Automated Error-Detection and Repair for Compositional Software Specifications

Abstract

Abstract. The complexity of error diagnosis in requirements specifications, already high, is increased when requirements refer to various system components, on whose interaction the system's aims depend. Further, finding causes of error, and ways of overcoming them, cannot easily be achieved without a systematic methodology. This has led researchers to explore the combined use of verification and machine-learning to support automated software analysis and repair. However, existing approaches have been limited by using formalisms in which modularity and compositionality cannot be explicitly expressed. In this paper we overcome this limitation. We define a translation from a representative process algebra, Finite State Processes, into the action language C+. This enables forms of verification not supported by previous methods. We then use a logicprogramming equivalent of C+, to which we apply inductive logic programming for learning repairs to system components while ensuring no new errors are introduced and interactions with other components are maintained. These two phases are iterated until a correct specification is reached, enabling rigorous and scalable support for automated analysis and repair of component-based specifications.

Automated Repair of Unrealisable LTL Specifications Guided by Model Counting

“…In reactive modeling, the system's expected properties are captured in temporal logics [38,39], this is a typical setting in many essential activities, such as model checking [17], property monitoring [11], and model-based testing [26]. Detecting and finding flaws in specifications have been the focus on many studies [20,21,52] Recent works present different techniques to automatically repair the system's specification [6,15,18]. Unlike these approaches, which target the behavioural model, AuRUS aims to repair the declarative specification from which the synthesis tool will later generate an adequate model.…”

An automated system repair framework with signal temporal logic

“…Following the success in automated fault detection methods [8,18,29,39], automated repair problem is getting more attention. In [3], machine learning and verification techniques are combined to repair system specifications. Similarly, in [13], a machine learning-based approach is developed to automatically repair system models written in B formal specification language.…”

“…For a parametric formula φ and a suitable parameter valuation, v, φ(v) denotes the ptSTL formula obtained by replacing each parameter with the corresponding value from v. As an example, consider the parametric formula φ = F − [ p 1 , p 2 ] x < p 3 with parameters p 1 , p 2 and p 3 . ptSTL formula φ(v) = F − [3,5] x < 10.2 is obtained with valuation…”

“…Our goal is to repair the system so that P1.cs ∧ P2.cs will be unreachable. We define the fault detection mechanism with respect to this requirement (see (3)):…”

Automated Repair of Unrealisable LTL Specifications Guided by Model Counting

“…When the current system behaviour does not satisfy the specification, it needs to be fixed. Recent works presented different techniques to automatically repair the model that describes the system behaviour [7,15,53]. As opposed to these repair approaches, which target the behavioural model, our approach aims at repairing the declarative specification from which the synthesis tool later will generate an adequate behavioural model.…”