Selection of appropriate software development life cycle using fuzzy logic

2013 ◽  
Vol 25 (3) ◽  
pp. 797-810 ◽  
Author(s):  
Veysi Öztürk
Author(s):  
Sharefa Murad

Cloud computing is getting probably the most objective, purpose, and dreams in most IT organizations on account of the advantages they are getting by relocating their advancements into it like expense and asset sparing. Green blurring processing is turning into a significant pattern with a solid relationship with distributed computing. It is about green and productivity that won't just prompt a superior business yet in addition a superior world. This paper will discuss a major phase of the software development life cycle, which is an arrangement, and how the selection of sending computerization is superior to the manual one particularly in a manner to make your cloud green.  


Author(s):  
Andriy Lishchytovych ◽  
Volodymyr Pavlenko

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.


Author(s):  
Sampada G.C ◽  
Tende Ivo Sake ◽  
Amrita

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.


2016 ◽  
Vol 685 ◽  
pp. 881-885
Author(s):  
Alexey Ponomarev ◽  
Hitesh S. Nalamwar

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


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