131,355 research outputs found
Integrating automated support for a software management cycle into the TAME system
Software managers are interested in the quantitative management of software quality, cost and progress. An integrated software management methodology, which can be applied throughout the software life cycle for any number purposes, is required. The TAME (Tailoring A Measurement Environment) methodology is based on the improvement paradigm and the goal/question/metric (GQM) paradigm. This methodology helps generate a software engineering process and measurement environment based on the project characteristics. The SQMAR (software quality measurement and assurance technology) is a software quality metric system and methodology applied to the development processes. It is based on the feed forward control principle. Quality target setting is carried out before the plan-do-check-action activities are performed. These methodologies are integrated to realize goal oriented measurement, process control and visual management. A metric setting procedure based on the GQM paradigm, a management system called the software management cycle (SMC), and its application to a case study based on NASA/SEL data are discussed. The expected effects of SMC are quality improvement, managerial cost reduction, accumulation and reuse of experience, and a highly visual management reporting system
Software Measurement Activities in Small and Medium Enterprises: an Empirical Assessment
An empirical study for evaluating the proper implementation of measurement/metric programs in software companies in one area of Turkey is presented. The research questions are discussed and validated with the help of senior software
managers (more than 15 years’ experience) and then used for interviewing a variety of medium and small scale software companies in Ankara. Observations show that there is a
common reluctance/lack of interest in utilizing measurements/metrics despite the fact that they are well known in the industry. A side product of this research is that internationally recognized standards such as ISO and CMMI are pursued if they are a part of project/job
requirements; without these requirements, introducing those standards to the companies remains as a long-term target to increase quality
Production of Reliable Flight Crucial Software: Validation Methods Research for Fault Tolerant Avionics and Control Systems Sub-Working Group Meeting
The state of the art in the production of crucial software for flight control applications was addressed. The association between reliability metrics and software is considered. Thirteen software development projects are discussed. A short term need for research in the areas of tool development and software fault tolerance was indicated. For the long term, research in format verification or proof methods was recommended. Formal specification and software reliability modeling, were recommended as topics for both short and long term research
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Practitioner-based measurement: a collaborative software measurement approach
A Process to Implement an Artificial Neural Network and Association Rules Techniques to Improve Asset Performance and Energy Efficiency
In this paper, we address the problem of asset performance monitoring, with the intention
of both detecting any potential reliability problem and predicting any loss of energy consumption
e ciency. This is an important concern for many industries and utilities with very intensive
capitalization in very long-lasting assets. To overcome this problem, in this paper we propose an
approach to combine an Artificial Neural Network (ANN) with Data Mining (DM) tools, specifically
with Association Rule (AR) Mining. The combination of these two techniques can now be done
using software which can handle large volumes of data (big data), but the process still needs to
ensure that the required amount of data will be available during the assets’ life cycle and that its
quality is acceptable. The combination of these two techniques in the proposed sequence di ers
from previous works found in the literature, giving researchers new options to face the problem.
Practical implementation of the proposed approach may lead to novel predictive maintenance models
(emerging predictive analytics) that may detect with unprecedented precision any asset’s lack of
performance and help manage assets’ O&M accordingly. The approach is illustrated using specific
examples where asset performance monitoring is rather complex under normal operational conditions.Ministerio de EconomÃa y Competitividad DPI2015-70842-
Annotated bibliography of Software Engineering Laboratory literature
An annotated bibliography of technical papers, documents, and memorandums produced by or related to the Software Engineering Laboratory is given. More than 100 publications are summarized. These publications cover many areas of software engineering and range from research reports to software documentation. All materials have been grouped into eight general subject areas for easy reference: The Software Engineering Laboratory; The Software Engineering Laboratory: Software Development Documents; Software Tools; Software Models; Software Measurement; Technology Evaluations; Ada Technology; and Data Collection. Subject and author indexes further classify these documents by specific topic and individual author
Continuous maintenance and the future – Foundations and technological challenges
High value and long life products require continuous maintenance throughout their life cycle to achieve required performance with optimum through-life cost. This paper presents foundations and technologies required to offer the maintenance service. Component and system level degradation science, assessment and modelling along with life cycle ‘big data’ analytics are the two most important knowledge and skill base required for the continuous maintenance. Advanced computing and visualisation technologies will improve efficiency of the maintenance and reduce through-life cost of the product. Future of continuous maintenance within the Industry 4.0 context also identifies the role of IoT, standards and cyber security
Correct and Control Complex IoT Systems: Evaluation of a Classification for System Anomalies
In practice there are deficiencies in precise interteam communications about
system anomalies to perform troubleshooting and postmortem analysis along
different teams operating complex IoT systems. We evaluate the quality in use
of an adaptation of IEEE Std. 1044-2009 with the objective to differentiate the
handling of fault detection and fault reaction from handling of defect and its
options for defect correction. We extended the scope of IEEE Std. 1044-2009
from anomalies related to software only to anomalies related to complex IoT
systems. To evaluate the quality in use of our classification a study was
conducted at Robert Bosch GmbH. We applied our adaptation to a postmortem
analysis of an IoT solution and evaluated the quality in use by conducting
interviews with three stakeholders. Our adaptation was effectively applied and
interteam communications as well as iterative and inductive learning for
product improvement were enhanced. Further training and practice are required.Comment: Submitted to QRS 2020 (IEEE Conference on Software Quality,
Reliability and Security
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