Metric based Performance Measurement of Software Development Methodologies from Traditional to DevOps Automation Culture

Poonam Narang,Pooja Mittal International Journal of Computer ScienceNetwork S 2023 International journal of computer science and netw Vol.23 No.6

Successful implementations of DevOps practices significantly improvise software efficiency, collaboration and security. Most of the organizations are adopting DevOps for faster and quality software delivery. DevOps brings development and operation teams together to overcome all kind of communication gaps responsible for software failures. It relies on different sets of alternative tools to automate the tasks of continuous integration, testing, delivery, deployment and monitoring. Although DevOps is followed for being very reliable and responsible environment for quality software delivery yet it lacks many quantifiable aspects to prove it on the top of other traditional and agile development methods. This research evaluates quantitative performance of DevOps and traditional/ agile development methods based on software metrics. This research includes three sample projects or code repositories to quantify the results and for DevOps integrated selective tool chain; current research considers our earlier proposed and implemented DevOps hybrid model of integrated automation tools. For result discussion and validation, tabular and graphical comparisons have also been included to retrieve best performer model. This comparative and evaluative research will be of much advantage to our young researchers/ students to get well versed with automotive environment of DevOps, latest emerging buzzword of development industries.

Development of an Automation Tool for the Three-Dimensional Finite Element Analysis of Machine Tool Spindles

Jin-Woo Choi 한국생산제조학회 2015 한국생산제조학회지 Vol.24 No.2

In this study, an automation tool was developed for rapid evaluation of machine tool spindle designs with automated three-dimensional finite element analysis (3D FEA) using solid elements. The tool performs FEA with the minimum data of point coordinates to define the section of the spindle shaft and bearing positions. Using object-oriented programming techniques, the tool was implemented in the programming environment of a CAD system to make use of its objects. Its modules were constructed with the objects to generate the geometric model and then to convert it into the FE model of 3D solid elements at the workbenches of the CAD system using the point data. Graphic user interfaces were developed to allow users to interact with the tool. This tool is helpful for identification of a near optimal design of the spindle based on, for example, stiffness with multiple design changes and then FEAs.

Development of an Automation Tool for the Three-Dimensional Finite Element Analysis of Machine Tool Spindles

Choi, Jin-Woo The Korean Society of Manufacturing Technology Eng 2015 한국생산제조학회지 Vol.24 No.2

In this study, an automation tool was developed for rapid evaluation of machine tool spindle designs with automated three-dimensional finite element analysis (3D FEA) using solid elements. The tool performs FEA with the minimum data of point coordinates to define the section of the spindle shaft and bearing positions. Using object-oriented programming techniques, the tool was implemented in the programming environment of a CAD system to make use of its objects. Its modules were constructed with the objects to generate the geometric model and then to convert it into the FE model of 3D solid elements at the workbenches of the CAD system using the point data. Graphic user interfaces were developed to allow users to interact with the tool. This tool is helpful for identification of a near optimal design of the spindle based on, for example, stiffness with multiple design changes and then FEAs.

Development of an Automation Tool for the Three-Dimensional Finite Element Analysis of Machine Tool Spindles

최진우 한국생산제조학회 2015 한국생산제조학회지 Vol.24 No.2

In this study, an automation tool was developed for rapid evaluation of machine tool spindle designs with automated three-dimensional finite element analysis (3D FEA) using solid elements. The tool performs FEA with the minimum data of point coordinates to define the section of the spindle shaft and bearing positions. Using object-oriented programming techniques, the tool was implemented in the programming environment of a CAD system to make use of its objects. Its modules were constructed with the objects to generate the geometric model and then to convert it into the FE model of 3D solid elements at the workbenches of the CAD system using the point data. Graphic user interfaces were developed to allow users to interact with the tool. This tool is helpful for identification of a near optimal design of the spindle based on, for example, stiffness with multiple design changes and then FEAs.

공작기계 설계자동차 적용방안 연구

여진욱,편영식 한국공작기계학회 1999 한국공작기계학회 추계학술대회논문집 Vol.1999 No.-

The purpose of the present. paper are not to develope machine tools of new concepts and advanced mechanisms but to introduce and apply new methods and concepts in the design procedure by using and changing the previously existing technologies. In this paper 3D modeller was proposed for designing machine tools and the design automation software(DesignMecha 2000) was used. 3D modeller enabled more fast design and the better manufacturability checking than 2D one so that design error was dramatically reduced. As designer may easily understand the real shape of a part and assembly object, it's easy to draw the drawings not only in a conceptual design but also in a detailed design. Also, design automation software enabled designer to consider the real important design parameters by reducing time to spend in estimating and calculating the strength of the model by the computer aided automatic calculation instead of a tedious and complex: calculation by manual method and help him to easily make the decision for selecting the stocks and design the structure of part or unit of machine tools.

Development of a Tool for Automation of Finite Element Analysis of a Shaft-Bearing System of Machine Tools

Jin-Woo Choi(최진우),Gi-Young Kang(강기영) 한국기계가공학회 2019 한국기계가공학회지 Vol.18 No.6

We have developed a tool that uses finite element analysis (FEA) to rapidly evaluate a shaft-bearing system of machine tools. We extracted commercial data on suitable clamping units and defined the inner profile of the shaft to avoid needing direct user input to define the profile. We use a splitting algorithm to convert the shaft into beam elements with two diameters and length. To validate the tool, we used it to design and evaluate a shaft-bearing system and found that our tool automated the construction of an FE system model in a commercial FEA package as well as the static stiffness evaluation; both tasks were completed in seconds, demonstrating a significant reduction from the minutes normally required to complete these tasks manually.

4차산업으로 인한 공작기계산업의 새로운 안전문제

박영석 한국안전학회 2022 한국안전학회지 Vol.37 No.4

The purposes of this study were to suggest 1) a future direction for Korea's machine tool industry and 2) how to secure the safety and reliability of emerging intelligent or automated machine tooling. The study concludes that, overseas, the machine tool industry is growing again while promoting innovation by converging with ICT. Accordingly, Korea also promotes ICT innovation to advance the machine tool industry, which is at the core of the national economy. As a result, unlike in the past, the frequency of serious injuries like entrapment accidents has recently decreased, while the proportion of collision accidents has increased. In addition, a new type of accident has become possible. Since ICT is network-based, the distinction between work and rest can become ambiguous; there is a risk of hacking, working hours and places are flexible and there are risk factors for diseases like chronic fatigue due to overload of specific personnel. As robots and automation are introduced, there is also a high probability of problems caused by physical and psychological burdens on system operators and resulting fatigue.

공작기계 구조물의 전산 모델링 자동화

이찬홍(Chan Hong Lee),하태호(Tae Ho Ha),이재학(Jae Hak Lee) Korean Society for Precision Engineering 2012 한국정밀공학회지 Vol.29 No.10

The FEM analysis of machine tools is the general analysis process to evaluate machine performance in the industry for a long time. Despite advances in FEM software, because of difficult simplicity of CAD drawing, little experience of joints stiffness modeling and troublesome manual contact area divide for bindings, the industry designers think the FEM analysis is still an area of FEM analysis expert. In this paper, the automation of modeling process with simplicity of drawing, modeling of joints and contact area divide is aimed at easy FEM analysis to enlarge utilization of a virtual machine tools. In order to verify the effects of modeling automation, a slant bed type model with tilting table is analyzed. The results show FEM modeling automation method only needed 45 minutes to complete the whole modeling process, while manual modeling method requires almost one month with 8200 calculations for coordinate transformations and stiffness data input.

Machine Learning Frameworks for Automated Software Testing Tools : A Study

김정호,류정우,신현정,송진희 한국콘텐츠학회 2017 International Journal of Contents Vol.13 No.1

Increased use of software and complexity of software functions, as well as shortened software quality evaluation periods, have increased the importance and necessity for automation of software testing. Automating software testing by using machine learning not only minimizes errors in manual testing, but also allows a speedier evaluation. Research on machine learning in automated software testing has so far focused on solving special problems with algorithms, leading to difficulties for the software developers and testers, in applying machine learning to software testing automation. This paper, proposes a new machine learning framework for software testing automation through related studies. To maximize the performance of software testing, we analyzed and categorized the machine learning algorithms applicable to each software test phase, including the diverse data that can be used in the algorithms. We believe that our framework allows software developers or testers to choose a machine learning algorithm suitable for their purpose.

Machine Learning Frameworks for Automated Software Testing Tools : A Study

Kim, Jungho,Ryu, Joung Woo,Shin, Hyun-Jeong,Song, Jin-Hee The Korea Contents Association 2017 International Journal of Contents Vol.13 No.1

Increased use of software and complexity of software functions, as well as shortened software quality evaluation periods, have increased the importance and necessity for automation of software testing. Automating software testing by using machine learning not only minimizes errors in manual testing, but also allows a speedier evaluation. Research on machine learning in automated software testing has so far focused on solving special problems with algorithms, leading to difficulties for the software developers and testers, in applying machine learning to software testing automation. This paper, proposes a new machine learning framework for software testing automation through related studies. To maximize the performance of software testing, we analyzed and categorized the machine learning algorithms applicable to each software test phase, including the diverse data that can be used in the algorithms. We believe that our framework allows software developers or testers to choose a machine learning algorithm suitable for their purpose.