A Model-Driven Approach for the Formal Verification of Storm-Based Streaming Applications

Data-intensive applications (DIAs) based on so-called Big Data technologies are nowadays a common solution adopted by IT companies to face their growing computational needs. The need for highly reliable applications able to handle huge amounts of data and the availability of infrastructures for distributed computing rapidly led industries to develop frameworks for streaming and big-data processing, like Apache Storm and Spark. The definition of methodologies and principles for good software design is, therefore, fundamental to support the development of DIAs. This paper presents an approach for non-functional analysis of DIAs through D-VerT, a tool for the architectural assessment of Storm applications. The verification is based on a translation of Storm topologies into the CLTLoc metric temporal logic. It allows the designer of a Storm application to check for the existence of components that cannot process their workload in a timely manner, typically due to an incorrect design of the topology

Formal verification of storm topologies through D-VerT

Data-intensive applications (DIAs) based on so-called Big Data technologies are nowadays a common solution adopted by IT companies to face their growing computational needs. The need for highly reliable applications able to handle huge amounts of data and the availability of infrastructures for distributed computing rapidly led industries to develop frame-works for streaming and big-data processing, like Apache Storm and Spark. The definition of methodologies and principles for good software design is, therefore, fundamental to support the development of DIAs. This paper presents an approach for non-functional analysis of DIAs through D- VerT, a tool for the architectural assessment of Storm applications. The verification is based on a translation of Storm topologies into the CLTLoc metric temporal logic. It allows the designer of a Storm application to check for the existence of components that cannot process their workload in a timely manner, typically due to an incorrect design of the topology

Evaluating Model Testing and Model Checking for Finding Requirements Violations in Simulink Models

Matlab/Simulink is a development and simulation language that is widely used by the Cyber-Physical System (CPS) industry to model dynamical systems. There are two mainstream approaches to verify CPS Simulink models: model testing that attempts to identify failures in models by executing them for a number of sampled test inputs, and model checking that attempts to exhaustively check the correctness of models against some given formal properties. In this paper, we present an industrial Simulink model benchmark, provide a categorization of different model types in the benchmark, describe the recurring logical patterns in the model requirements, and discuss the results of applying model checking and model testing approaches to identify requirements violations in the benchmarked models. Based on the results, we discuss the strengths and weaknesses of model testing and model checking. Our results further suggest that model checking and model testing are complementary and by combining them, we can significantly enhance the capabilities of each of these approaches individually. We conclude by providing guidelines as to how the two approaches can be best applied together.Comment: 10 pages + 2 page reference

Verifying big data topologies by-design: a semi-automated approach

Big data architectures have been gaining momentum in recent years. For instance, Twitter uses stream processing frameworks like Apache Storm to analyse billions of tweets per minute and learn the trending topics. However, architectures that process big data involve many different components interconnected via semantically different connectors. Such complex architectures make possible refactoring of the applications a difficult task for software architects, as applications might be very different with respect to the initial designs. As an aid to designers and developers, we developed OSTIA (Ordinary Static Topology Inference Analysis) that allows detecting the occurrence of common anti-patterns across big data architectures and exploiting software verification techniques on the elicited architectural models. This paper illustrates OSTIA and evaluates its uses and benefits on three industrial-scale case-studies

Modeling and Verification of Agent based Adaptive Traffic Signal using Symbolic Model Verifier

This paper addresses the issue of modeling and verification of a Multi Agent System (MAS) scenario. We have considered an agent based adaptive traffic signal system. The system monitors the smooth flow of traffic at intersection of two road segment. After describing how the adaptive traffic signal system can efficiently be used and showing its advantages over traffic signals with predetermined periods, we have shown how we can transform this scenario into Finite State Machine (FSM). Once the system is transformed into a FSM, we have verified the specifications specified in Computational Tree Logic(CTL) using NuSMV as a model checking tool. Simulation results obtained from NuSMV showed us whether the system satisfied the specifications or not. It has also showed us the state where the system specification does not hold. Using which we traced back our system to find the source, leading to the specification violation. Finally, we again verified the modified system with NuSMV for its specifications.Comment: 13 pages, 6 figures, Submitted to International Journal of Computer Application (IJCA

SMT-based Verification of LTL Specifications with Integer Constraints and its Application to Runtime Checking of Service Substitutability

An important problem that arises during the execution of service-based applications concerns the ability to determine whether a running service can be substituted with one with a different interface, for example if the former is no longer available. Standard Bounded Model Checking techniques can be used to perform this check, but they must be able to provide answers very quickly, lest the check hampers the operativeness of the application, instead of aiding it. The problem becomes even more complex when conversational services are considered, i.e., services that expose operations that have Input/Output data dependencies among them. In this paper we introduce a formal verification technique for an extension of Linear Temporal Logic that allows users to include in formulae constraints on integer variables. This technique applied to the substitutability problem for conversational services is shown to be considerably faster and with smaller memory footprint than existing ones