arXiv subjects

Ali Mili

Publications and source records attributed to Ali Mili.

5 recordsLinked to original sources

arXiv2023

Invariant Relations: A Bridge from Programs to Equations

Great advances in program analysis would be enabled if it were possible to derive the function of a program from inputs to outputs (or from initial states to final states, depending on how we model program semantics). Efforts to do so have always stalled against the difficulty to derive the function of loops; the expedient solution to capture the function of loops by unrolling them an arbitrary number of iterations is clearly inadequate. In this paper, we propose a relations-based method to derive the function of a C-like program, including programs that have loops nested to an arbitrary level. To capture the semantics of loops, we use the concept of invariant relation.

cs.LO↗

arXiv2019

Stryker: Scaling Specification-Based Program Repair by Pruning Infeasible Mutants with SAT

Many techniques for automated program repair involve syntactic program transformations. Applying combinations of such transformations on faulty code yields fix candidates whose correctness must be determined. Exploring these combinations leads to an explosion on the number of generated fix candidates that severely limits the applicability of such fault repair techniques. This explosion is most times tamed by not considering fix candidates exhaustively, and by disabling intra-statement modifications. In this article we present a technique for program repair that considers an ample set of intra-statement syntactic operations, and explores fix candidates exhaustively up to a provided bound. The suitability of the technique, implemented in our tool Stryker, is supported by a novel mechanism to detect and prune infeasible fix candidates. This allows Stryker to repair programs with several bugs, whose fixes require multiple modifications. We evaluate our technique on a benchmark of faulty Java container classes, which Stryker is able to repair, pruning significant parts of the space of generated candidates when more than one bug is present in the code.

cs.SE↗

arXiv2018

Programming Without Refining

To derive a program for a given specification R means to find an artifact P that satisfies two conditions: P is executable in some programming language; and P is correct with respect to R. Refinement-based program derivation achieves this goal in a stepwise manner by enhancing executability while preserving correctness until we achieve complete executability. In this paper, we argue that it is possible to invert these properties, and to derive a program by enhancing correctness while preserving executability (proceeding from one executable program to another) until we achieve absolute correctness. Of course, this latter process is possible only if we know how to enhance correctness.

cs.SE↗

arXiv2016

Program Derivation by Correctness Enhacements

Relative correctness is the property of a program to be more-correct than another program with respect to a given specification. Among the many properties of relative correctness, that which we found most intriguing is the property that program P' refines program P if and only if P' is more-correct than P with respect to any specification. This inspires us to reconsider program derivation by successive refinements: each step of this process mandates that we transform a program P into a program P' that refines P, i.e. P' is more-correct than P with respect to any specification. This raises the question: why should we want to make P' more-correct than P with respect to any specification, when we only have to satisfy specification R? In this paper, we discuss a process of program derivation that replaces traditional sequence of refinement-based correctness-preserving transformations starting from specification R by a sequence of relative correctness-based correctness-enhancing transformations starting from abort.

cs.LO↗

arXiv2016

Program Repair by Stepwise Correctness Enhancement

Relative correctness is the property of a program to be more-correct than another with respect to a given specification. Whereas the traditional definition of (absolute) correctness divides candidate program into two classes (correct, and incorrect), relative correctness arranges candidate programs on the richer structure of a partial ordering. In other venues we discuss the impact of relative correctness on program derivation, and on program verification. In this paper, we discuss the impact of relative correctness on program testing; specifically, we argue that when we remove a fault from a program, we ought to test the new program for relative correctness over the old program, rather than for absolute correctness. We present analytical arguments to support our position, as well as an empirical argument in the form of a small program whose faults are removed in a stepwise manner as its relative correctness rises with each fault removal until we obtain a correct program.

cs.SE↗