Nandamudi Lankalapalli Vijaykumar

A Practical Approach for Automated Test Case Generation using Statecharts

This paper presents an approach for automated test case generation using a software specification modeled in statecharts. The steps defined in such approach involve: translation of statecharts modeling into an XML-based language; and the PerformCharts tool generates FSMs based on control flow. These FSMs are the inputs for the Condado tool which generates test cases. The idea is to demonstrate that by using a higher-level technique, such as Statecharts, complex software can be represented with clarity and rich details. A case study was on an implementation of a protocol specified for communication between a scientific experiment and the on-board data handling computer of a satellite under development at National Institute for Space Research (INPE)

Generating model-based test cases from natural language requirements for space application software

Natural Language (NL) deliverables suffer from ambiguity, poor understandability, incompleteness, and inconsistency. Howewer, NL is straightforward and stakeholders are familiar with it to produce their software requirements documents. This paper presents a methodology, SOLIMVA, which aims at model-based test case generation considering NL requirements deliverables. The methodology is supported by a tool that makes it possible to automatically translate NL requirements into Statechart models. Once the Statecharts are derived, another tool, GTSC, is used to generate the test cases. SOLIMVA uses combinatorial designs to identify scenarios for system and acceptance testing, and it requires that a test designer defines the application domain by means of a dictionary. Within the dictionary there is a Semantic Translation Model in which, among other features, a word sense disambiguation method helps in the translation process. Using as a case study a space application software product, we compared SOLIMVA with a previous manual approach developed by an expert under two aspects: test objectives coverage and characteristics of the Executable Test Cases. In the first aspect, the SOLIMVA methodology not only covered the test objectives associated to the expert’s scenarios but also proposed a better strategy with test objectives clearly separated according to the directives of combinatorial designs. The Executable Test Cases derived in accordance with the SOLIMVA methodology not only possessed similar characteristics with the expert’s Executable Test Cases but also predicted behaviors that did not exist in the expert’s strategy. The key benefits from applying the SOLIMVA methodology/tool within a Verification and Validation process are the ease of use and, at the same time, the support of a formal method consequently leading to a potential acceptance of the methodology in complex software projects.

An Environment for Automated Test Case Generation from Statechart-based and Finite State Machine-based Behavioral Models

Automated test case generation from behavioral models like finite state machines (FSMs) and statecharts has long been studied. Environments that enable a test designer to model a real complex software and to obtain test cases to validate such a software are mandatory in an automated test approach. This paper presents an environment, GTSC, which enables test sequences to be obtained from both Statechart-based and FSM-based behavioral models. The environment supports test case generation from some test methods for FSM, such as switch cover, DS and UIO methods, and also from some test criteria for Statecharts based on the SCCF family. Two case studies involving embedded software developed for two computers of scientific experiments of a satellite under development at National Institute for Space Research (INPE) are presented in order to show the usefulness of the environment.

Strategies for improving the modeling and interpretability of Bayesian networks

One of the main factors for the knowledge discovery success is related to the comprehensibility of the patterns discovered by applying data mining techniques. Amongst which we can point out the Bayesian networks as one of the most prominent when considering the easiness of knowledge interpretation achieved. Bayesian networks, however, present limitations and disadvantages regarding their use and applicability. This paper presents an extension for the improvement of Bayesian networks, treating aspects such as performance, as well as interpretability and use of their results; incorporating genetic algorithms in the model, multivariate regression for structure learning and temporal aspects using Markov chains.

On Proposing Statecharts to Specify Performance Models

This paper shows that Statecharts, a high-level specification technique, can be used to represent performance models. This is a powerful technique and is based on state-transition diagrams added with concepts of hierarchy and orthogonality to represent a system behavior. It is shown that Statecharts may conveniently be used to represent models with richness and clarity. Using an analytical approach the technique to determine performance measurements is provided. Three examples are presented and the results show Statecharts’ potential for representing systems for performance evaluation.

Performance evaluation based on system modeling using Statecharts extensions

Abstract This paper presents two extensions for Statecharts: the Stochastic Statecharts, which use the original statecharts notation with a minor modification in the formal semantics and the Queuing Statecharts, which do not follow the pure Statecharts notation, but a join between Statecharts and queuing network representations. Some basic elements of Statecharts are redefined such as events and conditions, besides some concepts referring to the dynamic system behavior. The specification approaches show the basic behavior of a generic queuing system by means of templates and standard events. It is presented the PerformCharts, a new simulation environment based on Statecharts specification, which allows model solution using either Markov chains or the Network Simulator (NS).

A Conformance Testing Process for Space Applications Software Services

Comprehensive tests for space applications software are costly but extremely necessary. These software must be reliable and produced within schedule and budget. In a tentative of make the space mission software development for space agencies and industries more costeffective, the European Committee for Space Standardization (ECSS) has been compiling a set of standards that specify the common core of some space application systems. Once the set of services is standardized, the conformance problem is raised. In this paper we present a testing process for standardized services, which is based on the IS-9646 standard for ISO protocol conformance testing. The process includes an approach to derive test and fault cases by combining conformance testing concepts with the software-implemented fault injection (SWIFI) technique. One advantage of this process is the generation of a re-usable

Gradient pattern analysis of structural dynamics: application to molecular system relaxation

This paper describes an innovative technique, the gradient pattern analysis (GPA), for analysing spatially extended dynamics. The measures obtained from GPA are based on the spatio-temporal correlations between large and small amplitude fluctuations of the structure represented as a dynamical gradient pattern. By means of four gradient moments it is possible to quantify the relative fluctuations and scaling coherence at a dynamical numerical lattice and this is a set of proper measures of the pattern complexity and equilibrium. The GPA technique is applied for the first time in 3D-simulated molecular chains with the objective of characterizing small symmetry breaking, amplitude and phase disorder due to spatio-temporal fluctuations driven by the spatially extended dynamics of a relaxation regime.

Gradient pattern analysis of short nonstationary time series: an application to Lagrangian data from satellite tracked drifters

Based on the gradient pattern analysis (GPA) technique we introduce a new methodology for analyzing short nonstationary time series. Using the asymmetric amplitude fragmentation (AAF) operator from GPA we analyze Lagrangian data observed as velocity time series for ocean flow. The results show that quasi-periodic, chaotic and turbulent regimes can be well characterized by means of this new geometrical approach.

Introducing probabilities in Statecharts to specify reactive systems for performance analysis

Statecharts are expressed in a graphical language to specify complex reactive systems. They are extension of state-transition diagrams to which notions of hierarchy and orthogonality have been added. Recently, they have been suggested to represent performance models and in this regard a software package has been developed. In these performance models, the behavior of a system under study is considered to be probabilistic. Therefore, the inclusion of probabilities in Statecharts formalism will be studied. The proposed extension considers that a modeled system reacts probabilistically to events. In order to deal with these models, an analytical computational method based on constructing a Continuous-Time Markov Chain that is equivalent to the Statecharts model is proposed. The aspect of generating a Continuous-Time Markov Chain from Statecharts representation along with the solution to include probabilities among the transitions will be covered in this paper.