Software System Engineering Project
A Software System Engineering Project is a technology project that is an engineering project (to create or enhance software systems through engineering processes).
- AKA: Structured Software Engineering Endeavor, Formal Software Engineering Initiative, Software Engineering Project, Software Project, Engineering Software Project, Software System Project, Software Development Engineering Project.
- Context:
- It can typically enforce Engineering Standards through formal processes.
- It can typically apply Engineering Principles through systematic approaches.
- It can typically require Engineering Documentation through technical specifications.
- It can (typically) be delivered by a Software Development Project Team.
- It can (typically) involve stages such as requirements analysis, system design, software development, testing, and maintenance.
- It can (typically) establish Software Architecture Patterns through design decisions.
- It can (typically) implement Software Quality Metrics through measurement frameworks.
- It can (typically) manage Technical Debt through refactoring strategies.
- It can (typically) ensure Software Security through security engineering practices.
- It can (typically) maintain Software Traceability through requirement tracking.
- It can (typically) be executed by a Software Engineering Organization or Software Development Organization.
- It can (typically) produce Source Code Commit Records through version control systems.
- It can (typically) utilize 3rd-Party Software Development Frameworks for development efficiency.
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- It can (often) require project management skills and methodologies, such as Agile or Waterfall, to ensure successful completion.
- It can (often) involve Project Stakeholders, such as: software developers, project managers, end-users, and software clients.
- It can (often) utilize tools and technologies like version control systems, integrated development environments (IDEs), and software testing tools.
- It can (often) implement Continuous Integration/Continuous Deployment through automation pipelines.
- It can (often) adopt DevOps Practices through collaborative processes.
- It can (often) utilize Cloud Computing Resources through infrastructure as code.
- It can (often) enforce Code Review Processes through peer reviews.
- It can (often) establish Performance Benchmarks through load testing.
- It can (often) create API Documentation through automated tools.
- It can (often) implement Monitoring Solutions through observability platforms.
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- It can range from being a Small Software Engineering Project to being a Large Software Engineering Project.
- It can range from being a Simple Software Engineering Project to being a Complex Software Engineering Project, depending on its engineering scope.
- It can range from being a Basic Engineering Implementation to being a Critical System Engineering Project, depending on its engineering rigor.
- It can range from being a Single Domain Engineering Project to being a Multi Domain Engineering Project, depending on its engineering scope.
- It can range from being a Research Software Engineering Project to being a Production Software Engineering Project, depending on its project purpose.
- It can range from being a Component Software Engineering Project to being a System Software Engineering Project, depending on its system scale.
- It can range from being a Waterfall Software Engineering Project to being an Agile Software Engineering Project, depending on its development methodology.
- It can range from being a On-Premise Software Engineering Project to being a Cloud-Native Software Engineering Project, depending on its deployment model.
- It can range from being a Monolithic Software Engineering Project to being a Microservices Software Engineering Project, depending on its architecture style.
- It can range from being a Traditional Software Engineering Project to being an AI-Enhanced Software Engineering Project, depending on its technology adoption.
- It can range from being a Single-Team Software Engineering Project to being a Distributed-Team Software Engineering Project, depending on its team structure.
- It can range from being a Fixed-Scope Software Engineering Project to being an Evolving-Scope Software Engineering Project, depending on its requirement stability.
- It can range from being an Individual Software Engineering Project to being an Organizational Software Engineering Delivery Project, depending on its delivery scope.
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- It can include Software Development Projects for software implementation.
- It can manage Software Architecture Projects for system design.
- It can oversee Software Testing Projects for quality assurance.
- It can coordinate Software Integration Projects for system integration.
- It can direct Software Deployment Projects for system deployment.
- It can supervise Software Maintenance Projects for system maintenance.
- It can govern Software Security Projects for vulnerability management.
- It can orchestrate Software Migration Projects for platform transitions.
- It can facilitate Software Optimization Projects for performance improvements.
- It can administer Software Compliance Projects for regulatory adherence.
- It can encompass Machine Learning (ML)-based Development Projects for AI capability integration.
- It can spawn AI System Engineering Projects for AI system development.
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- Example(s):
- Software Implementation Engineering Projects (for software system implementations), such as:
- Software Development Projects (for software developments), such as:
- Software Architecture Projects (for software architectures), such as:
- Software Testing Projects (for software testings), such as:
- Software Integration Projects (for software integrations), such as:
- Software Deployment Projects (for software deployments), such as:
- Software Maintenance Projects (for software maintenances), such as:
- Mission Critical Software Engineering Projects (for mission critical systems), such as:
- Medical Software Engineering Projects (for medical systems), such as:
- Patient Monitoring Software Engineering Project for life support systems.
- Medical Diagnostic Software Engineering Project for clinical analysis systems.
- Electronic Health Record Software Engineering Project for healthcare data systems.
- Surgical Robot Software Engineering Project for robotic surgery systems.
- Transportation Software Engineering Projects (for transportation systems), such as:
- Financial Software Engineering Projects (for financial systems), such as:
- Medical Software Engineering Projects (for medical systems), such as:
- Industrial Software Engineering Projects (for industrial systems), such as:
- Manufacturing Software Engineering Projects (for manufacturing systems), such as:
- Production Control Software Engineering Project for factory automation systems.
- Assembly Line Software Engineering Project for manufacturing systems.
- Supply Chain Software Engineering Project for logistics systems.
- Predictive Maintenance Software Engineering Project for equipment monitoring systems.
- Quality Software Engineering Projects (for quality systems), such as:
- Manufacturing Software Engineering Projects (for manufacturing systems), such as:
- Research Software Engineering Projects (for research systems), such as:
- Laboratory Software Engineering Projects (for laboratory systems), such as:
- Instrument Control Software Engineering Project for experiment automation systems.
- Data Acquisition Software Engineering Project for scientific measurement systems.
- Laboratory Information Management Software Engineering Project for research data systems.
- Bioinformatics Software Engineering Project for genomic analysis systems.
- Simulation Software Engineering Projects (for simulation systems), such as:
- Physics Simulation Software Engineering Project for scientific modeling systems.
- Chemical Process Software Engineering Project for reaction analysis systems.
- Climate Modeling Software Engineering Project for weather prediction systems.
- Molecular Dynamics Software Engineering Project for protein folding systems.
- Laboratory Software Engineering Projects (for laboratory systems), such as:
- Enterprise Software Engineering Projects (for enterprise systems), such as:
- Infrastructure Software Engineering Projects (for infrastructure systems), such as:
- High Availability Software Engineering Project for system reliability systems.
- Load Distribution Software Engineering Project for system performance systems.
- Disaster Recovery Software Engineering Project for business continuity systems.
- Multi-Cloud Software Engineering Project for hybrid cloud systems.
- Integration Software Engineering Projects (for integration systems), such as:
- System Framework Software Engineering Project for enterprise integration systems.
- Data Platform Software Engineering Project for system interoperability systems.
- Service Mesh Software Engineering Project for microservice communication systems.
- Event Streaming Software Engineering Project for real-time data systems.
- Infrastructure Software Engineering Projects (for infrastructure systems), such as:
- AI Software Engineering Projects (for AI software systems), such as:
- Machine Learning Software Engineering Projects (including Machine Learning (ML)-based Development Projects) for machine learning systems.
- AI Agent-based Software Engineering Project for AI agent-based systems.
- Natural Language Processing Software Engineering Project for text analysis systems.
- Computer Vision Software Engineering Project for image processing systems.
- Deep Learning Platform Software Engineering Project for neural network systems.
- MLOps Software Engineering Project for ML lifecycle management systems.
- Open Source Software Engineering Projects (for open source systems), such as:
- Apache Projects (for apache systems), such as:
- Linux Software Engineering Projects (for linux systems), such as:
- Deep Learning Framework Projects, such as:
- Python Library Projects, such as:
- Hyperopt Library development for hyperparameter optimization.
- NumPy Project for numerical computing.
- Enterprise Software Engineering Projects (for enterprise systems), such as:
- ERP Software Engineering Projects (for ERP systems), such as:
- Resource Planning Software Engineering Project for business operations systems.
- Enterprise Integration Software Engineering Project for system coordination systems.
- Financial Management Software Engineering Project for accounting systems.
- Human Capital Management Software Engineering Project for HR systems.
- Organizational Software Engineering Delivery Projects, such as:
- ERP Software Engineering Projects (for ERP systems), such as:
- Integration Software Engineering Projects (for integration systems), such as:
- Protocol Software Engineering Projects (for protocol systems), such as:
- MCP Server Software Engineering Projects (for MCP server systems), such as:
- Domain MCP Software Engineering Project for llm integration systems.
- Custom MCP Software Engineering Project for enterprise integration systems.
- Open Source MCP Software Engineering Project for community integration systems.
- Commercial MCP Software Engineering Project for vendor integration systems.
- API Gateway Software Engineering Projects (for API gateway systems), such as:
- REST Gateway Software Engineering Project for service integration systems.
- GraphQL Gateway Software Engineering Project for data integration systems.
- WebSocket Gateway Software Engineering Project for real-time communication systems.
- gRPC Gateway Software Engineering Project for high-performance RPC systems.
- MCP Server Software Engineering Projects (for MCP server systems), such as:
- Protocol Software Engineering Projects (for protocol systems), such as:
- Platform Software Engineering Projects (for platform systems), such as:
- LLM Software Engineering Projects (for LLM systems), such as:
- Container Platform Software Engineering Projects (for container systems), such as:
- Framework Software Engineering Projects (for framework systems), such as:
- Protocol Framework Software Engineering Projects (for protocol framework systems), such as:
- MCP Framework Software Engineering Project for llm protocol systems.
- Integration Framework Software Engineering Project for system protocol systems.
- Communication Framework Software Engineering Project for messaging protocol systems.
- Security Framework Software Engineering Project for authentication protocol systems.
- Application Framework Software Engineering Projects (for application framework systems), such as:
- Protocol Framework Software Engineering Projects (for protocol framework systems), such as:
- Blockchain Software Engineering Projects (for blockchain systems), such as:
- Game Software Engineering Projects (for gaming systems), such as:
- Custom Development Projects, such as:
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- Software Implementation Engineering Projects (for software system implementations), such as:
- Counter-Example(s):
- A Rapid Software Development Project, which prioritizes speed over engineering rigor.
- A Prototype Software Project, which focuses on quick validation rather than engineering standards.
- A Construction Project, which involves physical infrastructure.
- A Construction Project involving physical infrastructure.
- A Marketing Campaign focused on advertising and promotion.
- A Hardware Engineering Project, which develops physical components rather than software systems.
- A Business Process Project, which redesigns workflows without software development.
- A Training Project, which develops skills rather than software systems.
- A Software Procurement Project, which acquires existing software rather than engineering solutions.
- See: Project, Project Management Triangle, Software Development Life Cycle, Engineering Project, Software Engineering, System Engineering, Software Architecture, DevOps, Agile Methodology, Software Quality Engineering, Technical Debt Management, Software Security Engineering, Software Development Project, AI System Engineering Project, Software Engineering Organization, Software Development Organization, 3rd-Party Software Development Framework, Source Code Commit Record, Machine Learning (ML)-based Development Project, Organizational Software Engineering Delivery Project, Software-based Computing System.
References
2020
- (Akgün, 2020) ⇒ Ali E. Akgün. (2020). “Team Wisdom in Software Development Projects and Its Impact on Project Performance.” International Journal of Information Management, 50.
- ABSTRACT: While the concept of wisdom, which refers to how people make right use of their knowledge through their practical actions, judgments, and ethical decisions, in general attracts researcher interest in a variety of disciplines, such as philosophy, psychology and management studies, little is known about how wisdom is conceptualized and then operationalized in the software development project team context. Based on the frameworks for philosophical, group and organizational wisdom, this paper identifies software development project team wisdom as a process for how team members best use the stock and flow of their knowledge through collective judgment, virtue-ethics, emotions/feelings, and effective decision-making during their project-related efforts. Adapting the efforts and functional similarities of both group and organizational wisdom practices, this effort determines that wisdom-related mechanisms (e.g., team diversity, networking with other teams and people, and their past experiences), joint epistemic actions (e.g., team reasoning, intuition, and aesthetic capacity), and team virtue and prudence become the different faces of the software development team wisdom process. We then propose how these different faces interrelate and how they also relate to project process effectiveness, such as team learning and speed-to-users, both of which have been rarely addressed empirically in the context of software development project teamwork.
By examining 210 in-house software development project teams in a field study and using structural equation modeling analysis, our results empirically show the following: (a) software development wisdom-related mechanisms positively relate to software development team prudence and virtue and their joint epistemic actions, (b) software development team prudence and virtue are positively associated with software development team joint epistemic actions, and further (d) software development team joint epistemic actions are positively associated with software development project process effectiveness. We conclude by discussing our findings as they relate to the wisdom framework of software development project teams and suggest the key managerial implications for different types of software development projects.
- ABSTRACT: While the concept of wisdom, which refers to how people make right use of their knowledge through their practical actions, judgments, and ethical decisions, in general attracts researcher interest in a variety of disciplines, such as philosophy, psychology and management studies, little is known about how wisdom is conceptualized and then operationalized in the software development project team context. Based on the frameworks for philosophical, group and organizational wisdom, this paper identifies software development project team wisdom as a process for how team members best use the stock and flow of their knowledge through collective judgment, virtue-ethics, emotions/feelings, and effective decision-making during their project-related efforts. Adapting the efforts and functional similarities of both group and organizational wisdom practices, this effort determines that wisdom-related mechanisms (e.g., team diversity, networking with other teams and people, and their past experiences), joint epistemic actions (e.g., team reasoning, intuition, and aesthetic capacity), and team virtue and prudence become the different faces of the software development team wisdom process. We then propose how these different faces interrelate and how they also relate to project process effectiveness, such as team learning and speed-to-users, both of which have been rarely addressed empirically in the context of software development project teamwork.
2016
- (Abdelrafe et al., 2016) ⇒ Elzamly Abdelrafe, Burairah Hussin, and Norhaziah Salleh. (2016). “Top Fifty Software Risk Factors and the Best Thirty Risk Management Techniques in Software Development Lifecycle for Successful Software Projects.” International Journal of Hybrid Information Technology 9, no. 6
- QUOTE: … the values, principles and practices for modelling software in SDLC as well as used to identify and maintain a clear and correct understanding of the software development project being built [19], [20]. Furthermore, it don‟t contain any risk management techniques because it is …
1987
- (Bullard et al., 1988) ⇒ Catherine L. Bullard, Inez Caldwell, James Harrell, Cis Hinkle, and A. Jefferson Offutt. (1988). “Anatomy of a Software Engineering Project.” In: Proceedings of the nineteenth SIGCSE technical symposium on Computer science education, pp. 129-133.
- ABSTRACT: This paper discusses a complete software development project carried out in a one quarter undergraduate software engineering course. The project was the design and implementation of a complete system by 25 students. They worked in smaller groups on four functionally separate subsystems that were successfully integrated into a complete system. This was accomplished by using five advanced students to manage the groups, real users to criticize each step of the process, and UNIX tools to implement the subsystems. This paper describes the project, presents the methodologies used, and discusses both the positive and negative aspects of this course. It concludes by presenting a set of recommendations based on our experience with this project.