A Historical Perspective on Runtime Assertion Checking in Software Development

This report presents initial results in the area of software testing and analysis produced as part of the Software Engineering Impact Project. The report describes the historical development of runtime assertion checking, including a description of the origins of and significant features associated with assertion checking mechanisms, and initial findings about current industrial use. A future report will provide a more comprehensive assessment of development practice, for which we invite readers of this report to contribute information

The ASSERT Virtual Machine Kernel: Support for preservation of temporal properties.

The ASSERT Project1 is aimed at defining new software engineering methods and tools for the development of critical embedded real-time systems in the aerospace domain. One of its main achievements is a new model-driven software process, which is based on the concept of property-preserving model transformations. Functional models developed with appropriate tools for the application domain are embedded in containers defining component interfaces and non-functional (e.g. timing) properties in a platform-independent set of notations. The resulting model is then automatically transformed to a platform-specific model using deployment information on target computer nodes, communication channels, and software platforms. Finally, source code for each computer node is automatically generated from the platform-specific model. The key element of the ASSERT process is that non-functional properties must be preserved during all phases of model transformations. In order to ensure that properties are preserved in model transformations and that the different views of each model are consistent with each other, a common meta-model has been defined which provides a formal basis to the whole process. This meta-model is called the Ravenscar Computational Model (RCM)

Model-based dependability analysis : state-of-the-art, challenges and future outlook

Abstract: Over the past two decades, the study of model-based dependability analysis has gathered significant research interest. Different approaches have been developed to automate and address various limitations of classical dependability techniques to contend with the increasing complexity and challenges of modern safety-critical system. Two leading paradigms have emerged, one which constructs predictive system failure models from component failure models compositionally using the topology of the system. The other utilizes design models - typically state automata - to explore system behaviour through fault injection. This paper reviews a number of prominent techniques under these two paradigms, and provides an insight into their working mechanism, applicability, strengths and challenges, as well as recent developments within these fields. We also discuss the emerging trends on integrated approaches and advanced analysis capabilities. Lastly, we outline the future outlook for model-based dependability analysis

Analyzing big time series data in solar engineering using features and PCA

In solar engineering, we encounter big time series data such as the satellite-derived irradiance data and string-level measurements from a utility-scale photovoltaic (PV) system. While storing and hosting big data are certainly possible using today’s data storage technology, it is challenging to effectively and efficiently visualize and analyze the data. We consider a data analytics algorithm to mitigate some of these challenges in this work. The algorithm computes a set of generic and/or application-specific features to characterize the time series, and subsequently uses principal component analysis to project these features onto a two-dimensional space. As each time series can be represented by features, it can be treated as a single data point in the feature space, allowing many operations to become more amenable. Three applications are discussed within the overall framework, namely (1) the PV system type identification, (2) monitoring network design, and (3) anomalous string detection. The proposed framework can be easily translated to many other solar engineer applications

Using formal methods to support testing

Formal methods and testing are two important approaches that assist in the development of high quality software. While traditionally these approaches have been seen as rivals, in recent years a new consensus has developed in which they are seen as complementary. This article reviews the state of the art regarding ways in which the presence of a formal specification can be used to assist testing

NASA space station automation: AI-based technology review

Research and Development projects in automation for the Space Station are discussed. Artificial Intelligence (AI) based automation technologies are planned to enhance crew safety through reduced need for EVA, increase crew productivity through the reduction of routine operations, increase space station autonomy, and augment space station capability through the use of teleoperation and robotics. AI technology will also be developed for the servicing of satellites at the Space Station, system monitoring and diagnosis, space manufacturing, and the assembly of large space structures

A Symbolic Model Checking Approach to Verifying Satellite Onboard Software

This paper discusses the use of symbolic model checking technology to verify the design of an embedded software control system called attitude and orbit control system (AOCS). This system is mission-critical because it is responsible for maintaining the attitude of the satellite and for performing fault detection, isolation, and recovery decisions of the satellite. An executable AOCS implementation by Space Systems Finland has been provided to us in Ada source code form. In order to use symbolic model checking methods, the Ada implementation of the system was modeled at a quite detailed implementation level using the input language of the symbolic model checker NuSMV 2. We describe the modeling techniques and abstractions used to alleviate the state explosion problem due to handling of timers and the large number of system components controlled by AOCS. The specification of the required system behavior was also provided to us in a form of extended state machine diagrams with prioritized transitions. These diagrams have been translated to a set of temporal logic properties, allowing the piecewise checking of the system behavior one extended state machine transition at a time. We also report on the scalability of symbolic model checking tools for the case study at hand as well as discuss potential topics for future work