Automation tools for building blocks in Software Process
Last Updated :
15 Nov, 2023
Process automation generally refers to use of digital technology simply to work and perform a process or processes. This is done to accomplish or complete workflow or function. To an iterative process, process automation and change management is a very critical one. Even if change will be too expensive, then development will resist and won’t allow it. To automate process of software development, various tools are available nowadays.

In diagram given above, some of important tools are included and introduced that are very much needed across overall software process and correlates very well to process framework. Each of tools of software development map closely to one of process workflows and each of these process workflows have a distinct for automation support. Workflow automation generally makes complicated software process in an easy way to manage. Here you will see environment that is necessary to support process framework. Some of concerns are associated with each workflow are given below :
- Management : Nowadays, there are several opportunities and chances available for automation of project planning and control activities of management workflow. For creating planning artifacts, several tools are useful such as software cost estimation tools and Work Breakdown Structure (WBS) tools. Workflow management software is an advanced platform that provides flexible tools to improve way you work in an efficient manner. Thus, automation support can also improve insight into metrics.
- Environment : Automating development process and also developing an infrastructure for supporting different project workflows are very essential activities of engineering stage of life-cycle. environment that generally gives and provides process automation is a tangible artifact that is generally very critical to life-cycle of system being developed. Even, top-level WBS recognizes environment like a first-class workflow. Integrating their own environment and infrastructure for software development is one of main tasks for most of software organizations.
- Requirements : Requirements management is a very systematic approach for identifying, documenting, organizing, and tracking changing requirements of a system. It is also responsible for establishing and maintaining agreement between user or customer and project team on changing requirements of system. If process wants strong traceability among requirements and design, then architecture is very much likely to evolve in a way that it optimizes requirements traceability other than design integrity. This effect is even more and highly effective and pronounced if tools are used for process automation. For effective requirement management, points that must include are maintaining a clear statement of requirements with attributes for every type of requirement and traceability to other requirements and other project artifacts.
- Design : Workflow design is actually a visual depiction of each step that is involved in a workflow from start to end. It generally lays out each and every task sequentially and provides complete clarity into how data moves from one task to another one. Workflow design tools simply allow us to depict different tasks involved graphically as well as also depict performers, timelines, data, and other aspects that are crucial to execution. Visual modeling is primary support that is required and essential for design workflow. Visual model is generally used for capturing design models, representing them in a human-readable format, and also translating them into source code.
- Implementation : The main focus and purpose of implementation workflow are to write and initially test software, relies primarily on programming environment (editor, compiler, debugger, etc.). But on other hand, it should also include substantial integration along with change management tools, visual modeling tools, and test automation tools. This is simply required to just support iteration to be productive. It is main focus of Construction phase. The implementation simply means to transform a design model into executable one.
- Assessment and Deployment : Workflow assessment is initial step to identifying outdated software processes and just replace them with most effective process. This generally combines domain expertise, qualitative and quantitative information gathering and collection, proprietary tools, and much more. It requires and needs every tool discussed along with some additional capabilities simply to support test automation and test management. Defect tracking is also a tool that supports assessment.
More Automation Tools for building blocks in Software Process are-
- Version Control: Git is a popular tool for version control, which is an essential step in the software development process. Git is a system for sharing version control that keeps track of changes, manages branches and offers a history of code alterations to enable collaborative development. Its automated features to simplify the integration of code and reduce the possibility of disputes among team members.
- Static analysis and code quality: SonarQube is an effective tool for ongoing code quality inspection. It does static code analysis, finding and emphasizing errors, security flaws and code issues. Furthermore, by spotting and resolving problems with coding standards and guidelines, linters like Pylint and ESLint are essential to maintain code quality.
- Monitoring and Logging: Prometheus is quite good at gathering and storing metrics from different systems, as well as monitoring and sending out alerts. For consolidated logging and log analysis, the ELK Stack (Elasticsearch, Logstash, Kibana) provides a comprehensive solution. By automating the procedures of troubleshooting and monitoring, these technologies guarantee the dependability and efficiency of software programmes.
- Containerization: By encapsulating apps and their dependencies, Docker transforms software packaging. By simplifying installing, scaling and management of containerized applications, Kubernetes enhances Docker. When combined, these solutions offer a scalable and consistent environment that makes resource utilization effective and portable across a range of deployment scenarios.
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