317,516 research outputs found
Software correlators as testbeds for RFI algorithms
In-correlator techniques offer the possibility of identifying and/or excising
radio frequency interference (RFI) from interferometric observations at much
higher time and/or frequency resolution than is generally possible with the
final visibility dataset. Due to the considerable computational requirements of
the correlation procedure, cross-correlators have most commonly been
implemented using high-speed digital signal processing boards, which typically
require long development times and are difficult to alter once complete.
"Software" correlators, on the other hand, make use of commodity server
machines and a correlation algorithm coded in a high-level language. They are
inherently much more flexible and can be developed - and modified - much more
rapidly than purpose-built "hardware" correlators. Software correlators are
thus a natural choice for testing new RFI detection and mitigation techniques
for interferometers. The ease with which software correlators can be adapted to
test RFI detection algorithms is demonstrated by the addition of kurtosis
detection and plotting to the widely used DiFX software correlator, which
highlights previously unknown short -duration RFI at the Hancock VLBA station.Comment: 6 pages, 1 figure, accepted for publication in Proceedings of Science
[PoS(RFI2010)035]. Presented at RFI2010, the Third Workshop on RFI Mitigation
in Radio Astronomy, 29-31 March 2010, Groningen, The Netherland
A Quality Model for Actionable Analytics in Rapid Software Development
Background: Accessing relevant data on the product, process, and usage
perspectives of software as well as integrating and analyzing such data is
crucial for getting reliable and timely actionable insights aimed at
continuously managing software quality in Rapid Software Development (RSD). In
this context, several software analytics tools have been developed in recent
years. However, there is a lack of explainable software analytics that software
practitioners trust. Aims: We aimed at creating a quality model (called
Q-Rapids quality model) for actionable analytics in RSD, implementing it, and
evaluating its understandability and relevance. Method: We performed workshops
at four companies in order to determine relevant metrics as well as product and
process factors. We also elicited how these metrics and factors are used and
interpreted by practitioners when making decisions in RSD. We specified the
Q-Rapids quality model by comparing and integrating the results of the four
workshops. Then we implemented the Q-Rapids tool to support the usage of the
Q-Rapids quality model as well as the gathering, integration, and analysis of
the required data. Afterwards we installed the Q-Rapids tool in the four
companies and performed semi-structured interviews with eight product owners to
evaluate the understandability and relevance of the Q-Rapids quality model.
Results: The participants of the evaluation perceived the metrics as well as
the product and process factors of the Q-Rapids quality model as
understandable. Also, they considered the Q-Rapids quality model relevant for
identifying product and process deficiencies (e.g., blocking code situations).
Conclusions: By means of heterogeneous data sources, the Q-Rapids quality model
enables detecting problems that take more time to find manually and adds
transparency among the perspectives of system, process, and usage.Comment: This is an Author's Accepted Manuscript of a paper to be published by
IEEE in the 44th Euromicro Conference on Software Engineering and Advanced
Applications (SEAA) 2018. The final authenticated version will be available
onlin
A Survey on Software Testing Techniques using Genetic Algorithm
The overall aim of the software industry is to ensure delivery of high
quality software to the end user. To ensure high quality software, it is
required to test software. Testing ensures that software meets user
specifications and requirements. However, the field of software testing has a
number of underlying issues like effective generation of test cases,
prioritisation of test cases etc which need to be tackled. These issues demand
on effort, time and cost of the testing. Different techniques and methodologies
have been proposed for taking care of these issues. Use of evolutionary
algorithms for automatic test generation has been an area of interest for many
researchers. Genetic Algorithm (GA) is one such form of evolutionary
algorithms. In this research paper, we present a survey of GA approach for
addressing the various issues encountered during software testing.Comment: 13 Page
A Model-Driven Approach for Business Process Management
The Business Process Management is a common mechanism recommended by a high number of standards for the management of companies and organizations. In software companies this practice is every day more accepted and companies have to assume it, if they want to be competitive. However, the effective definition of these processes and mainly their maintenance and execution are not always easy tasks. This paper presents an approach based on the Model-Driven paradigm for Business Process Management in software companies. This solution offers a suitable mechanism that was implemented successfully in different companies with a tool case named NDTQ-Framework.Ministerio de Educación y Ciencia TIN2010-20057-C03-02Junta de Andalucía TIC-578
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Fault-based regression testing in a reactive environment
Regression testing is the process of retesting software after modification. Regression testing is a major factor contributing to the high cost of software maintenance. To control this cost, regression testing must be accomplished efficiently through effective reuse of test cases and judicious generation of new test cases.Fault-based testing focuses on the detection of particular classes of faults. RELAY is a fault-based testing technique that guarantees the detection of errors caused by any fault in a chosen fault classification. RELAY can be used as a regression testing technique to generate the test cases required to demonstrate that a modification is properly made. In addition, the information related to a test case chosen to detect a potential fault guides in choosing previously-selected test cases that should be reused, for a given modification.This paper presents the concepts behind RELAY and discusses how RELAY could be used as a regression testing technique. It also describes a testing environment that supports reactive regression testing as well as testing throughout the development lifecycle, which is based on integrating the RELAY model with other testing techniques
Model-Based Security Testing
Security testing aims at validating software system requirements related to
security properties like confidentiality, integrity, authentication,
authorization, availability, and non-repudiation. Although security testing
techniques are available for many years, there has been little approaches that
allow for specification of test cases at a higher level of abstraction, for
enabling guidance on test identification and specification as well as for
automated test generation.
Model-based security testing (MBST) is a relatively new field and especially
dedicated to the systematic and efficient specification and documentation of
security test objectives, security test cases and test suites, as well as to
their automated or semi-automated generation. In particular, the combination of
security modelling and test generation approaches is still a challenge in
research and of high interest for industrial applications. MBST includes e.g.
security functional testing, model-based fuzzing, risk- and threat-oriented
testing, and the usage of security test patterns. This paper provides a survey
on MBST techniques and the related models as well as samples of new methods and
tools that are under development in the European ITEA2-project DIAMONDS.Comment: In Proceedings MBT 2012, arXiv:1202.582
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