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The results revealed that the choice of the Software Engineering course is related to the students’ affinity with the profession, but the financial compensation and the employability also influence on the course choice.
The results of the course show that this type of software engineering course gives students a more realistic experience than traditional software engineering courses.
Proceedings ArticleDOI
Stan Jarzabek, Pin-Kwang Eng 
18 Apr 2005
12 Citations
We trust this kind of the course is essential in curricula as it allows students better absorb knowledge learned in other software engineering courses.
This report is unique and valuable, especially for software engineering education, which goes beyond the discipline-specific limits of computer science curricula.
This paper suggests specific areas of business competencies that should be integrated into the software engineering curriculum.
I suspect that there is no one set of software engineering topics that should be included, but rather a range of topics to select from based on the purpose and perspective of the course.
The approach has been used in several software engineering courses and the results are positive and promising.
Proceedings ArticleDOI
01 Aug 1998
20 Citations
We submit that a key impediment to the development of new courses and curricula and the advancement of software engineering education is the lack of guidance and support for such development.

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How can the GFSI barriers can be overcome?
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To overcome Global Information Society (GFSI) barriers, various strategies can be implemented. Firstly, enhancing coordination, teamwork, and shared understanding in requirements engineering can help address challenges related to communication, time management, team mistrust, linguistic and cultural barriers. Secondly, utilizing communication and collaboration technologies effectively while addressing communication barriers can prevent project failures in global software development. Additionally, ensuring access to international knowledge bases, promoting electronic collaboration, and addressing issues like data meanings, legal accountability, and networking standards can facilitate the realization of a GFSI for health. Moreover, bridging the gap between different sensor platforms in global sensor networks can lead to more flexible and robust networks. Lastly, fostering cultural changes in higher education institutions to promote interprofessional education through e-learning can help overcome barriers to collaborative working and communication.
What is spontaneous architecture?
5 answers
Spontaneous architecture refers to architectural design and construction processes that evolve organically without strict premeditated planning. It often involves a collaborative and participatory approach, where buildings and urban structures grow in response to social, economic, and cultural contexts rather than being solely dictated by architects. Studies suggest that the mesoscale architecture of neuronal networks can influence the generation and richness of spontaneous activity, highlighting the importance of clustered connectivity in promoting diverse patterns of activity. In the realm of software systems, spontaneous interactions between software entities are facilitated by utilizing semantically linked information about their capabilities and features, rather than relying solely on predefined interfaces. Overall, spontaneous architecture embodies a dynamic and adaptive approach to design and construction, emphasizing responsiveness to evolving needs and contexts.
What is Rationale for the study meaning?
5 answers
The rationale for a study refers to the underlying reasons or justification for conducting the research, outlining its purpose and significance. In the context of software development, rationale extracted from chat messages is crucial for documenting decisions, considering alternatives, and facilitating software evolution and maintenance. This rationale, found in chat messages, provides valuable insights into the discussions, considerations, and argumentation that lead to development decisions, aiding in knowledge reuse and coping with changes in the software system. Despite the challenges posed by the volume and unstructured nature of chat messages, machine learning techniques show promise in extracting and identifying different elements of rationale from these messages, highlighting their importance in software development processes.
How do flow diagrams contribute to improved productivity in various industries, such as architecture and engineering?
4 answers
Flow diagrams play a crucial role in enhancing productivity across different industries like architecture and engineering. In software engineering, understanding flow through architecture is essential for removing impediments and fostering agility. Initially used for defining control, flow diagrams evolved into a versatile tool for planning automated computation at various levels of composition. In process improvement projects, clear frameworks utilizing flow diagrams like value-stream maps are vital for analyzing 'as-is,' 'could-be,' and 'should-be' scenarios, enhancing process modeling in manufacturing, service, and healthcare sectors. Moreover, data flow diagrams provide logical models of data flow, aiding in summarizing system information and organizing data entities, thereby contributing to improved productivity in system analysis and design.
What are the key indicators used to measure the success of cultural hacking initiatives?
5 answers
Key indicators used to measure the success of cultural hacking initiatives include the assessment of culturally-transmitted information retention in human minds, the reflection of organizational culture and values in software quality improvement initiatives, and the tangible experience of desired organizational culture in daily work environments through Culture Hacks. Additionally, the evaluation of interfaces between companies and consumers to simulate, dissimulate, and introduce new orientations plays a crucial role in measuring the impact of cultural hacking initiatives. Furthermore, the integration of the Cultural and Creative Cities Monitor (CCCM) framework at the local scale to assess the impacts of urban regeneration processes, particularly through community-based indicators, provides a comprehensive approach to evaluating the success of cultural and creative urban strategies.
What are the current trends and advancements in software development for AI applications?
5 answers
Current trends and advancements in software development for AI applications encompass various areas. AI tools in software engineering focus on systematic data evaluation in neural networks, structured analysis of big data for pattern discovery, and automation of routine tasks like debugging and documentation. Additionally, advancements in AI sensors offer cost-effective monitoring solutions for smart homes and healthcare, utilizing multidimensional sensors and brain-like computation devices. Moreover, the integration of AI with high-performance computing and specialized hardware drives innovations like autonomous vehicles and voice assistants, emphasizing the importance of transparency and explainability in AI systems. Overall, the current landscape showcases a synergy between AI algorithms, sensor technologies, and computing infrastructures, paving the way for enhanced productivity and efficiency in software development for AI applications.
What are the current trends and challenges in sustainable web development using WebAssembly?
5 answers
Current trends in sustainable web development using WebAssembly include the adoption of WebAssembly in non-web environments like IoT and Edge computing. This trend aligns with the shift towards web-based technologies in modern manufacturing, where Web-based Digital Twins (WDT) are utilized to enhance sustainability in industrial cyber-physical systems. Challenges in sustainable web development using WebAssembly involve addressing the performance gap with native code, which can be up to 45% slower due to issues like inefficient translation of instructions and overhead in system calls. Additionally, ensuring energy efficiency in software development is crucial for sustainability, with myths and beliefs hindering progress in controlling software energy consumption and making software greener. Overcoming these challenges requires exploring methods like leveraging WebAssembly for edge computing to achieve portability and migratability in edge-offloading platforms.
Why enterprise software should be innovated?
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Enterprise software should be innovated to enhance firms' innovative performance, increase labor productivity, and adapt to changing market circumstances. Research suggests that innovative products, such as ERP systems tailored to specific industries like agriculture, can facilitate management decisions and provide a dynamic framework for decision-making. Additionally, enterprise software systems, including ERP, SCM, and CRM, have been linked to fostering process and product innovations within firms. As markets evolve, companies must integrate design and innovation best practices into their software products to remain competitive and address the growing importance of user experience. By combining innovation management with software engineering practices, small companies can differentiate themselves through innovative approaches and build innovative products and services effectively.
How does AI-assisted software testing improve real-time monitoring during the testing process?
8 answers
AI-assisted software testing significantly enhances real-time monitoring during the testing process through various innovative approaches and methodologies. By leveraging AI, the testing process becomes more efficient, capable of handling complex data streams, and adaptive to changes in real-time, ensuring high-quality software performance and reliability. One of the primary ways AI improves real-time monitoring is through the automation of workflow and the acceleration of data analysis, as demonstrated in the context of x-ray ptychography, where AI/ML-accelerated analysis significantly speeds up the processing of large experimental datasets, enabling real-time experimental steering and low-latency monitoring. Similarly, in power grid systems, AI-assisted methods facilitate efficient data processing and event classification, improving system performance through timely data analysis. AI techniques also enable innovative monitoring of software systems by adapting to runtime changes and ensuring the software's adaptability in evolving environments. This is achieved through knowledge representations and inference rules that guide runtime adaptations, such as parameter tuning or re-assembly of processing chains. Moreover, AI's capability to anticipate bugs before irreversible changes are made enhances the reliability of software during production runs, addressing the challenge of non-deterministic concurrency bugs. In the realm of smart manufacturing, AI-driven methods monitor real-time production, detecting abnormalities efficiently to maintain product quality and reduce waste. Additionally, AI's role in software testing extends to diagnosing failed tests and suggesting further tests to identify correct diagnoses, thereby reducing the number of tests required to find the correct diagnosis. The integration of AI in software testing not only addresses the tedious and time-consuming nature of traditional testing processes but also fills the gap left by less effective automation tools in the era of continuous integration and delivery pipelines. This comprehensive approach to AI-assisted software testing, encompassing automation, real-time adaptation, and efficient bug detection and diagnosis, underscores the transformative impact of AI on enhancing real-time monitoring capabilities during the software testing process.
Is group composition important for student learning?
5 answers
Group composition plays a crucial role in student learning outcomes across various educational contexts. Research indicates that student team composition significantly impacts learning outcomes in software engineering education, writing composition development in English as a foreign language, virtual learning group dynamics and skill acquisitions, and collaborative learning in CSCL environments. Studies have shown that students benefit from working in groups with diverse learning styles, abilities, gender, and race, leading to improved performance and satisfaction in group learning situations. Furthermore, findings suggest that students in homogenous groups with similar levels of prior knowledge tend to score higher on assessments compared to those in heterogeneous groups. Therefore, designing effective group compositions is essential for enhancing student learning experiences and outcomes in various educational settings.
What process models are used in software implementation?
5 answers
Various process models are utilized in software implementation, ranging from traditional to agile methodologies. Traditional software engineering methodologies emphasize the use of business process models to support processes and documentation. On the other hand, agile methodologies like iterative and incremental models, waterfall model, and V-model are commonly employed in software development due to their flexibility and adaptability to change. These models play a crucial role in guiding the software development process through stages like requirement gathering, designing, development, testing, and implementation, ultimately determining the success or failure of the software development project. Researchers often compare and evaluate these models to select the most suitable one based on specific project needs, resources, and experience.