Exploring conditional rewriting logic computations

Abstract

Trace exploration is concerned with techniques that allow computation traces to be dynamically searched for specific contents. Depending on whether the exploration is carried backward or forward, trace exploration techniques allow provenance tracking or impact tracking to be done. The aim of provenance tracking is to show how (parts of) a program output depends on (parts of) its input and to help estimate which input data need to be modified to accomplish a change in the outcome. The aim of impact tracking is to identify the scope and potential consequences of changing the program input. Rewriting Logic (RWL) is a logic of change that supplements (an extension of) the equational logic by adding rewrite rules that are used to describe (nondeterministic) transitions between states. In this paper, we present a rich and highly dynamic, parameterized technique for the forward inspection of RWL computations that allows the nondeterministic execution of a given conditional rewrite theory to be followed up in different ways. With this technique, an analyst can browse, slice, filter, or search the traces as they come to life during the program execution. The navigation of the trace is driven by a user-defined, inspection criterion that specifies the required exploration mode. By selecting different inspection criteria, one can automatically derive a family of practical algorithms such as program steppers and more sophisticated dynamic trace slicers that compute summaries of the computation tree, thereby facilitating the dynamic detection of control and data dependencies across the tree. Our methodology, which is implemented in the Anima graphical tool, allows users to evaluate the effects of a given statement or instruction in isolation, track input change impact, and gain insight into program behavior (or misbehavior).

Assertion-based analysis via slicing withABETS(system description)

“…user-provided slicing criteria refinements (Alpuente et al 2015); (ii) a program slicing feature for delivering program fragments that include all and only the rules/equations responsible for the detected error.…”

Combining Runtime Checking and Slicing to Improve Maude Error Diagnosis

“…This function relies on an instrumentation technique for Maude steps that allows the relevant information of the step, such as the selected redex and the contractum produced by the step, to be traced explicitly despite the fact that terms are rewritten modulo a set B of equational axioms that may cause their components to be implicitly reordered in the original trace. Also, the dynamic dependencies exposed by backward trace slicing are exploited in [8] to provide a (preliminary) program slicing capability that can identify those parts of a Maude theory that can (potentially) affect the values computed at some point of interest.…”

“…The implementation comprises: (i) a frontend consisting of a RESTful Web service written in Java, with an intuitive user interface based on AJAX technology written in HTML5, Canvas, and Javascript; and (ii) a back-end that implements the proposed trace analysis methodology in Maude. The implementation of the backend consists of about 350 Maude function definitions (approximately 2700 lines of source code) that partially reuse the slicing and exploration machinery developed in previous work [4,5,8], extending it with the constraint-checking capabilities described in this paper.…”

“…A key feature of our approach is that the assertions (or more precisely, their runtime checks) are used to automatically synthesize advisable slicing criteria from inferred error symptoms. Our methodology smoothly blends in with the general framework for the analysis and exploration of rewriting logic computations that we developed in previous research [8].…”

“…Maude modules correspond to specifications in rewriting logic [24], which is a logic that allows the representation of many models of concurrent and distributed systems. In [6,8], a rich and highly dynamic parameterized scheme for exploring rewriting logic computations is developed that can significantly reduce the size and complexity of the runs under examination by automatically slicing both programs and computation traces [4].…”