Software Development Automation
Automate Your Way to Successful Software Delivery
With over 34 years of experience in delivering custom software, ScienceSoft offers a comprehensive guide to automating software development.
Software Development Automation: The Essence
Automation in software development is a way to minimize errors during the software development process, make it faster and more cost-efficient, and improve team collaboration and productivity.
Automation tools and techniques can be used at almost every step of the SDLC: requirements gathering, design, coding, testing, deployment and maintenance.
Note: Automation in software development and business automation are different areas. Software development automation focuses on improving the software development process, while business automation focuses on improving overall business operations. Business automation refers to the use of technology to automate various business processes, such as accounting, inventory management, and customer service.
If you are interested in business automation, please use the following links:
Software Development Automation at Every Step of SDLC
Below, ScienceSoft shows why and how to automate almost every software delivery stage.
Automation at this SDLC stage is very complex and challenging due to the subjective nature of requirements and the need for human input and interpretation. Still, it's possible to use tools to automate software requirements collection, analysis, and documentation.
Some of the possible tools include:
- Requirements management tools (Atlassian Jira, Trello, Asana, etc.): these tools provide a centralized repository for all requirements and allow stakeholders to collaborate on requirements in real time.
- Natural language processing tools: NLP tools can help extract requirements from natural language documents, such as user stories, emails, and chat logs. These tools use machine learning algorithms to identify key phrases and concepts in the text and convert them into structured data. However, today, we don't use these tools at ScienceSoft and don't see the NLP's wide adoption for this purpose.
Automation tools can help create and validate software design documents, ensure that they meet the necessary standards and requirements. Some of the automation opportunities at this stage include the use of:
- Design patterns (MVC, MVVM, Observer, etc.) that provide proven solutions to common architectural problems and can improve software quality and maintainability.
- Modeling tools (UML, ArchiMate, SysML, etc.) that help automate the process of creating software architecture diagrams. These tools provide a standardized notation for representing software architecture and allow stakeholders to collaborate on architecture design in real time.
- Architecture analysis tools (SonarQube, CAST, etc.) that help automate the process of analyzing software architecture for quality and compliance. These tools can identify potential issues in the architecture and provide recommendations for improvement.
The tools that help automate the process of writing code include:
- Integrated development environments (Eclipse, Visual Studio, NetBeans, etc.) provide such useful features as auto-completion, syntax highlighting, and debugging. These tools can reduce the time and effort required for coding and ensure that the code is consistent with the architecture.
- Low-code platforms (Microsoft Power Apps, OutSystems, Mendix, etc.) provide a visual, drag-and-drop interface for building applications. This allows developers to quickly create and modify application components without writing extensive lines of code. Low-code platforms also typically include pre-built templates and integrations, reducing the need for developers to start from scratch.
- Unit testing tools (JUnit, NUnit, PyUnit, TestNG, etc.) allow developers to write test cases that check the functionality of specific parts of their code and then run those tests automatically.
- Version control tools provide a centralized repository for source code, documentation, and other project assets. Version control tools automate code branching and merging, automatically track every code change, and perform code reviews.
- Code generation tools (Yeoman, Codesmith, MyGeneration, etc.) automate code generation from templates or models. There are also AI-based tools (like OpenAI) that analyze large amounts of data and learn from patterns to generate optimized code for specific tasks or applications. At ScienceSoft, we don't use these tools as we see they are yet in their infancy.
QA automation involves writing and running code-based test scripts to simulate user and software interactions. ScienceSoft's team usually automates regression and integration tests, cross-browser testing, performance testing, and security testing. For this, we use such tools as Selenium, Protractor, Appium, REST Assured, RestSharp frameworks and Apache JMeter.
Automation tools can assist in deploying software parts to various environments, such as development, testing, staging, and production.
At this stage, the most popular practices and tools include:
- Continuous integration and continuous deployment (CI/CD) tools (Jenkins, GitLab CI/CD, CircleCI, etc.) to automate the process of building, testing, and deploying applications. At ScienceSoft, we generally need 3–5 weeks to develop an efficient CI/CD process for a mid-sized software development project with several microservices, an API layer and a front-end part. The most sophisticated CI/CD process helps integrate, test and deploy new software functionality within 2–3 hours.
- Containerization tools (e.g., Docker and Kubernetes) can reduce the time and effort required to deploy an app in containers and ensure the app is always running in a consistent environment.
- Infrastructure-as-code (IaC) tools (e.g., Terraform and AWS CloudFormation) can reduce the time and effort to deploy the infrastructure resources the app requires and ensure that the infrastructure is always configured correctly.
The key practice at this stage is CI/CD pipeline implementation. CI/CD pipeline implementation does not require IaC and containerization, but both can be beneficial in achieving faster and more reliable deployments, ensuring consistency across different environments.
Automation can help monitor how the app behaves after the deployment and identify issues before they become problems.
At this stage, the most popular automation practices include the use of:
- Monitoring tools (Nagios, Zabbix, Datadog, etc.) that automatically monitor network services, hosts, and devices, and alert administrators when performance issues or risks of failure arise.
- Log analysis tools (Logstash, Splunk, Graylog, Logmatic, etc.) that automatically analyze logs for issues and potential failures.
- Configuration management tools (Ansible, Chef, Puppet, etc.) that help automate the management of app configurations.
- Patch management tools (WSUS, SCCM, etc.) that help automate the process of applying patches and updates to software.
Most Common Development Automation Challenges and Their Solutions
Lack of scalability
As software development projects grow in size and complexity, it can become difficult to scale automation efforts to meet the project's demands. To address this challenge, it's important to invest in scalable automation frameworks and tools that can handle larger and more complex projects.
Automation can introduce new security risks, particularly if sensitive data or systems are involved. To mitigate security concerns, development teams should establish clear security protocols and follow best practices for automation. This can include limiting access to sensitive data, implementing encryption and authentication measures, and conducting regular security audits.
Automation can be expensive to implement and maintain, particularly for smaller organizations with limited resources. To address cost concerns, we at ScienceSoft often start with an automation feasibility study. Also, it's good to explore open-source automation tools and frameworks, which may be more cost-effective than proprietary solutions, start small and gradually build up automation infrastructure.
Software Development Automation Services by ScienceSoft
We can help you discover potential areas for automation, calculate the necessary investments and potential ROI. We also build the automation strategy and roadmap, carefully select and customize the most effective automation tools for your specific needs, conduct training and workshops for your internal teams.
ScienceSoft offers comprehensive services around the most popular SDLC automation practices: low-code development (process setup, tool configuration, and training for your citizen developers), test automation, CI/CD implementation, and application maintenance automation.
Hire experienced talents to eliminate staff shortage or automation skill deficiency in your development team. We can provide from 1 to 100 employees, managed by our or your team leads or project managers. You will get CVs in 1–2 days; interviews will be arranged in 1–4 days.
Software Development Automation: Success Stories by ScienceSoft
Customer Portal Built with Power Apps for Saudia Cargo
ScienceSoft implemented a Dynamics 365 customer portal integrated with a sales module for Saudia Cargo, Asia’s leading cargo airline. ScienceSoft ensured a secure environment for all business-client communication, transactions and document flow, and gave the company’s clients faster and controllable way to apply for cargo transportation services.
CI/CD Implementation for a Smart Retail Digital Signage Solution
ScienceSoft implemented CI/CD pipelines compatible with multiple clouds to automate the development cycle of a content management system for a digital signage product of a North American startup. With CI/CD pipelines set up, ScienceSoft’s team ensured a seamless introduction of frequent code changes (up to 100 commits a day).
Automated Testing for vCIO Solution of a US Leading Training Services Provider
- Automated functional regression, integration and cross-browser testing.
- Integrating continuous testing into continuous integration (CI) pipeline to run tests automatically every time a new change was introduced.
- Optimizing long end-to-end UI tests.
Image Processing Software Continuous Integration
ScienceSoft’s team built a continuous integration pipeline to automatically run unit tests (570 tests to check units’ logic) and acceptance tests (470 user scenarios operating at a higher level than unit tests). Running tests in parallel helped reduce the test time from 4-5 to 1.5-2 hours.
Test Automation for Two Web Portals and a Mobile App
For more than two years, ScienceSoft has been creating and maintaining automated smoke and regression tests for a custom client portal, a Salesforce-based service portal, and iOS and Android versions of a mobile app.
Why Automate Software Development with ScienceSoft?
- 34 years of experience in building software.
- 10 years in DevOps consulting.
- 22 years in test automation.
- Both advisory and practical assistance.
- Quality-first approach based on a mature ISO 9001-certified quality management system.
- ISO 27001-certified security management based on comprehensive policies and processes, advanced security technology, and skilled professionals.
- A vast test automation toolkit, including Selenium, Apache JMeter, Ranorex, REST-assured, etc.
- Development of custom test automation frameworks.
- For the second straight year, ScienceSoft USA Corporation is listed among The Americas’ Fastest-Growing Companies by the Financial Times.
Sourcing Models for Software Development Automation
- Full control over the automation process setup and team productivity.
- Specific resources may be required, which are not efficient to hire for a one-time project.
- All hiring and managerial efforts are on your side.
- A vendor assumes full responsibility for the team assembly and management and the quality of deliverables.
- Established frameworks for test automation, CI/CD pipelines, application monitoring, etc.
- Tangible negative impact can arise from working with a vendor who can't fulfill its contractual obligations, deliver quality services, protect sensitive data.
In-house team + Outsourced consultancy
- An in-house team deeply knows internal processes and software systems, while an outsourced consultancy offers expert guidance, helps overcome challenges, and fills the gaps in technical skills.
- Risks of choosing an unreliable vendor.
- Establishing smooth collaboration between teams requires time and experience.
What Do Our Software Automation Specialists Do?
Software developer (trained in the target low-code platform)
- Training and mentoring citizen developers.
- Building low-code apps.
- Integrating the new apps with data sources and other enterprise apps.
CI/CD engineer / DevOps engineer
- Developing CI/CD pipelines.
- Reviewing and modifying CI/CD pipelines.
- Maintaining CI/CD tools and platforms (if applicable).
- Developing and maintaining CI/CD pipeline configurations.
Test automation architect
- Designing a test automation architecture.
- Selecting and configuring test automation tools and frameworks.
- Managing test automation engineers to improve the maintainability and granularity of automated tests and decrease test execution time.
Test automation engineer
- Setting up the test environment and test data generation.
- Developing, executing, and maintaining automated test scripts.
- Reviewing automatically generated defect reports.
- Collaborating with other cross-functional team members to improve the maintainability and granularity of test scripts.
Why Automate SDLC with ScienceSoft
Cost-Benefit Analysis of Software Development Automation
Below, we highlight the impact and cost components of the most popular SDLC automation practices.
|Benefits||Cost components and cost factors|
Cost components and cost factors
Cost components and cost factors
Cost components and cost factors
Cost components and cost factors
Key Automation Tools We Use at ScienceSoft
Microsoft Power Apps
- Among Leaders in Gartner’s Magic Quadrant for Enterprise Low-Code Application Platforms.
- Creation of low-code applications with pre-built templates or from a blank canvas.
- Extending existing apps with new functionality.
- 300+ connectors to integrate with the Office 365 universe, Azure SQL, Azure Cosmos DB, Amazon Redshift, and more.
- Rich AI capabilities – pre-built AI models can extract text from images, perform key phrase extraction and sentiment analysis.
- Introducing advanced app security and controls.
Power Apps licenses: $5 – one app per user/month and $20 – unlimited apps per user/month.
AI Builder: $500 per unit/month.
Cost of authenticated users of a portal built with Microsoft Power Apps:
- $200/per 100 logins.
- $1,000/per 1,000 logins.
- $3,500/per 5,000 logins.
Cost of anonymous external portal users: $100/per 100,000 portal page views.
Development and execution of automated web UI tests
- 4.5 rating on Gartner.com
- Supports Windows, Mac, Linux OSs.
- Supports Chrome, Firefox, Internet Explorer/Edge, Safari, Opera browsers.
- Supports C#, Java, PHP, Python, Ruby, Scala.
- Selenium web application tests can be re-used in mobile testing with Appium.
- Many helping forums and a huge community.
- 4.3 rating on G2.com
- Easy installation on different operating systems.
- Speedy release cycles.
- Intuitive user interface.
- Ecosystem of over 1,800 plugins (platforms, user interfaces, administration, source code and build management tools).
- Support of distributed builds to reduce loads on the CI server.
- A thriving community of contributors, which helps keep the tool up-to-date.
ScienceSoft is a US-headquartered IT services company with 34 years of experience in building software, 10 years in DevOps consulting and 22 years in test automation. We offer both advisory and practical assistance with software development automation to help businesses speed up high-quality releases. ScienceSoft is ISO 9001 and ISO 27001 certified, meaning we assure the quality of the delivered services and the security of the customers’ data.