scholarly journals Analysis of Low Code-No Code Development Platforms in comparison with Traditional Development Methodologies

2021 ◽  
Vol 9 (12) ◽  
pp. 508-513
Author(s):  
Shreyas Shridhar
Keyword(s):  
Life Cycle ◽  
New Information ◽  
Development Life Cycle ◽  
Software Development Life Cycle ◽  
Programming Skills ◽  
The Cost ◽  
Business Requirements ◽  
Close Fit ◽  
New System ◽  
Code Development

Abstract: This paper examines the overview of low-code/no-code development platforms in comparison with traditional development methodologies and examines the benefits and limitations of the same. For several decades, businesses have had multiple options when they demanded new information systems. They could develop a new system using in-house developers, or they could order a system from an external merchant. This offers a close fit to business obligations. However, nowadays, there is a new alternative that is becoming increasingly prevalent. Low code/no code (LC/NC) applications can cater to business requirements efficiently, can be implemented instantly, and the cost is much less than systems developed in-house. Few, if any, programming skills are required. Keywords: Traditional development, No code development, low code development, Low code No code development, Software development life cycle (SDLC)

Effort Estimation Model for each Phase of Software Development Life Cycle

2012 ◽  
pp. 238-246
Author(s):  
Sarah Afzal Safavi ◽  
Maqbool Uddin Shaikh
Keyword(s):  
Life Cycle ◽  
Software Development ◽  
Cost Estimation ◽  
Use Case ◽  
Effort Estimation ◽  
Cost Overrun ◽  
Estimation Model ◽  
Development Life Cycle ◽  
Software Development Life Cycle ◽  
The Cost

The assessment of main risks in software development discloses that a major threat of delays are caused by poor effort / cost estimation of the project. Low / poor cost estimation is the second highest priority risk [Basit Shahzad]. This risk can affect four out of a total five phases of the software development life cycle i.e. Analysis, Design, Coding and Testing. Hence targeting this risk alone may reduce the overall risk impact of the project by fifty percent. Architectural designing of the system is a great activity which consumes most of the time in SDLC. Obviously, effort is put forth to produce the design of the system. It is evident that none of the existing estimation models try to calculate the effort put on designing of the system. Although use case estimation model uses the use case points to estimate the cost. But what is the cost of creating use cases? One reason of poor estimates produced by existing models can be negligence of design effort/cost. Therefore it shall be well estimated to prevent any cost overrun of the project. We propose a model to estimate the effort in each of these phases rather than just relying upon the cost estimation of the coding phase only. It will also ease the monitoring of project status and comparison against planned cost and actual cost incurred so far at any point of time.

Effort Estimation Model for each Phase of Software Development Life Cycle

2011 ◽  
pp. 270-277
Author(s):  
Sarah Afzal Safavi ◽  
Maqbool Uddin Shaikh
Keyword(s):  
Life Cycle ◽  
Software Development ◽  
Cost Estimation ◽  
Use Case ◽  
Effort Estimation ◽  
Cost Overrun ◽  
Estimation Model ◽  
Development Life Cycle ◽  
Software Development Life Cycle ◽  
The Cost

The assessment of main risks in software development discloses that a major threat of delays are caused by poor effort / cost estimation of the project. Low / poor cost estimation is the second highest priority risk [Basit Shahzad]. This risk can affect four out of a total five phases of the software development life cycle i.e. Analysis, Design, Coding and Testing. Hence targeting this risk alone may reduce the overall risk impact of the project by fifty percent. Architectural designing of the system is a great activity which consumes most of the time in SDLC. Obviously, effort is put forth to produce the design of the system. It is evident that none of the existing estimation models try to calculate the effort put on designing of the system. Although use case estimation model uses the use case points to estimate the cost. But what is the cost of creating use cases? One reason of poor estimates produced by existing models can be negligence of design effort/cost. Therefore it shall be well estimated to prevent any cost overrun of the project. We propose a model to estimate the effort in each of these phases rather than just relying upon the cost estimation of the coding phase only. It will also ease the monitoring of project status and comparison against planned cost and actual cost incurred so far at any point of time.

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.

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.

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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