Mario Sangiorgio

SPecification RecoverY: inferring behavior models of stateful software components, and using them at run time to detect when a component's behavior changes

In the recent years, several research efforts have been devoted to developing approaches to synthesize specifications of software behavior. Most of the proposed approaches addressed the inference of finite-state abstractions. The synthesized abstractions have been integrated in different validation scenarios, such as testing. While finite-state models can be effectively used as models of a software component’s behavior for certain specific purposes, they can hardly be used as full-fledged specifications. Because of their very limited expressive power, they cannot represent some of the component behaviors and may lead to synthesizing too coarse abstractions. In this paper, we survey a set of approaches that instead infer infinite-state abstractions, which can be used to express richer sets of behaviors of a software component in a black-box manner. For such approaches, we also discuss the few existing applications to software validation. In particular, we discuss the limitations and identify how, in principle, they can be used in different validation scenarios and how this opens new research directions.

Modern software systems are composed of several services which may be developed and maintained by third parties and thus they can change independently and without notice during the system’s runtime execution. In such systems, changes may possibly be a threat to system functional correctness, and thus to its reliability. Hence, it is important to detect them as soon as they happen to enable proper reaction. Change detection can be done by monitoring system execution and comparing the observed execution traces against models of the services composing the application. Unfortunately, formal specifications for services are not usually provided and developers have to infer them. In this paper we propose a methodology which exactly addresses these issues by using software behavior models to monitor component execution and detect changes. In particular, we describe a technique to infer behavior model specifications with a dynamic black box approach, keep them up-to-date with run time observations and detect behavior changes. Finally, we present a case study to validate the effectiveness of the approach in component change detection for a component that implements a complex, real communication protocol.

We present Spy@Runtime, a tool to infer and work with behavior models. Spy@Runtime generates models through a dynamic black box approach and is able to keep them updated with observations coming from actual system execution. We also show how to use models describing the protocol of interaction of a software component to detect and report functional changes as soon as they are discovered. Monitoring functional properties is particularly useful in an open environment in which there is a distributed ownership of a software system. Parts of the system may be changed independently and therefore it becomes necessary to monitor the component's behavior at run time.