Swedish Institute of Computer Science Publications Database
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Towards Execution Time Prediction for Test Cases from Test Specification
No full textKnowing the execution time of test cases is important to perform test scheduling, prioritization and progress monitoring. This short paper presents a novel approach for predicting the execution time of test cases based on test specifications and available historical data on previously executed test cases. Our approach works by extracting timing information (measured and maximum execution time) for various steps in manual test cases. This information is then used to estimate the maximum time for test steps that have not previously been executed, but for which textual specifications exist. As part of our approach natural language parsing of the specifications is performed to identify word combinations to check whether existing timing information on various test activities already exists or not. Finally, linear regression is used to predict the actual execution time for test cases. A proof-of-concept use-case at Bombardier transportation serves to evaluate the proposed approach
SecureSense: End-to-End Secure Communication Architecture for the Cloud-connected Internet of Thing
No full text
Choosing Component Origins for Software Intensive Systems: In-house, COTS, OSS or Outsourcing?--A Case Survey
No full textThe choice of which software component to use influences the success of a software system. Only a few empirical studies investigate how the choice of components is conducted in industrial practice. This is important to understand to tailor research solutions to the needs of the industry. Existing studies focus on the choice for off-the-shelf (OTS) components. It is, however, also important to understand the implications of the choice of alternative component sourcing options (CSOs), such as outsourcing versus the use of OTS. Previous research has shown that the choice has major implications on the development process as well as on the ability to evolve the system. The objective of this study is to explore how decision making took place in industry to choose among CSOs. Overall, 22 industrial cases have been studied through a case survey. The results show that the solutions specifically for CSO decisions are deterministic and based on optimization approaches. The non-deterministic solutions proposed for architectural group decision making appear to suit the CSO decision making in industry better. Interestingly, the final decision was perceived negatively in nine cases and positively in seven cases, while in the remaining cases it was perceived as neither positive nor negative
Searchable Encrypted Relational Databases: Risks and Countermeasures
No full textWe point out the risks of protecting relational databases via Searchable Symmetric Encryption (SSE) schemes by proposing an inference attack exploiting the structural properties of relational databases. We show that record-injection attacks mounted on relational databases have worse consequences than their file-injection counterparts on unstructured databases. Moreover, we discuss some techniques to reduce the effectiveness of inference attacks exploiting the access pattern leakage existing in SSE schemes. To the best of our knowledge, this is the first work that investigates the security of relational databases protected
by SSE schemes
Domain-Agnostic Discovery of Similarities and Concepts at Scale
No full textAppropriately defining and efficiently calculating similarities from large data sets are often essential in data mining, both for gaining understanding of data and generating processes, and for building tractable representations. Given a set of objects and their correlations, we here rely on the premise that each object is characterized by its context, i.e. its correlations to the other objects. The similarity between two objects can then be expressed in terms of the similarity between their contexts. In this way, similarity pertains to the general notion that objects are similar if they are exchangeable in the data. We propose a scalable approach for calculating all relevant similarities among objects by relating them in a correlation graph that is transformed to a similarity graph. These graphs can express rich structural properties among objects. Specifically, we show that concepts - abstractions of objects - are constituted by groups of similar objects that can be discovered by clustering the objects in the similarity graph. These principles and methods are applicable in a wide range of fields, and will here be demonstrated in three domains: computational linguistics, music and molecular biology, where the numbers of objects and correlations range from small to very large
Industrial Wireless IP-based Cyber Physical Systems
No full textIndustrial control systems have traditionally been built around dedicated wired solutions. The requirements of flexibility, mobility, and cost have created a strong push toward wireless solutions, preferably solutions requiring low power. Simultaneously, the increased need for interoperability and integration with the wider Internet made a transition to IP-based communication unavoidable. Following these trends, we survey 6TiSCH, the emerging family of standards for IP-based industrial communication over low-power and lossy networks. We describe the state of the standardization work, the major issues being discussed, and open questions recently identified. Based on extensive first-hand experience, we discuss challenges in implementation of this new wave of standards. Lessons learned are highlighted from four popular open-source implementations of these standards: OpenWSN, Contiki, RIOT, and TinyOS. We outline major requirements, present insights from early interoperability testing and performance evaluations, and provide guidelines for chip manufacturers and implementers
CrossZig: Combating Cross-Technology Interference in Low-power Wireless Networks
No full textLow-power wireless devices suffer notoriously from Cross- Technology Interference (CTI). To enable co-existence, researchers have proposed a variety of interference mitigation strategies. Existing solutions, however, are designed to work with the limitations of currently available radio chips. In this paper, we investigate how to exploit physical layer properties of 802.15.4 signals to better address CTI. We present CrossZig, a cross-layer solution that takes advantage of physical layer information and processing to improve low-power communication under CTI. To this end, CrossZig utilizes physical layer information to detect presence of CTI in a corrupted packet and to apply an adaptive packet recovery which incorporates a novel cross-layer based packet merging and an adaptive FEC coding. We implement a prototype of CrossZig for the low-power IEEE 802.15.4 in a software-defined radio platform. We show the adaptability and the performance gain of CrossZig through experimental evaluation considering both micro-benchmarking and system performance under various interference patterns. Our results demonstrate that CrossZig can achieve a high accuracy in error localization (94.3% accuracy) and interference type identification (less than 5% error rate for SINR ranges below 3 dB). Moreover, our system shows consistent performance improvements under interference from various interfering technologies