scholarly journals Systematic mapping study: On the coverage of aspect-oriented methodologies for the early phases of the software development life cycle

2020 ◽  
Author(s):  
Fernando Pinciroli ◽  
Jose Luis Barros Justo ◽  
Raymundo Forradellas
Keyword(s):  
Life Cycle ◽  
Software Development ◽  
Systematic Mapping Study ◽  
Mapping Study ◽  
Systematic Mapping ◽  
Development Life Cycle ◽  
Software Development Life Cycle ◽  
Early Phases

scholarly journals Formal methods in software development: A road less travelled

2010 ◽  
Vol 45 ◽  
Author(s):  
John A Van der Poll
Keyword(s):  
Life Cycle ◽  
Software Development ◽  
Formal Methods ◽  
Formal Specification ◽  
The Other ◽  
Formal Specifications ◽  
Development Life Cycle ◽  
Software Development Life Cycle ◽  
Verification Techniques ◽  
Early Phases

An integration of traditional verification techniques and formal specifications in software engineering is presented. Advocates of such techniques claim that mathematical formalisms allow them to produce quality, verifiably correct, or at least highly dependable software and that the testing and maintenance phases are shortened. Critics on the other hand maintain that software formalisms are hard to master, tedious to use and not well suited for the fast turnaround times demanded by industry. In this paper some popular formalisms and the advantages of using these during the early phases of the software development life cycle are presented. Employing the Floyd-Hoare verification principles during the formal specification phase facilitates reasoning about the properties of a specification. Some observations that may help to alleviate the formal-methods controversy are established and a number of formal methods successes is presented. Possible conditions for an increased acceptance of formalisms in oftware development are discussed.

Concurrent Modeling in Early Phases of the Software Development Life Cycle

2010 ◽  
pp. 129-144 ◽  
Author(s):  
Petra Brosch ◽  
Philip Langer ◽  
Martina Seidl ◽  
Konrad Wieland ◽  
Manuel Wimmer ◽  
...  
Keyword(s):  
Life Cycle ◽  
Software Development ◽  
Development Life Cycle ◽  
Software Development Life Cycle ◽  
Early Phases

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.

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