Refactorings of Design Defects using Relational Concept Analysis

Software engineers often need to identify and correct design defects, ıe} recurring design problems that hinder development and maintenance\ud by making programs harder to comprehend and--or evolve. While detection\ud of design defects is an actively researched area, their correction---mainly\ud a manual and time-consuming activity --- is yet to be extensively\ud investigated for automation. In this paper, we propose an automated\ud approach for suggesting defect-correcting refactorings using relational\ud concept analysis (RCA). The added value of RCA consists in exploiting\ud the links between formal objects which abound in a software re-engineering\ud context. We validated our approach on instances of the <span class='textit'></span>Blob\ud design defect taken from four different open-source programs

Testing microelectronic biofluidic systems

According to the 2005 International Technology Roadmap for Semiconductors, the integration of emerging nondigital CMOS technologies will require radically different test methods, posing a major challenge for designers and test engineers. One such technology is microelectronic fluidic (MEF) arrays, which have rapidly gained importance in many biological, pharmaceutical, and industrial applications. The advantages of these systems, such as operation speed, use of very small amounts of liquid, on-board droplet detection, signal conditioning, and vast digital signal processing, make them very promising. However, testable design of these devices in a mass-production environment is still in its infancy, hampering their low-cost introduction to the market. This article describes analog and digital MEF design and testing method

Using FCA to Suggest Refactorings to Correct Design Defects

Design defects are poor design choices resulting in a hard-to- maintain software, hence their detection and correction are key steps of a\ud disciplined software process aimed at yielding high-quality software\ud artifacts. While modern structure- and metric-based techniques enable\ud precise detection of design defects, the correction of the discovered\ud defects, e.g., by means of refactorings, remains a manual, hence\ud error-prone, activity. As many of the refactorings amount to re-distributing\ud class members over a (possibly extended) set of classes, formal concept\ud analysis (FCA) has been successfully applied in the past as a formal\ud framework for refactoring exploration. Here we propose a novel approach\ud for defect removal in object-oriented programs that combines the\ud effectiveness of metrics with the theoretical strength of FCA. A\ud case study of a specific defect, the Blob, drawn from the\ud Azureus project illustrates our approach

The use of job aids for visual inspection in manufacturing and maintenance

Visual inspection is a task regularly seen in manufacturing applications and is still primarily carried out by human operators. This study explored the use of job aids (anything used to assist the operator with the task, such as lists, check sheets or pictures) to assist with visual inspection within a manufacturing facility that inspects used parts. Job aids in the form of inspection manuals were used regularly during the inspection process, and how accurately they were followed was dependent on a number of factors such as size of part, experience of the operator, and accuracy of the inspection manuals. If the job aids were well structured, well written and accessible, then the inspectors were seen to follow them, however for certain jobs inspectors were seen to change the inspection order making inspection more efficient. The findings of the study suggest that prior experience can help in designing efficient, easy to use job aids and that a collaborative approach to design as well as using pictorial examples for comparison purposes would improve the inspection process

Knowledge-based support in Non-Destructive Testing for health monitoring of aircraft structures

Maintenance manuals include general methods and procedures for industrial maintenance and they contain information about principles of maintenance methods. Particularly, Non-Destructive Testing (NDT) methods are important for the detection of aeronautical defects and they can be used for various kinds of material and in different environments. Conventional non-destructive evaluation inspections are done at periodic maintenance checks. Usually, the list of tools used in a maintenance program is simply located in the introduction of manuals, without any precision as regards to their characteristics, except for a short description of the manufacturer and tasks in which they are employed. Improving the identification concepts of the maintenance tools is needed to manage the set of equipments and establish a system of equivalence: it is necessary to have a consistent maintenance conceptualization, flexible enough to fit all current equipment, but also all those likely to be added/used in the future. Our contribution is related to the formal specification of the system of functional equivalences that can facilitate the maintenance activities with means to determine whether a tool can be substituted for another by observing their key parameters in the identified characteristics. Reasoning mechanisms of conceptual graphs constitute the baseline elements to measure the fit or unfit between an equipment model and a maintenance activity model. Graph operations are used for processing answers to a query and this graph-based approach to the search method is in-line with the logical view of information retrieval. The methodology described supports knowledge formalization and capitalization of experienced NDT practitioners. As a result, it enables the selection of a NDT technique and outlines its capabilities with acceptable alternatives

Influence of parasitic capacitance variations on 65 nm and 32 nm predictive technology model SRAM core-cells

The continuous improving of CMOS technology allows the realization of digital circuits and in particular static random access memories that, compared with previous technologies, contain an impressive number of transistors. The use of new production processes introduces a set of parasitic effects that gain more and more importance with the scaling down of the technology. In particular, even small variations of parasitic capacitances in CMOS devices are expected to become an additional source of faulty behaviors in future technologies. This paper analyzes and compares the effect of parasitic capacitance variations in a SRAM memory circuit realized with 65 nm and 32 nm predictive technology model

Integrated process of images and acceleration measurements for damage detection

The use of mobile robots and UAV to catch unthinkable images together with on-site global automated acceleration measurements easy achievable by wireless sensors, able of remote data transfer, have strongly enhanced the capability of defect and damage evaluation in bridges. A sequential procedure is, here, proposed for damage monitoring and bridge condition assessment based on both: digital image processing for survey and defect evaluation and structural identification based on acceleration measurements. A steel bridge has been simultaneously inspected by UAV to acquire images using visible light, or infrared radiation, and monitored through a wireless sensor network (WSN) measuring structural vibrations. First, image processing has been used to construct a geometrical model and to quantify corrosion extension. Then, the consistent structural model has been updated based on the modal quantities identified using the acceleration measurements acquired by the deployed WSN. © 2017 The Authors. Published by Elsevier Ltd