10Lloyd, J.: Foundations of Logic Programming, 2nd edn. Springer, Berlin (1987). https://doi.org/10.1007/978-3-642-83189-8O’Callahan, R., Jones, C., Froyd, N., Huey, K., Noll, A., Partush, N.: Engineering record and replay for deployability: Extended technical report (2017). CoRR abs/1705.05937, http://arxiv.org/abs/1705.05937Ströder, T., Emmes, F., Schneider-Kamp, P., Giesl, J., Fuhs, C.: A linear operational semantics for termination and complexity analysis of ISO prolog. In: Vidal, G. (ed.) LOPSTR 2011. LNCS, vol. 7225, pp. 237–252. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-32211-2_16Undo Software: Increasing software development productivity with reversible debugging (2014). https://undo.io/media/uploads/files/Undo_ReversibleDebugging_Whitepaper.pd

Proving termination of programs automatically with AProVE

AProVE is a system for automatic termination and complexity proofs of Java, C, Haskell, Prolog, and term rewrite systems (TRSs). To analyze programs in high-level languages, AProVE automatically converts them to TRSs. Then, a wide range of techniques is employed to prove termination and to infer complexity bounds for the resulting TRSs. The generated proofs can be exported to check their correctness using automatic certifiers. For use in software construction, we present an AProVE plug-in for the popular Eclipse software development environment

Teaching breast ultrasound skills including core-needle biopsies on a phantom enhances undergraduate student's knowledge and learning satisfaction

Purpose To investigate whether a training program on breast ultrasound skills including core-needle biopsies to undergraduate students can improve medical knowledge and learning satisfaction. Methods Medical students attending mandatory classes at the Medical School of the University of Saarland received a supplemental theoretical and hands-on training program on ultrasound (US) breast screening and on US-guided core-needle biopsy using an agar–agar phantom. Experienced breast specialists and ultrasound examiners served as trainers applying Peyton’s 4-step training approach. The students’ theoretical knowledge and hands-on skills were tested before and after the training program, using a multiple-choice questionnaire (MCQ), the Objective Structured Clinical Examination (OSCE) and a student curriculum evaluation. Results The MCQ results showed a significant increase of the student’s theoretical knowledge (50.2–75.2%, p < 0.001). After the course, the OSCE showed a mean total of 17.3/20 points (86.5%), confirming the practical implementation of the new skills. The student curriculum evaluation in general was very positive. A total of 16/20 questions were rated between 1.2 and 1.7 (very good) and 3 questions were rated as 2.1 (good). Conclusion Undergraduate student’s medical education can be enhanced by teaching breast US skills

Automatically proving termination and memory safety for programs with pointer arithmetic

While automated verification of imperative programs has been studied intensively, proving termination of programs with explicit pointer arithmetic fully automatically was still an open problem. To close this gap, we introduce a novel abstract domain that can track allocated memory in detail. We use it to automatically construct a symbolic execution graph that over-approximates all possible runs of a program and that can be used to prove memory safety. This graph is then transformed into an integer transition system, whose termination can be proved by standard techniques. We implemented this approach in the automated termination prover AProVE and demonstrate its capability of analyzing C programs with pointer arithmetic that existing tools cannot handle

Biabduction (and related problems) in array separation logic

We investigate array separation logic (\mathsf {ASL}), a variant of symbolic-heap separation logic in which the data structures are either pointers or arrays, i.e., contiguous blocks of memory. This logic provides a language for compositional memory safety proofs of array programs. We focus on the biabduction problem for this logic, which has been established as the key to automatic specification inference at the industrial scale. We present an \mathsf {NP} decision procedure for biabduction in \mathsf {ASL}, and we also show that the problem of finding a consistent solution is \mathsf {NP}-hard. Along the way, we study satisfiability and entailment in \mathsf {ASL}, giving decision procedures and complexity bounds for both problems. We show satisfiability to be \mathsf {NP}-complete, and entailment to be decidable with high complexity. The surprising fact that biabduction is simpler than entailment is due to the fact that, as we show, the element of choice over biabduction solutions enables us to dramatically reduce the search space