mirror of
https://github.com/azaion/gps-denied-desktop.git
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update metodology, add claude solution draft
This commit is contained in:
Oleksandr Bezdieniezhnykh
@@ -12,9 +12,10 @@
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- orthophoto images from the UAV for the analysis
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- list of expected GPS for the centers for each picture in csv format: picture name, lat, lon
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- video from the UAV for the analysis
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- list of expected GPS for the centers of video per timeframe in csv format: timestamp, lat, lon for each 1-2 seconds of the
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- list of expected GPS for the centers of video per timeframe in csv format: timestamp, lat, lon for each 1-2 seconds
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- ...
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Analyze very thoroughly input data and form system's restrictions for input data and acceptance ctiteria
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Analyze very thoroughly input data and form system's restrictions and acceptance ctiteria
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- `restrictions.md`: Restrictions we have in real world in the -dashed list format. For example:
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- We're limiting our solution to airplane type UAVs.
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@@ -31,89 +32,68 @@
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## 1.2 **✨AI Research**: Restrictions and Acceptance Criteria assesment
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Form the next prompt:
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- Replace *.md to the corresponding content
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In the new context form the next prompt:
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- Add *.md to the context
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- Add sample files to the prompt
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- Put proper sample filenames in the text of the prompt
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and run it in DeepResearch tool (Gemini, ChatGPT, or other)
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**📝prompt template:**
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We have this problem:
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`docs/00_problem/problem_description.md`
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System should process this data samples:
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`sample1.jpg`, `sample2.jpg`, `coordinates.csv`, ...
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We have next restrictions for the input data:
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`docs/00_problem/restrictions.md`
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Output of our system should meet these acceptance criteria:
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`docs/00_problem/acceptance_criteria.md`
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and run it in DeepResearch tool (Gemini, DeepSeek, or other)
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```
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We have the problem described in `problem_description.md`.
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- System should process data samples in the attached files (if any). They are for reference only.
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- Restrictions for the input data are stated in `restrictions.md`.
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- Acceptance criteria for the output of the system are stated in `acceptance_criteria.md`.
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Check how realistic these acceptance criteria are.
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Check how critical is each criterion. Also find out more acceptance criteria for this specific domain.
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Research impact of each value in acceptance criteria to the whole system quality.
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Assess acceptable ranges for each value in each acceptance criteria in the state of the art solutions, and propose corrections in the next table:
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Check how critical each criterion is. Find out more acceptance criteria for this specific domain.
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Research the impact of each value in the acceptance criteria on the whole system quality.
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Assess acceptable ranges for each value in each acceptance criterion in the state-of-the-art solutions, and propose corrections in the next table:
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- Acceptance criterion name
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- Our values
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- Your researched criterion values
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- Status: Is criterion was added by your research to our system, or modified, or removed, cause not necessary
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Also asses restrictions we've put for the system. Are they realistic? Propose corrections in the next table:
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- Status: Is the criterion added by your research to our system, modified, or removed
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Assess the restrictions we've put on the system. Are they realistic? Propose corrections in the next table:
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- Restriction name
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- Our values
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- Your researched restriction values
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- Status: Is restriction was added by your research to our system, or modified, or removed, cause not necessary
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- Status: Is a restriction added by your research to our system, modified, or removed
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```
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**👨💻Developers**: Revise the result, discuss them and overwrite `docs/00_problem/acceptance_criteria.md`
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## 1.3 **✨AI Research**: Research the problem in great detail
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Form the next prompt:
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- Replace *.md to the corresponding content
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In the new context form the next prompt:
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- Add *.md to the context
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- Add sample files to the prompt
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- Put proper sample filenames in the text of the prompt
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and run it in DeepResearch tool (Gemini, ChatGPT, or other)
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**📝prompt template:**
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Research this problem:
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`docs/00_problem/problem_description.md`
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System should process this data samples. They are for references only:
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`sample1.jpg`, `sample2.jpg`, `coordinates.csv`
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We have next restrictions for the input data:
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`docs/00_problem/restrictions.md`
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Output of our system should meet these acceptance criteria:
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`docs/00_problem/acceptance_criteria.md`
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Find out all the state of the art solutions for this problem and produce the resulting solution draft in the next format:
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- Product solution description
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- Architecture approach that meet restrictions and acceptance criteria
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- Testing strategy. Research the best approaches to cover all the acceptance criteria, functional and non-functional tests
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and run it in DeepResearch tool (Gemini, DeepSeek, or other)
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```
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Research this problem in `problem_description.md`.
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- The system should process data samples in attached files (if any). They are for reference only.
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- We have the next restrictions for the input data in `restrictions.md`.
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- Output of our system should meet these acceptance criteria in `acceptance_criteria.md`.
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- Find out all the state-of-the-art solutions for this problem and produce the resulting solution draft in the next format:
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- Short Product solution description. Brief component interaction diagram.
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- Architecture approach that meets restrictions and acceptance criteria. Tables to compare possible component decisions.
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- Testing strategy. Research the best approaches to cover all the acceptance criteria, functional, and non-functional tests
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Be concise in formulating, The less words the better, but do not miss any important details.
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```
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**👨💻Developer**: Revise the result from AI. Research the problem as well, and add/modify/remove some solution details in the draft.
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Store it to the `docs/01_solution/solution_draft_01.md`
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## 1.4 **✨AI Research**: Solution draft assessment
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Form the next prompt by replacing *.md with corresponding content and run it in DeepResearch tool (Gemini, ChatGPT, or other)
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**📝prompt template:**
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In the solution here:
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`docs/01_solution/solution_draft_xx.md`
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find out all the possible weak points and problems. Address them and find out ways to solve them. Based on your findings, form new solution draft in the same format.
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Add *.md to the context and run it in DeepResearch tool (Gemini, DeepSeek, or other)
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```
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We have a problem here in `problem_description.md` with restrictions `restrictions.md`. We've presented the solution here in `solution_draft_xx.md`.
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Identify all potential weak points and problems. Address them and find out ways to solve them. Based on your findings, form a new solution draft in the same format without mentioning or comparison with first solution draft. Also, in case of replacing some components with better one, do not just throw away the previous, form a table with comparison for the component.
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```
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**👨💻Developer**: Research by yourself as well - how to solve additional problems which AI figured out, and add them to the result. Store the result draft to the `docs/01_solution/solution_draft_xx+1.md`, and repeat the process. When the next solution wouldn't differ much from the previous one, store the last draft as `docs/01_solution/solution.md`
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## 1.5 **🤖📋AI plan**: Solution Decomposition
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**📝prompt:**
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```
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Decompose the solution `@docs/01_solution/solution.md` to the components.
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Store description of each component to the file `docs/02_components/[##]_[component_name]/spec.md` with the next structure:
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- Component Name
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@@ -141,14 +121,16 @@
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- StepN - Expected resultN
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Do not put any code yet. Ask as many questions as needed.
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```
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**👨💻Developer**: Answer the questions AI asked, put as many details as possible
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## 1.6 **🤖📋AI plan**: Business Requirement generation
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```
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From the initial requirements above generate Jira epics:
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- Ask the Jira project key and latest created jira task number. For example AZ-412
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- Access the solution `@docs/01_solution/solution.md` and description of each component in the files `docs/02_components/[##]_[component_name]/spec.md`
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- Generate Jira Epics from the Components
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- Ensure each epic has clear goal and acceptance criteria, verify the criteria with `@docs/00_initial/acceptance_criteria.md`
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- Generate draw.io components diagram based on previous diagram shows relations between components and Jira Epic numbers corresponding to each component.
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```
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@@ -2,7 +2,7 @@
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## 2.1 **🤖📋AI plan**: Component Decomposition
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For each component in `docs/02_components` do next:
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**📝prompt:**
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```
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Decompose `@docs/02_components/[##]_[component_name]/spec.md` to the features. If component is simple enough, make only 1 feature, if complex - separate per features. Feature can contain 0 or more APIs. Create `docs/02_components/[##]_[component_name]/[##]_[feature_name]_feature.md` with the next structure:
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- Name
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- Description
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@@ -14,12 +14,12 @@
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Do NOT generate any code yet, only brief explanations what should be done.
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Ask as many questions as needed.
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```
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**👨💻Developer**: Answer the questions AI asked, put as many details as possible
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## 2.2 **🤖AI agent**: Feature implementation
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For each component in `docs/02_components/[##]_[component_name]/` folder do next:
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**📝prompt:**
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```
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Read component description `@docs/02_components/[##]_[component_name]/spec.md`.
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Read all features in the folder `@docs/02_components/[##]_[component_name]`. For each feature do next:
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- Implement it
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@@ -27,9 +27,10 @@
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- Create unit tests from the Test cases description, run it and make sure the result is a success
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- Create integration test for the feature, run and make sure the result is a success
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If integration tests are specified in component spec, then write them and run, and make sure that component working correctly
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```
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## 2.3 **🤖AI agent**: Solution composition and integration tests
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**📝prompt:**
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```
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Read all the files here `docs/03_tests/` and for each file write down tests and run it.
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Compose a final test results in a csv with the next format:
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- Test filename
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@@ -38,4 +39,5 @@
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Fix all problems if tests failed until we got a successful result.
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In case if one or more tests was failed due to missing data from user or API or other system, ask it from developer.
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Repeat test cycle until no failed tests.
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Repeat test cycle until no failed tests.
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```
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