Introduction to the Research Scope
As with most research it’s best to begin by clearly defining the scope of the research problem i am addressing.
I do conduct open research as well but I like my research to yield discoveries or challenge truths.
In software engineering, this might include topics like algorithmic efficiency, software scalability, or AI-driven automation.
Sometimes I research beyond computing and interleave my research across other branches such as education, humanities like anthropology or business and management.
for example I could also touch on human-computer interaction or cybersecurity concerns in modern systems.
The scope is not restricted is my point and sometimes this approach highlights gaps where subjects have not been thoroughly linked
In such cases my research should pinpoint any gaps in existing knowledge or practice,
Or Bermuda triangles so to speak where few venture!
this blog can link to research I personally conduct & highlights such gaps.
I intend to Outline specific research questions that drive inquiry.
For a Master’s level project, these might be relatively narrow, focusing on solving a specific technical problem.
For instance:
• “How can machine learning algorithms be optimized for real-time data processing in edge computing environments?”
For a PhD-level thesis, the questions would often be more exploratory or conceptual:
Eg
•“What is the role of ethical AI in the development of autonomous systems, and how can biases be minimised through software engineering practices?”
Literature Review:
This section should highlight the existing body of work in my areas of interest.
I will engage with both foundational texts and recent studies.
For example:
• Discuss classic software engineering principles (like the SOLID principles) in the context of modern developments such as microservices or serverless architectures.
• Reference influential papers from key conferences such as ICSE (International Conference on Software Engineering) or NeurIPS (for AI-related research).
I might also incorporate systematic literature reviews or meta-analyses that address the effectiveness of particular software methodologies (e.g., Agile vs. DevOps in project management).
Research Methodology:
I break down how i plan to conduct research depending on the type of research that I opt for.
For a Master’s project, i may employ practical, experiment-based methodologies—e.g., comparing different algorithms in a controlled environment to measure performance.
I could discuss:
• Quantitative approaches, such as benchmarking software performance across different platforms.
• Qualitative approaches, like conducting developer surveys to understand common pain points in software development lifecycles.
For a PhD-level project, a methodology could involve more theoretical work, such as formal verification of software systems or the development of new mathematical models for improving software security.
I may also contribute new methodologies or frameworks to the field.
Case Studies and Application:
To demonstrate practical relevance, i can draw from industry case studies.
I have obviously what in the real world for many years so I already have a bunch of case studies
I would intend to some of those into my learning and development As part of my experiential learning
But it would be nice to do investigation around the discovery as I found when I was at work
But also it would be nice to explore the things that have emerged, which I don’t know But will find out.
research on distributed systems could reference real-world applications like cloud infrastructure at companies like Amazon or Microsoft.
For PhD-level work, i may also delve into more niche areas like blockchain technology and its application in secure transaction systems.
Some of this connects with my interests in finance, Some of you may know that I began my career Working at Reuters in 2007 and since worked at JP Morgan, HSBC bank, Ubs, Barclays, And more
I attended an event recently where they were speaking about the role of quantum computing for example
I know there are dedicated teams within financial services for those areas of work & research
Experiments and Prototypes:
A key component in software engineering research is the development and testing of prototypes.
For example:
• At the Master’s level, i might develop a machine learning model that improves software testing automation.
Kind of like when I had to do manual QA, And what I would’ve liked back in those days.
• At the PhD level, i could prototype a novel software architecture that enhances fault tolerance in large-scale distributed systems.
This is just an idea currently - I know that It’s important to provide links to GitHub repositories or other platforms where my prototypes can be seen!
Anyway that’s the jist….
Here’s more:
https://dev.to/gracerosen/an-area-of-research-33ie
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