A Novel Model for Aligning Knowledge Management Activities within the Process of Developing Quality Software

2020 ◽  
Vol 13 (3) ◽  
pp. 470-476
Author(s):  
Omar Sabri
Keyword(s):  
Knowledge Management ◽  
Life Cycle ◽  
Software Development ◽  
Success Factors ◽  
Building Blocks ◽  
It Infrastructure ◽  
Development Life Cycle ◽  
Development Processes ◽  
Software Development Life Cycle ◽  
Novel Model

Background: Currently, the organization's competitive advantage is based on critical decisions to achieve their objectives by understanding the power of knowledge as a source within the organizations. However, there is a lack of qualitative models/frameworks for integrating Knowledge Life Cycle (KLC) within software development life cycle SDLC. Therefore, the goal of this research is to involve Knowledge Management activities within the SDLC in Information Technology companies to produce quality software. With the help of knowledge movements within the companies, the quality of provided software is used to improve organizations performance and products better and faster. Methods: This research highlights the importance of Knowledge Management activities during a typical software development process to provide the software as a final product/target. Moreover, the paper proposes a model to explain the relationships between knowledge management activities within the process of software development life cycle to produce quality software using three basic building blocks: people, organizations, and technologies. The success factors for the blocks are selected depending on the most recent literature occurrences and on their fitness to the nature of this study. Results: The research proposes a novel model for the success factors to evaluate the effects of the building blocks, and workflows during the software development processes. The selected success factors for the blocks are (Training, Leadership, Teamwork, Trust, IT Infrastructure, Culture, and strategies). Also, the research demonstrates the relationships between KM success factors and SDLC to produce quality software. Conclusion: In this research, we proposed a novel model to explain the relationships between knowledge management activities within the process of software development life cycle to produce quality software using three basic building blocks: people, organizations, and technologies. We selected seven success factors for the blocks depending on: 1) their importance and occurrence in a number of literature by many authors; and 2) their fitness to the nature of this study. The success factors (Training, Leadership, Teamwork, Trust, IT Infrastructure, Culture, and strategies) of the proposed model can be used to evaluate the effects of people, organizations, technologies, and workflows during the software development processes to obtain the required software quality. Finally, a quantitative study will be implemented to investigate the proposed hypothesis and to measure factors influencing the suggested model. By assessing to which degree these factors are present/ absent within the SDLC process the managers will be able to address the weakness by preparing a suitable plan and produce quality software.

A Systematic Review and Catalog of Security Metric during the Secure Software Development Life Cycle

2020 ◽  
Vol 13 ◽  
Author(s):  
Sampada G.C ◽  
Tende Ivo Sake ◽  
Amrita
Keyword(s):  
Systematic Review ◽  
Life Cycle ◽  
Software Development ◽  
Software Security ◽  
Security Assessment ◽  
Security Metrics ◽  
Development Life Cycle ◽  
Development Processes ◽  
Secure Software Development ◽  
Software Development Life Cycle

Background: With the advancement in the field of software development, software poses threats and risks to customers’ data and privacy. Most of these threats are persistent because security is mostly considered as a feature or a non-functional requirement, not taken into account during the software development life cycle (SDLC). Introduction: In order to evaluate the security performance of a software system, it is necessary to integrate the security metrics during the SDLC. The appropriate security metrics adopted for each phase of SDLC aids in defining the security goals and objectives of the software as well as quantify the security in the software. Methods: This paper presents systematic review and catalog of security metrics that can be adopted during the distinguishable phases of SDLC, security metrics for vulnerability and risk assessment reported in the literature for secure development of software. The practices of these metrics enable software security experts to improve the security characteristics of the software being developed. The critical analysis of security metrics of each phase and their comparison are also discussed. Results: Security metrics obtained during the development processes help to improve the confidentiality, integrity, and availability of software. Hence, it is imperative to consider security during the development of the software, which can be done with the use of software security metrics. Conclusion: This paper reviews the various security metrics that are meditated in the copious phases during the progression of the SDLC in order to provide researchers and practitioners with substantial knowledge for adaptation and further security assessment.

scholarly journals DevOPS Now and Then

2020 ◽  
Author(s):  
Raju Singh
Keyword(s):  
Life Cycle ◽  
Software Development ◽  
Continuous Improvement ◽  
Building Blocks ◽  
Extended Version ◽  
Agile Method ◽  
Development Cycle ◽  
Development Life Cycle ◽  
Continuous Delivery ◽  
Software Development Life Cycle

DevOps is an emerging practice to be followed in the Software Development life cycle. The name DevOps indicates that it’s an integration of the Development and Operation team. It is followed to integrate the various stages of the development cycle. DevOps is an extended version of the existing Agile method. DevOps aims at continuous integration, Continuous Delivery, Continuous Improvement, faster feedback and security. This paper reviews the building blocks of DevOps, challenges in adopting DevOps, Models to improve DevOps practices and Future works on DevOps

ECSE

2014 ◽  
pp. 296-309 ◽  
Author(s):  
Sakgasit Ramingwong ◽  
Lachana Ramingwong
Keyword(s):  
Life Cycle ◽  
Software Development ◽  
Engineering Students ◽  
Major Influence ◽  
Engineering Construction ◽  
Software Products ◽  
Development Life Cycle ◽  
Critical Issues ◽  
Development Processes ◽  
Software Development Life Cycle

Software development is uniquely different especially when compared to other engineering processes. The abstractness of software products has a major influence on the entire software development life cycle, which results in a number of uniquely important challenges. This chapter describes and discusses Engineering Construction for Software Engineers (ECSE), an effective workshop that helps software engineering students to understand some of these critical issues within a short period of time. In this workshop, the students are required to develop a pseudo-software product from scratch. They could learn about unique characteristics and risks of software development life cycle as well as other distinctive phenomenon through the activities. The workshop can still be easily followed by students who are not familiar with certain software development processes such as coding or testing.

ECSE

2017 ◽  
pp. 191-205
Author(s):  
Sakgasit Ramingwong ◽  
Lachana Ramingwong
Keyword(s):  
Life Cycle ◽  
Software Development ◽  
Engineering Students ◽  
Major Influence ◽  
Engineering Construction ◽  
Software Products ◽  
Development Life Cycle ◽  
Critical Issues ◽  
Development Processes ◽  
Software Development Life Cycle

Software development is uniquely different especially when compared to other engineering processes. The abstractness of software products has a major influence on the entire software development life cycle, which results in a number of uniquely important challenges. This chapter describes and discusses Engineering Construction for Software Engineers (ECSE), an effective workshop that helps software engineering students to understand some of these critical issues within a short period of time. In this workshop, the students are required to develop a pseudo-software product from scratch. They could learn about unique characteristics and risks of software development life cycle as well as other distinctive phenomenon through the activities. The workshop can still be easily followed by students who are not familiar with certain software development processes such as coding or testing.

scholarly journals Analysis of the Veracities of Industry Used Software Development Life Cycle Methodologies

2020 ◽  
Vol 16 (2) ◽  
Author(s):  
AZM Ehtesham Chowdhury ◽  
Abhijit Bhowmik ◽  
Hasibul Hasan ◽  
Md Shamsur Rahim
Keyword(s):  
Life Cycle ◽  
Comparative Analysis ◽  
Software Development ◽  
Modern Human ◽  
Successful Development ◽  
Software Applications ◽  
Use Of Technology ◽  
Development Life Cycle ◽  
Development Processes ◽  
Software Development Life Cycle

Currently, software industries are using different SDLC (software development life cycle) models which are designed for specific purposes. The use of technology is booming in every perspective of life and the software behind the technology plays an enormous role. As the technical complexities are increasing, successful development of software solely depends on the proper management of development processes. So, it is inevitable to introduce improved methodologies in the industry so that modern human centred software applications development can be managed and delivered to the user successfully. So, in this paper, we have explored the facts of different SDLC models and perform their comparative analysis.

Computable metrics of personal performance in software development teams

2019 ◽  
Author(s):  
Andriy Lishchytovych ◽  
Volodymyr Pavlenko
Keyword(s):  
Life Cycle ◽  
Software Development ◽  
Product Quality ◽  
Performance Indicators ◽  
Key Performance Indicators ◽  
Project Manager ◽  
Development Life Cycle ◽  
Software Product ◽  
Software Development Life Cycle

The present article describes setup, configuration and usage of the key performance indicators (KPIs) of members of project teams involved into the software development life cycle. Key performance indicators are described for the full software development life cycle and imply the deep integration with both task tracking systems and project code management systems, as well as a software product quality testing system. To illustrate, we used the extremely popular products - Atlassian Jira (tracking development tasks and bugs tracking system) and git (code management system). The calculation of key performance indicators is given for a team of three developers, two testing engineers responsible for product quality, one designer, one system administrator, one product manager (responsible for setting business requirements) and one project manager. For the key members of the team, it is suggested to use one integral key performance indicator per the role / team member, which reflects the quality of the fulfillment of the corresponding role of the tasks. The model of performance indicators is inverse positive - the initial value of each of the indicators is zero and increases in the case of certain deviations from the standard performance of official duties inherent in a particular role. The calculation of the proposed key performance indicators can be fully automated (in particular, using Atlassian Jira and Atlassian Bitbucket (git) or any other systems, like Redmine, GitLab or TestLink), which eliminates the human factor and, after the automation, does not require any additional effort to calculate. Using such a tool as the key performance indicators allows project managers to completely eliminate bias, reduce the emotional component and provide objective data for the project manager. The described key performance indicators can be used to reduce the time required to resolve conflicts in the team, increase productivity and improve the quality of the software product.

Software Traceability – A Key to Improve Software Evolution

2016 ◽  
Vol 685 ◽  
pp. 881-885
Author(s):  
Alexey Ponomarev ◽  
Hitesh S. Nalamwar
Keyword(s):  
Life Cycle ◽  
Software Development ◽  
Software Evolution ◽  
Software Traceability ◽  
Development Life Cycle ◽  
Methods And Techniques ◽  
Software Development Life Cycle

Software traceability is an important part in software development that is getting more and more attention nowadays from organizations and researchers. The paper outlines the importance, different methods and techniques of software traceability. It also explains the need of automating traceability, problems and drawbacks of existing traceability tools, the ongoing challenges facing implementation of traceability in software development life cycle, and finally the paper discusses whether software traceability should be mandated as a key to improve software evolution

Project Implementation Decision Using Software Development Life Cycle Models: A Comparative Approach

2021 ◽  
Vol 28 (1) ◽  
Author(s):  
M.A. Adeagbo ◽  
J.E.T. Akinsola ◽  
A.A. Awoseyi ◽  
F. Kasali
Keyword(s):  
Life Cycle ◽  
Comparative Analysis ◽  
Software Development ◽  
Cost Estimation ◽  
Comparative Approach ◽  
Project Implementation ◽  
Development Life Cycle ◽  
Software Development Life Cycle ◽  
Waterfall Model ◽  
Spiral Model

Selection of a suitable Software Development Life Cycle (SDLC) model for project implementation is somewhat confusing as there are a lot of SDLC models with similar strengths and weaknesses. Also, the solutions proffered among the researchers so far have been the  qualitative comparative analysis of SDLC models. Hence, this paper proposes a comparative analysis of SDLC models using quantitative approach in relation to strengths and weaknesses of SDLC models. The study adapted comparative analysis and Software Development Life Cycle (SDLC) models features’ classification using ten characteristics such as project complexity, project size, project duration, project with risk, implementation/initial cost, error discovery, associated cost, risk analysis, maintenance and cost estimation. A quantitative measure that employs online survey using experts in software design and engineering, project management and system analysis was carried out for the evaluation of SDLC models. Purposeful Stratified Random Sampling (SRS) technique was used to gather the data for analysis using XLSTAT after pre-processing, taking into consideration both benefit and cost criteria. The overall performance evaluation showed that Spiral-Model is the best followed by V-Model and lastly Waterfall Model with comparative values of 38.63%, 35.76% and 25.61% respectively. As regards cost estimation, Waterfall Model is the most efficient with value of 41%, then V-Model with 31% and lastly Spiral Model with 28%. V-Model has great error recovery capability with value of 45% which is closely followed by Spiral Model with 37% and lastly Waterfall Model with 18%. The study revealed that, a model with efficient risk assurance does not guarantee efficient cost management. In the future work, more characteristics regarding SDLC models shall be considered.

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