Coding and simulation help
Code and simulations you can rerun and explain.
Yes, we help M.Tech and PhD scholars in engineering write, debug and understand their Python or MATLAB code, machine learning models and network simulations.
Many times the code is only one part of the trouble. One scholar sends us a Jupyter notebook which ran once on a friend’s laptop. Another has a MATLAB folder with files like final2_new_v3.m. Some have an NS2 Tcl script from a forum, which prints a trace file nobody can read. In base paper it is written 98% accuracy. Your code is giving only 71%. Review meeting is in three weeks. You need code you can run again in front of your guide and explain line by line.
We write or fix the code together with you, and we keep it clean with comments. For each result we keep a note of which version and which settings gave it. Then on a call we go through the logic with you. Suppose in viva the examiner asks about your learning rate or the routing metric you took, you should be able to tell the reason yourself.
Who this suits
Engineering scholars mostly come to us in one of these situations:
- You are trying to rebuild the algorithm of your base paper in Python or MATLAB, and your results are far below what the paper reports.
- Your machine learning model is giving a very high score, and your guide is asking if test data has leaked into the training.
- Your wireless sensor network or MANET work needs simulation runs in NS2 or NS3. The protocol idea is ready with you, but the scripts and graphs are not.
- The M.Tech Phase II demo is near. Some parts of the code work alone, but when you join them together it fails.
What you get
- Code that runs on your machine
Python scripts or notebooks, MATLAB files or simulation scripts, kept in folders with simple names. Wherever the logic is not clear by reading, we add comments. Before handover we test it on a setup close to yours.
- A record of the environment
For Python you get a requirements file with exact package versions. For MATLAB we write down the release and the toolboxes used. This way the code will still run next year on your college lab machine also.
- Results you can reproduce
Random seeds are fixed and the train and test split is written clearly. One script rebuilds every number and every graph of your results chapter, starting from the raw data.
- A fair comparison
We run your method and the baseline methods on the same data, with the same settings as the base paper. Then the comparison table in your thesis is honest. Suppose your method does not beat the baseline in every measure, the table will show that.
- Thesis-ready figures
Graphs in print resolution, with axis labels, units and legends, and the same style in all chapters. For simulations, plots like packet delivery ratio, delay or energy against number of nodes are made from your own trace files only.
- A README and a walkthrough call
A short README telling how to run each part of the code. And one recorded video call where we go through the code with you, till you are able to explain every step on your own.
How the work runs
Share the problem and the base paper
Send us your objectives, the base paper you are following, whatever code you have, and the dataset or the simulation settings given in the base paper. Also tell us the software versions in your lab.
Agree what “done” means
We write a short scope together. It says which algorithm, which dataset, which metrics, which baselines and which graphs. After we both agree on this list, we don’t keep adding new things in between.
Build, test and share as we go
Code comes to you in stages. We don’t keep everything for one big upload in the last week. At each stage you run it yourself and tell us when something breaks.
Walk through and hand over
First we do the walkthrough call on the code. After that you get the final folder with code, README, results and figures.
Ask about coding and simulation help
Only four fields to fill. We will call or WhatsApp you back by the next working day, and many times earlier than that. First talk with us is free, you don’t pay anything for it.
How long it takes
| Work | Typical time | Depends on |
|---|---|---|
| Fixing and documenting existing code | 4 to 7 working days | Size of the code and how badly it is broken |
| Implementing one algorithm from a base paper | 1 to 3 weeks | If the paper gives enough detail to rebuild the method |
| A machine learning pipeline with baselines and tuning | 2 to 4 weeks | Size of the dataset and the computing power you have |
| An NS2 or NS3 simulation with graphs for 3 to 5 metrics | 2 to 3 weeks | Changes in the protocol and how many scenarios |
| Walkthrough and changes after your review meeting | 3 to 5 working days | Whatever corrections your guide asks |
One training run of a deep learning model can take hours. A free cloud notebook may also disconnect a long session in the middle. So if you have a big dataset and you know there will be many runs, tell us in the beginning itself. We will keep extra days for computing in the plan.
What it costs
Coding work changes more than any other work we do. Some bug fixes are over in one day. Building a new simulation framework from zero may go for some weeks. That is why we first read your base paper and your code. After that we send a written quote with the scope, the stages and the dates. Payment is also in stages, and at the end of each stage you have code which you can run.
The quote depends on
- How much code is already there, and what condition it is in
- Language and tools, like Python, MATLAB, NS2, NS3 or something else
- If the method is from a clear base paper or is a new one
- Size of the dataset and how much computing time it takes
- Number of baselines, metrics and graphs needed
Who you’d be working with
Thesis Writing Service is run by Saaira Technologies from Nagercoil, Tamil Nadu. We work with scholars by phone, WhatsApp, email and video, so you never need to travel. The figures are the company’s own.
- years of research support
- 10+
- scholars helped
- 1,500+
- subject areas
- 12+
- countries
- 25+
Questions scholars ask
Should I use NS2 or NS3 for my simulation?
For a new thesis we mostly suggest NS3. It is the newer simulator, first released in 2008, written in C++ and having Python bindings. NS2 still works, and lot of older papers have used it. Only thing is, in some reviews the committee members are asking why NS2 for a new work. If your base paper used NS2 and you need a direct comparison with it, then staying with NS2 is a fair reason.
My laptop has no GPU. Can I still do deep learning?
In many cases, yes. Small models will train on a CPU, only it is slow. When the model is bigger you will want a GPU, and a cloud notebook like Google Colab gives some GPU time free, but there are limits on it. Your college may also have a server in the lab. We plan the experiments based on what you can really run.
Python or MATLAB?
Go with what your lab and your guide are using. When your guide wants to check the code, it is easier if it is in a language he or she knows. MATLAB is common in signal processing, control and image processing departments. For machine learning, most people use Python. For a thesis both are acceptable. The main thing is you can run the code yourself and explain it during your review.
My model gets 99.8% accuracy. Is that a problem?
It can be. Very high accuracy many times means data leakage. We have seen cases where the same records were sitting in training set and test set both. In one project a single feature was giving away the answer. Another common one is scaling done before the split. Also if your classes are unbalanced, accuracy number by itself is misleading. Put precision, recall and F1 in the table with it. We check all this first.
Can you rebuild the algorithm in my base paper?
In most cases we can, provided the paper gives the details. Many papers skip the settings which matter, such as learning rate, number of epochs or simulation time. We make a list of what is missing, choose sensible values along with you and write them down. Your thesis can then say exactly how you rebuilt the base paper.
Do I get the full source code?
Yes, you get every file. That includes the README, the environment record and the figure scripts. It is your thesis code.
I need the code and the report. Can you help with both?
Yes. For an M.Tech or MCA project, our dissertation help takes care of the report. For a doctorate, our PhD thesis help covers the chapters. When code and write-up are planned together, the results chapter matches what the code is actually doing.
Stuck on a chapter? Talk it through with us.
Call or WhatsApp, say where you are in your thesis, and we’ll tell you plainly what kind of help makes sense, if any.