This year, Oppia will be participating in Google Summer of Code 2023! GSoC is a global program which offers students and non-experienced contributors the opportunity to discover and work with open-source organizations. The contributions are supported by a stipend. Contributors work closely with one or more mentors from an open-source organization to implement either a project idea by the organization, or a proposal of their own. You might be interested in our GSoC info pages from previous years: 2022, 2021, 2020, 2019, 2018, 2017, 2016.

In order to receive updates about GSoC at Oppia, please subscribe to the Oppia GSoC Announce mailing list.

Oppia will be giving an automatic extension to all the projects i.e, all the projects will have 8 weeks for each milestone, with an internal evaluation after 6 weeks. The coding period dates are strict and intended to balance offering flexibility to contributors with the need on the org admin side to have a streamlined process and a more time-bounded GSoC period. Contributors may opt for a shorter timeline if desired. Therefore, there will not be any additional extensions. Please refer to the Dates and Deadlines section below.

Also, please note that acceptance into GSoC isn't a prerequisite for becoming an Oppia contributor. The Oppia project is run by the community for the community, and we warmly welcome anyone who'd like to help out! You can get started by following the instructions here.

Contributors

GSoC is an excellent opportunity for new contributors to get paid to work on an open source project. If you're interested in applying as a contributor, you should definitely read the following resources:

Google Summer of Code contributor guide
Google's list of resources
GSoC FAQ

Current Projects

The following projects (with linked proposals where available) are currently in progress for GSoC 2023:

Kshitij Patil: Contributor Dashboard Admin Stats Table
Patel Muhammed: Accessibility improvements
Rishi Kejriwal: Serial chapter launch
Shivkant Chauhan: Dockerize Oppia
Ashwath Kannan: Improvements for translation reviewer experience

Getting started

Welcome! If you're interested in applying to work with Oppia for GSoC, please follow these steps:

Sign up to the oppia-gsoc-announce@ mailing list in order to receive important notifications about Oppia's participation in GSoC. If you like, you can also turn on notifications for Github Discussions to participate in general discussion related to Oppia's involvement in GSoC. Make sure to set your preferences correctly so that you actually get the emails!
Get a better understanding of what Oppia is about:
- Read the user documentation to become familiar with important concepts like explorations and interactions.
- Play some lessons on Oppia.org, which hosts a live instance of Oppia.
To get started with development, read and follow the instructions in the contributors' guide carefully (Oppia Web). You might also find this [[page of learning resources|Learning-Resources]] helpful for learning the technologies needed to contribute to Oppia.
- Note! Oppia Android won't be offering GSoC projects in 2023, but will be doing so again from 2024 onwards.
Do one or more starter projects to become familiar with the contribution process. This will help us get an idea of what it's like to work with you. It will also help you get a better understanding of the codebase and our development process, which may help with writing a good project proposal. Once you've merged at least 2 pull requests, you will get an invitation to become a collaborator to the Oppia repository and be officially onboarded! This step is a prerequisite to applying for GSoC.
- Note! You must be onboarded to the repository to which you will contribute during GSoC. For example, to work on an Oppia Web GSoC project, you need to be onboarded to the oppia/oppia repository, which means that your 2 pull requests need to be to oppia/oppia.
- Pro-tip! Quality is more important than quantity; we want to see examples of your best work. So, please make sure to read the [["getting started" guide|Contributing-code-to-Oppia]] and [[PR instructions|Rules-for-making-PRs]] carefully, follow the tips for success, manually test your code before submitting (to ensure it does what you want it to and doesn't break anything else), ensure that your code conforms to the style rules, and pay attention to small details. These are good skills to learn when developing software in general, and they will also help you build credibility as a responsible developer who can be trusted to be a good steward of the Oppia codebase.
Select one or more GSoC project ideas that you're most interested in, and write your project proposal! We strongly encourage you to discuss your project ideas and share your proposal with the community, so that you can get feedback and ensure that what you're writing makes sense to others. Please follow the instructions in the GSoC proposal template section to do this.

If you have any questions about a project, or would like to discuss your approach with the Oppia community and get feedback, you can also email the oppia-gsoc-discuss@ mailing list. Please be specific when asking questions, since this makes it easier for us to help you.
- Pro-tip! 75% of the accepted proposals had begun their work at least 4 weeks prior to the deadline. Hence, we strongly recommend that the contributors start writing proposals as early as possible.
Good luck!

FAQs

Q: Is Oppia Android a part of this year's GSoC?

A: Oppia Android won't be able to participate in GSoC this year. Note that this is a one-off, and Oppia Android hopes to be back in 2024 when we have better processes and documentation to help contributors get onboarded more smoothly.

Q: What technical skills do I need to work on Oppia?

A: For Oppia Web, Angular 2+, Python 3.9 and Google App Engine are useful and recommended for most Oppia work; in addition, UI design skills are useful for frontend, user-facing work. Please see the individual project ideas to determine whether these skills are recommended for the project in question. Note that, although GSoC is aimed at beginner contributors to open source and at students, "beginner to open source" is not the same as "beginner to coding" -- the projects assume some proficiency with coding. This [[page of learning resources|Learning-Resources]] might be helpful for learning the technologies needed to contribute to Oppia.

Q: How can I increase my chances of getting selected?

A: Writing a good project proposal, engaging with the community, helping other contributors, successfully contributing, and demonstrating that you can work independently can all help you. We've also compiled some notes below on the selection criteria we'll be using this year.

Q: Can you be flexible around my other commitments in the summer?

A: No, Oppia will strictly adhere to GSoC timeline and will usually not be able to provide any additional extensions. Please refer to the Dates and Deadlines section below.

Q: Which projects are most important for Oppia?

A: All the projects we've listed in the Ideas List are important, and we'd be very happy to see good progress made on any of them! Projects are treated as equally important during selection; note that the relative importance of a project to Oppia is not part of the selection criteria. We strongly encourage you to pick a project that you'd enjoy doing over the summer!

Q: Can I submit more than one proposal to Oppia?

A: Yes, you can. However, we strongly recommend picking one project and writing a solid proposal for it. Splitting attention across multiple projects might not be a great idea. (That said, GSoC is offering full-length and half-length projects, so one exception might be if you're interested in doing either the 'full version' or the 'half version' of a project idea that can support both modes. In such a case, you would be welcome to submit both the 'full version' and the 'half version' as separate applications, but, before doing so, please make sure that you'd be happy with either outcome if you are selected.)

Q: How early should I start working on the proposal?

A: As early as possible. Make sure to get feedback from mentors before finally submitting the proposal. This will help you to write a better proposal, as you can refine the details based on the feedback you receive. Mentors will need some time to review your proposal, so it's a good idea to begin as early as possible. Make sure to follow all instructions in the proposal template (especially around sharing and access) to reduce delays in reviewing your proposal. Please note that 75% of the accepted proposals for last year had begun their work at least 4 weeks prior to the deadline. Hence, we strongly recommend that the contributors start writing proposals as early as possible.

Q: I only discovered Oppia recently. Does this mean that, during selection, my application would automatically be ranked lower than those by other applicants who have a longer tenure with Oppia?

A: Definitely not! Here are the selection criteria we use when selecting contributors for GSoC. Note that tenure is explicitly not part of these criteria.

Q: What are the minimum number of PRs that one should have?

A: You should have at least 2 PRs merged, but they don't need to be large. Beyond that, remember that quality is more important than quantity. It is better to submit a non-trivial PR rather than a one-line wording change. Start with starter issues, then move ahead with prioritized issues from the team that is offering the project you are interested in. Here are the boards of the respective teams: LaCE Quality, Developer Workflow, Contributor Experience.

Q: What is the total number of contributors that will be accepted?

A: As many as we think will succeed, though the Google GSoC admins may impose limits based on how they decide to distribute contributor slots among the different open-source organizations.

Q: I do not have any experience in skill XYZ. Is some certification required?

A: Try to work on good first issues and take courses online. In the field of software development, it is common to develop experience and expertise as you take up and complete projects successfully. We do not require any formal certification of particular skills.

Q: Is it okay if I only focus on the frontend or backend?

A: This probably depends on the project(s) you wish to apply for. However, note that the ability to be effective in both the frontend and backend will open up more opportunities for you, since projects often touch multiple layers of the stack.

Q: The Google GSoC FAQ mentions that the program is only for new contributors. I have already contributed to Oppia and I have write access. Can I still participate?

A: The GSoC program is open to new and beginner contributors to open source and to students. Some of our contributors with write access are still beginner contributors, whereas some of our other contributors with write access will not qualify because they are experienced contributors. If you have only recently received write access, or have been contributing to Oppia for less than a year, you are probably still a beginner contributor. If the previous sentence does not apply to you, and you want to know which group you fall into, please contact @srijanreddy98, @U8NWXD or @aasiffaizal for a decision.

Q: I'd love to contribute to open source, but I'm not sure I have enough time during the summer to do a GSoC project. Can I still help out?

A: Yes, GSoC might not be the best choice if you don't have enough time during the summer. However, you can start contributing to Oppia by following the instructions in the contributors' guide (Oppia Web, Oppia Android).

Q: Why doesn't Oppia provide difficulty levels for projects?

A: Difficulty can vary from person to person depending on the skills required which is why we list all the prerequisite skills for each project.

Q: Can I use content from the project ideas list or PRD in my proposal?

A: You are welcome to use content from the project ideas list or associated project PRDs in your proposal. However, remember from our selection criteria that when we review proposals, one of the things we look for is evidence that the applicant understands the project and existing codebase well. Strong proposals will therefore contain details that are original (e.g. that are not copied from the PRD).

Dates and Deadlines

Noteworthy dates for 2023 (Official GSoC Timeline, Full Oppia Timeline):

Jan 23 - Feb 7: Mentoring organizations apply
Feb 22: Mentoring organizations are announced
Mar 20 - Apr 4: GSoC contributor application period
May 4: Accepted GSoC contributors are announced
May 4 - May 28: Community bonding period
May 29 - Jul 26: Standard Milestone 1 work period for GSoC contributors
Jul 31 - Sep 27: Standard Milestone 2 work period for GSoC contributors
Oct 6: GSoC period at Oppia officially ends

Note! The coding period dates are strict and intended to balance offering flexibility to contributors with the need on the org admin side to have a streamlined process and a more time-bounded GSoC period.

Types of work related to Oppia projects

The Oppia team is committed to making GSoC an enriching educational experience for contributors. In order to ensure a well-rounded engineering experience, GSoC contributors will have the opportunity to do some or all of the following, depending on their project:

Meet with their mentors regularly
Meet with other contributors related to their project area
Read and understand parts of the codebase related to their project
Receive code reviews for all code they write for their project
Write automated tests for their projects
Create UI mocks (if doing frontend development)
Give presentations and demos of their projects
Contribute to community initiatives, such as release testing and documentation
Write design documents (if implementing large features or introducing new systems)

We've also asked our previous GSoC contributors what they learned during previous GSoCs. Here are their collated answers:

Technical ability
- Writing clean code, while keeping in mind the requirement for the code to run in production.
- The quality of code that I write now is much improved. Also, I got the experience of working with a team.
- Building an entirely new feature in a scalable way.
- Writing robust tests.
- Working on a large codebase.
- Reading and understanding code from other open-source organizations.
- I gained a lot of technical knowledge, learned how to write automated tests better, got better at communicating and getting myself unblocked, among other things.
Technical domain knowledge
- I feel more confident on working with Angular. Oppia was the first time I worked with unit and e2e tests.
- I feel a lot more confident in writing code now, whether it be making my own projects or contributing to other open-source projects.
- I learned lots of things about typescript and webpack.
- The biggest improvement is that now I can make better design decisions, UI decisions, and technical decisions, and my understanding of the overall full-stack development has increased.
- I enjoyed finding and fixing accessibility issues.
- I learned the importance of testing and also following a clean architecture.
Technical leadership skills
- How to manage my time well, how to achieve deadlines especially when I got evaluations from external evaluators.
- How to properly plan a project before implementing it.
- Technical design skills (and validation of technical ideas).
- How to give, respond to and understand reviews.
Communication and personal development
- Putting forward my thoughts more systematically and deeply so that everyone can understand me well.
- My conversation skills have surely improved and I feel more confident while joining online meetings. Also, I am more mindful of the deadlines and enjoyed solving challenges faced in this project.
- How to write a good proposal.
- How to work with a large community like this which is spread over different time zones.
- How to reach out to people, work with them, and solve each other's problems.
- I have become a better developer, not only in term of technical skills but in thinking of actual application of the product build and the edge case scenarios the user might face. Another major learning has been to speak up and ask for help or anything required which I previously was not too confident of.
Why contributors want to stay
- Community
  - I had a great experience with Oppia and would like to continue contributing to the project. I'd like to help newer contributors too, (for example by reviewing their code when I get the chance).
  - The organisation is active and have strong community bond.
  - It is really an awesome experience working with some amazing folks from all around the world at Oppia.
  - The kind of support the complete community provides is extra-ordinary.
- Giving back
  - Everybody wants to do some good work but let's be honest, it is maybe the lazyness or the time issue that you are not able to do the type of work you always wanted to do, what can be a good way to give back to the community than to contributing here.
  - It makes me very happy that I'm a part of an organization which provides free education and I think the education is the biggest blessing we can give to one to make them stand on their feet.
  - I would love to be part of this org by knowing that maybe not much but yes I'm trying to make an impact and my contribution in the educational field. I really want to do this because where I come from there is not much of education.
  - Also the main reason to stay connected is the purpose the community serves. Providing education to those who do not have access to it helps me give back to the society.
- Growth / learning:
  - Working with Oppia has really helped me grow as a developer and I would really like to stick around to gain even more experience of real world software development.
  - The kind of work that Oppia does is really inspiring and there are a lot of opportunities to improve your skills be it be technical skills or leadership skills and most of all the people at Oppia are really fun to work with :)
  - I like working in Oppia since it not only helps me improve my coding skills but also helps me grow as an individual.

GSoC Proposal Template

When submitting a proposal, please use the provided GSoC proposal template. We will only consider proposals submitted using this template.

You are welcome to ask mentors for reviews during the proposal preparation phase. We recommend getting the WHAT section reviewed before doing substantial work on the HOW section, and getting the first part of the HOW section reviewed before doing work on the second part. This is meant to help ensure that later sections of the proposal build on a solid baseline, and avoid wasted work.

Some important notes:

Your proposal should be shared as "anyone with the link can leave comments" and sent to oppia-gsoc-discuss@. Do not send proposals directly to individual GSoC mentors. Mentors have been instructed not to respond to proposals that are not shared publicly, and we take a negative view on restricting access to proposals after feedback is provided. This is because, in the spirit of open-source, we would like to keep the discussions open, so it is intentional that everyone (including non-mentors) should be able to see your proposal and leave comments and suggestions on it.
Your final proposal should be self-contained. In particular, to be fair to all applicants, key components of the proposal should not be editable after the deadline. Don't assume that reviewers will follow external links.
Your proposal must be original (see section 2.4 of the Contributor Participation Agreement). During the selection process, proposals that are found to have passed off others' work as their own will automatically be disqualified. If you include any text in your proposal that is copied from the Internet or other sources, you should make it clear that you are doing so, and provide a link or reference back to the source, with appropriate credit. Note that you must attribute sources even if you paraphrase (i.e. re-write their content in your own words). In cases of doubt, we would encourage you to err on the side of giving credit (since not doing so may be construed as plagiarism).

Tips for writing a good project plan

Here's some advice about proposals and milestone timeline planning that we collated from previous contributors and mentors:

Choose a project you're interested in! If you have a strong interest in your project, this might make it easier for you to pick up the necessary skills and tackle unforeseen difficulties that may arise during GSoC.
Familiarize yourself with the relevant part of the codebase for your project, especially if you haven't touched it before. It's important to think about how to integrate your project with the current Oppia structure — don't design in a vacuum.
Define milestones with enough detail to get a proper ETA for each milestone (so, don't just say "write e2e tests"). Otherwise, you run the risk of significantly underestimating the timeline.
Clear written communication and presentation is crucial in preparing your proposal. The proposal should show that you have a good understanding of the codebase and the final goal of the project. For example, in a user-facing proposal, don't just make a list of files that need to be changed; it is also important to show detailed mocks and user flow diagrams that demonstrate a clear understanding of the requirements.
Limit proposal length. A lengthy proposal is not necessarily a better proposal; adding large amounts of unnecessary detail can sometimes obscure the main points you are trying to get across.
Ensure that the problem statement is within your limits to tackle, and make sure that what you're proposing is within your capabilities. The Project Ideas section contains some suggested milestones, but it is up to you to come up with a complete plan that is within your ability. In other words, contributors can propose whatever they want; it’s up to the Oppia team to subsequently figure out (during selection) whether we’re happy about what’s being proposed.
Contributors who make the last milestone bulky normally run into issues. So, make sure that you distribute work evenly.

What should applicants expect from mentors in a proposal review?

Please write your proposal on the assumption that you "own" your chosen project. From your perspective, the submitted proposal should be in as good a condition as possible before you ask for a review. Make sure that you have a sufficiently good understanding of the codebase/project so that you can find and fix flaws in the design; don't assume that reviewers are responsible for doing this for you. Note that your proposal doesn't need to be flawless — we expect that you might make mistakes, and reviewers will be happy to guide you on how to improve. Instead, by "as good a condition as possible", we mean that your proposal should demonstrate:
- Your ownership of the project
- The research you have put into writing it
- Your analytical skills
- Your independence in making complex decisions
Make sure to present solutions and ask for feedback, rather than just asking for solutions. You can do this by presenting the various solutions you came up with within your proposal, and doing an analysis of their advantages & disadvantages from the end-user perspective using a comparison table. Finally, choose the best solution you have, and explain the reasoning for how you arrived at your choice. Note that this doesn't mean that you must always have multiple ideas to solve a problem, but you should instead always explain how you reached a solution, and why is it the best one from the end-user's perspective. Think about how you might gather some data to validate your conclusions (e.g. by finding support in the peer-reviewed literature, or by showing your ideas to potential users in the target audience and asking for feedback, etc.).
Mentors' suggestions are suggestions, not mandates (often, reviewers may not be certain whether their suggestion is correct). We do not expect you to always agree with your reviewers! This means that, as the proposal owner, you are always welcome to decide whether to accept/reject such suggestions. In either case, when you are accepting/rejecting a suggestion provided by a reviewer, try to explain your reasoning and the research that led to your decision.
If you're confused about something, try to identify the point of confusion and ask have specific discussions about it, rather than simply agreeing to whatever is proposed. Don't rely on an "appeal to authority" (e.g. "I am doing it this way because reviewer XXX said so") — the rational analysis and thought that underlie the decision are what's important, so make sure that you understand and clearly communicate the reasons behind the decisions you make.
Note that the process Oppia uses to select GSoC contributors typically includes multiple independent mentors, most of whom will not have looked at the earlier versions of your submitted proposal. Your reviewer may or may not be involved in the final selection process, and it is definitely not the case that you need to implement all your reviewer's suggestions/requests in order to be selected. We recommend considering your reviewer as a friendly advisor who is available to help you and provide guidance, rather than the main future evaluator of your proposal.

Sample proposals from past years

If you'd like to get a sense of what a proposal might contain, please see our GSoC 2022 page for examples of proposals that we accepted in 2022. However, please note that the GSoC Proposal Template has been slightly updated for 2023, so please be sure to follow the 2023 template.

Note: although some of the previous years' proposals are a bit on the long side, there's no formal length requirement for your proposal. The quality of what you write is much more important than the amount of text you write, and we encourage you to write shorter proposals that still convey the main aim of the project.

Selection Criteria

In order to select contributors for GSoC, we will mainly be looking at three things:

The quality of the submitted proposal
The quality of the applicant's previously-submitted PRs (in order to assess their ability to code, debug, break down complex tasks, etc.). Note that quantity isn't a prerequisite in itself, though contributors who've submitted multiple PRs are likely to have had more opportunities to demonstrate the abilities needed to succeed in GSoC.
Our prior experience working with the contributor (do they keep commitments, communicate well, demonstrate independence/initiative/responsiveness, help others, etc.)

We believe that strong performance in these dimensions is likely to correlate well with the contributor having an enjoyable, fulfilling and productive experience over the summer, and successfully completing the GSoC program.

For the proposal, we generally look for a clear indication that the contributor has a good, clear understanding of the project, and has broken it down sufficiently well, in a way that makes it very likely to succeed. Some indicators that could help with this include:

Clear, unambiguous communication. (This is important; your proposal will be read by many mentors!)
A clear analysis of (and good design decisions that build on top of) the original project idea, with a strong focus on creating a simple, intuitive experience for end users.
A proposed solution approach which is sufficiently concrete and which demonstrates that the applicant has a good understanding of both the scope of the problem and the existing codebase.
A description, if applicable, of how the applicant plans to mitigate risks that could potentially derail the project.
A concrete, specific breakdown of the work to be done for each milestone.

Communication

If you have questions pertaining to "how to get started with Oppia" or any other queries regarding GSoC at Oppia, please ask them on GitHub Discussions (Web). Please be specific when asking questions; this makes it easier for us to help you. Also, please make sure to read the relevant "getting started" wiki page (Web) first, since the answer to your question might already exist there!

To receive important announcements and updates about GSoC at Oppia, please subscribe to the Oppia GSoC Announce mailing list.

Oppia's Project Ideas List

Note: If you're coming to this section from an external link, please make sure to scroll up and read this entire wiki page carefully, not just this section. There's a lot of useful information on the rest of the page, including a FAQ and a section describing selection criteria. Thanks!

The following is a list of Oppia's 2023 GSoC project ideas. You are welcome to choose among these ideas, or propose your own! However, if you're planning to propose something original, it's essential to engage with the Oppia community beforehand in order to get feedback and guidance to improve the proposal. We'd also recommend taking a look at Oppia's mission and seeing if there is a natural way to tie your idea to the Oppia project's goals, otherwise it might not be a good fit at this time.

Please note that the list of project ideas below is not set in stone: more projects may be added later, and some project descriptions may also change a bit, so check back regularly. In addition, the mentor assignments listed below are provisional, and may change depending on which proposals are eventually accepted.

Learner and Creator Experience (LaCE) team

1.1. Implementing the “needs guiding responses” section of the lesson analytics dashboard

We have decided that for now, we don't have the capacity to support this project.

1.2. Improving the lesson creation experience

Project Description:

The aim of this project is to provide three enhancements to the exploration editor page for lesson creators: (a) showing the history of metadata changes to an exploration; (b) showing the history of changes to a specific card and allowing that history to be browsed through; (c) allowing creators to see which languages a particular part of a lesson has been translated into when editing it, and to update those translations if appropriate.

(Note: If desired, you may submit a proposal for a half-size project covering EITHER both options (a) and (b), OR option (c). If you do this, please label your proposal accordingly with “parts (a) + (b)” or “part (c)” in the title.)

For (a): The current exploration history tab allows comparison between each “state card”, but doesn’t include details of the exploration metadata. An additional box containing these details should be added to the comparison graph.

For (b): In the state editor, it should be possible to see a “Last edited by XXX at version YYY” annotation (excluding translation commits) at the bottom right. Clicking this should open a pop-up modal that shows the changes made to the card in that last edit, and a further link at the bottom right saying “Previously edited by XXX at version YYY” which, when clicked, advances the modal to the previous change, and so on. (This is intended to function a little bit like “git blame” in the GitHub UI.)

For (c): In the state editor, when a change is made to a part of a card and this results in a “should translations be updated?” pop-up modal, the modal should also include a list of the existing languages for which that content has been translated, and the currently-saved translations for those languages. The lesson creator should be asked to update these translations if the changes are trivial to do (e.g. the content is just numbers), and otherwise leave them alone by default. This will help to save some re-translation work for the community. Note: these translation changes should not be applied immediately – if the lesson creator subsequently discards their change before committing it to the backend, then those translation changes should also be discarded.

Size of this project: large (~350 hours); can be reduced to medium (~175 hours) if desired (see description)

Potential Mentors: @Rijuta-s

Product Clarifier: @dchen97

Technical Clarifier: @SanjaySajuJacob

Knowledge/Skills Recommended:

Knowledge and understanding of Python
Knowledge and understanding of TypeScript, Angular, HTML, and CSS
Ability to write Beam jobs
Technical design skills
(Ideally) Some UI/UX design skills

Suggested Milestones:

Milestone 1: Creators should be able to see changes to an exploration’s metadata in the comparison view in the history tab. They should also be able to navigate through all the historical changes to a particular state (excluding changes that solely affect translations).
Milestone 2: Creators should be able to see a list of existing translations through the modal that pops up when they make changes to a published exploration, and should be able to edit those if the edits are easy to make.

Dependency on Release Schedule: Some sections of this proposal may entail writing Beam jobs to update existing server data. The timeline should be arranged so that such jobs can be run and verified during the appropriate release cycle. Note that releases can be delayed by up to a month, and you should account for such delays in your timeline.

Proposal notes:

The main thing that is important to demonstrate in the proposal for this project is good technical design skills. Strong proposals would first show a good understanding of the current system, and correctly describe the parts of it that are relevant to the relevant subproject, before suggesting the changes that would be needed in order to achieve the desired functionality.
For (b), some precomputation may be needed in order to retrieve the version of the "previous change" quickly.
For (b), it would be useful to generalize the system so that one can go forward/back from any given state. This would allow additional useful functionality like clicking on a state in a particular version when it's shown in the history tab, and moving forward/back through its history. Be sure to handle state additions, deletions and renames correctly!

Useful resources:

How to write Apache Beam jobs: wiki page
Release schedule: wiki page

1.3. Serial chapter launch

Project Description:

Currently, it takes a very long time to publish lessons as it requires the entire topic to be published. Therefore, the broad aim of this project is to create a system that allows for individual lessons to be published as they are created. This project involves the following steps:

Allow curriculum admins to create a pipeline/queue of unpublished chapters on the story editor page by assigning each lesson one of three labels: Draft, Ready to Publish and Published.
Allow curriculum admins to set up planned dates for publication for the lessons currently in the queue. These dates should be used to notify the curriculum admins about upcoming or behind schedule launches.
Create a system that sends weekly emails to curriculum admins notifying them about upcoming or missed deadlines.
Notify learners about recently published lessons on the learner dashboard and the classroom page, and about upcoming ones on the chapter end card.
Allow learners to opt to receive email notifications when new lessons are published.

Link to PRD: Serial Chapter Launch

Size of this project: medium (~175 hours)

Potential Mentors: @Nik-09

Product Clarifier: @dchen97

Technical Clarifier: @seanlip

Knowledge/Skills Recommended:

Knowledge and understanding of Python
Knowledge and understanding of TypeScript, Angular, HTML, and CSS

Suggested Milestones:

Milestone 1: Create a system that allows curriculum admins to add lessons to the pipeline and mark them with appropriate labels and deadline dates, which is then used to send appropriate notifications to the admins once a week via email.
Milestone 2: Implement the learner-facing part of this project that involves pushing notifications to the learner dashboard and the classroom pages when new topics are published. Also notify learners about upcoming topics when they reach the chapter end card. Learners should also be able to sign up to receive email notifications when new lessons are published.

Proposal notes:

Hide this feature behind a feature flag until the entire project is complete.

Useful resources:

1.4. Learner Dashboard Redesign

Project Description:

The Learner Dashboard is the “home page” for signed-in learners. This is the place where they can get a broad understanding of their progress and quickly be able to pick up where they left off or start something new.

In its current state, the architecture of the learner dashboard is inconsistent and unintuitive. Therefore this project aims to fix various issues plaguing the learner dashboard. Broadly, the contributor is expected to the following:

Move the “Feedback Updates” tab out of the learner dashboard to the profile pic dropdown. There should also be an indicator that appears when there are updates to show, and the overall feedback-update flow (including sending and receiving messages in feedback threads) should work smoothly.
Update the learner dashboard to have the following architecture:
1. Home
  1. “Continue where you left off” section
    1. CTA (call to action) to start any lessons (from Classroom or community library) that are in progress
    2. CTA to start next suggested lesson for any goals they’ve set (if any)
    3. CTA to start next suggested lesson to complete for any learner groups they’ve joined (if any)
  2. Learn something new section
    1. Show topics in classroom and CTA to view the topic pages
    2. CTA to start any lessons that haven’t been started that are in their Play Later list (if any)
    3. CTA to go to Math Classroom (“Browse All Math lessons”)
    4. Lesson search box
  3. Learner Groups section
    1. Show any invitations that are not yet responded to for learner groups
    2. Include CTAs to show more info, accept, or decline invitations
    3. Include a CTA to view any learner groups they’ve already joined (should navigate to the associated learner group page)
  4. Review section
    1. If they’ve completed any previous topics from the classroom, suggest CTAs for up to 3 relevant review cards
2. Goals
  1. CTAs to set or remove any goals (can only have up to 5 goals set at a time)
  2. Can view current goals and progress towards completing those goals
  3. Can view previously completed goals
  4. CTA to start next suggested item to move forward their goal (i.e. next lesson in the topic they need to complete)
3. Progress
  1. Can view all lessons (Classroom and Community Library) that are currently in progress
    1. CTA to continue any of these lessons
  2. Can view all skills they’ve started learning or mastering (i.e. via Practice sessions) and the level of mastery
    1. CTA to start practice session with that skill (will be directed to practice session tab for that topic with that skill pre-selected)
    2. CTA to view relevant review card for that skill
  3. Can view all completed lessons (Classroom and Community Library)
Make sure the new architecture and UI is responsive and has all the necessary accessibility labels (like aria, tag etc)

Link to PRD: Learner Dashboard IA Redesign Project Primer

Size of this project: medium (~175 hours)

Potential Mentors: @heyimshivam

Product Clarifier: @dchen97

Technical Clarifier: @seanlip

Knowledge/Skills Recommended:

Knowledge and understanding of TypeScript, Angular, HTML, and CSS

Suggested Milestones:

Milestone 1: Move the feedback tab out of the learner dashboard and add it in the profile pic dropdown menu and add an indicator to notify the user when there updates to show and update the architecture for the home tab. Verify that the feedback flow is working fully end-to-end.
Milestone 2: Update the architecture for the Goals and Progress tabs.

Proposal notes: None

Useful resources: None

1.5. Improvements to Math Interactions

Project Description:

In the current system,

There is no interaction that takes percentages as a response. Currently, TextInput fields are used to take input in the form of percentages.
Learners use their physical keyboards on laptops or desktops to give input to math explorations. This may create confusion and can slow down or hinder learners' progress. For example, users may not identify * as the symbol for multiplication, they may instead provide “x” as the symbol for multiplication in their response, which will be recorded as a wrong answer.
Number lines are implemented by creators using the ImageClickInput interaction.

The proposed solution to this problem is to:

Introduce a clickable keyboard to solve math interactions.
1. For algebraic expression, numeric expression and algebraic equation input, a clickable keyboard with special characters will show up below the input field on desktop/mobile. This keyboard will have the basic algebraic keys like ‘+’, ‘-’, ‘×’, ‘÷’, ‘(‘, ‘)’, ‘=’, and when clicked it will “type” that character in the input field.
2. Learners should be able to use both these keys and their standard keyboard when submitting their solution.
Allow learners to submit answers in the form of percentages and allow curriculum admins to convert the responses from text input fields to percentage.
1. Introduce a percentage interaction with a ‘%’ button below it.
2. Provide a utility, gated behind a feature flag, for curriculum admins to convert existing text input fields to percentage input. Curriculum admins should be able to transform text input to percent input with the click of a button, and the system will accept that change and perform the necessary updates if it is able to validate that the update can be done successfully for that exploration card. The effect of the button should be to perform the standard actions that would be needed to do the update manually, but without losing any of the existing answer groups, translations, and voiceovers.
Introduce a number line interaction.
1. Lesson creators should be able to provide the start and end integer values of the number line as well as the interval length. The number line should have equally spaced out marks between the starting and ending values. Creators should not be able to create a number line with more than 10 or less than 3 points.
2. Creators should be able to specify the feedback that the learner gets based on their responses at various points along the number line. Care should be taken to correctly handle the case when the number line parameters subsequently change – a warning should be displayed to the creator if the corresponding rule becomes invalid.
3. Learners should be able to choose and drag their solution along the number line and the cursor should instantly "snap" to the demarcated lines along the number line. The learner should be able to confirm their choice and get feedback once they have submitted.

Link to PRD: Improvements to Math Interactions PRD

Size of this project: medium (~175 hours)

Potential Mentors: @kevintab95

Product Clarifier: @dchen97

Technical Clarifier: @Lawful2002

Knowledge/Skills Recommended:

Knowledge and understanding of Python
Knowledge and understanding of TypeScript, Angular, HTML, and CSS

Suggested Milestones:

Milestone 1: Implementation of percentage interaction and text to percentage conversion utility
Milestone 2: Implementation of virtual math keyboard and number line interaction.

Useful resources:

1.6. Improve Accessibility

Project Description:

Oppia aims to provide a good and fruitful learning experience to all people. This includes people with certain conditions like poor vision, hearing loss etc. Certain tools like Lighthouse grade pages based on their accessibility and assign a score from 0 to 1 (inclusive). As of now not all pages on Oppia have an accessibility score of 1, which can make it difficult for some learners to use Oppia which is not ideal.

Therefore, the aim of this project is to improve the accessibility of all learner facing pages on Oppia, i.e. getting the Lighthouse scores of all these pages to 1.0. Under this project, the contributor is expected to fix all the accessibility issues that have already been filed and run Lighthouse tests on all learner facing pages and bring their scores to 1.0, if that isn’t already the case.

What's Explicitly Out of Scope: Improving the accessibility of non-learner facing pages (e.g. Admin page, Release coordinator page, etc.)

Link to PRD: None

Size of this project: medium (~175 hours)

Potential Mentors: @Rijuta-s

Product Clarifier: @dchen97

Technical Clarifier: @seanlip

Knowledge/Skills Recommended:

Knowledge and understanding of TypeScript, Angular, HTML, and CSS

Suggested Milestones:

Milestone 1: Fix all the accessibility issues already filed on Oppia’s github repository.
Milestone 2: Bring the Lighthouse Accessibility scores of all learner facing pages to 1.

Proposal notes:

Run Lighthouse tests in the browser

1.7. User feedback reporting UI on Web

Project Description:

Currently, users of the Oppia platform can submit feedback through one of three channels depending on the nature of the issue:

Issues related to lessons are reported through the feedback tab present inside the lesson player.
Technical issues are generally reported through Github.
Additional feedback may be shared through the site feedback form linked in the footer at oppia.org.

Three different channels for submitting feedback are not ideal because it discourages casual users from reporting issues. Therefore the aim of this project is to introduce a feedback button on every page of Oppia’s web app, clicking on which will open a minimizable modal where users can submit different kinds of feedback. This will make it easier for less technically adept users to submit issues/feedback without having knowledge about the workings of the Oppia platform. The issues/feedback generated will contain metadata (the page the user clicked the feedback button from, current language, etc.) which will make it easy to ascertain details about the shared feedback without having the author explicitly mentioning it.

The contributor is expected to create a new feedback modal that is reachable from every page on Oppia, possibly by pressing a button on the navbar (or any other spot which is easily reachable by the users). Once on this modal, the users should be able to select the type of feedback (technical, content, platform, etc.), add a description, upload an image, add server logs (if applicable), and optionally add their contact information (if they are open to the Oppia team following up).

The feedback should then be sent to an email alias (feedback@oppia.org), which would then be evaluated by the tech and PM teams to determine if and how to address them.

Link to PRD: Web user feedback PRD

Size of this project: medium (~175 hours)

Potential Mentors: @sahiljoster32

Product Clarifier: @dchen97

Technical Clarifier: @seanlip

Knowledge/Skills Recommended:

Knowledge and understanding of Python
Knowledge and understanding of TypeScript, Angular, HTML, and CSS

Suggested Milestones:

Milestone 1: Create logic for handling the submitted feedback. Make sure the submitted feedback is sanitized. Add necessary metadata to each piece of feedback to add context, after which it is sent to the feedback team via email.
Milestone 2: Build the frontend interface to allow users to submit feedback. Ensure this feedback modal is accessible from everywhere on the Oppia platform and supports i18n, is RTL and mobile friendly, and, has proper aria tags for accessibility.

Proposal notes:

The feedback needs to have certain metadata attached to it to provide context to the person triaging the issues later down the line. This metadata should include the current page (where the modal has been opened) and the current site language. The information about the current page may be fetched from the context service or the URL can itself be used (in case the context service doesn’t provide enough information about the current page). The site language can be fetched using the i18n language code service.

Note that platform-level feedback submitted through this channel should not be stored anywhere in the backend.

To prevent bots from spamming the feedback channel use Google reCAPTCHA to validate users if they are not logged in (the captcha is not required when the user is signed in).

Useful resources:

Contributor Dashboard team

2.1. Contributor Dashboard Admin Stats Table

Project Description:

Contributor dashboard admin page revamp. Table view of contributors with key stats, e.g. number of translations/questions submitted/reviewed. Each row represents a contributor and is actionable, allowing an admin to add or remove contribution rights.

Size of this project: medium (~175 hours)

Potential Mentors: @sagangwee

Product Clarifier: @dchen97

Technical Clarifier: @sagangwee

Knowledge/Skills Recommended:

Knowledge and understanding of Python
Knowledge and understanding of TypeScript, Angular, basic HTML, and CSS

Suggested Milestones:

Milestone 1: Complete the backend changes:
- Introduce language coordinator admin role
- Modify contributor dashboard admin controller to allow adding or removing language coordinators
- Add new endpoint to contributor dashboard admin controller for fetching contributor stats
Milestone 2: Complete the frontend changes:
- Display contributor stats table on contributor dashboard admin page
- Show different available admin actions depending on user admin role
- Add support for sorting by table column (will require some backend query changes)
- Implement table pagination

Dependency on Release Schedule:

Proposal notes:

For contributor stats, you can query the existing stats models in core/storage/suggestion/gae_models.py, e.g. TranslationContributionStatsModel.
To support sorting by table column, we’ll need to add a sort key for each attribute. The sort key will be used in the storage query. See PR #1653 for an example.
Pagination is hard. See PR #16289 to see how pagination was added to the existing contributor stats tables.

Useful resources:

PRD

2.2. Prioritized Translation Languages and Auto-Translations

Project Description:

Support the marking of languages as “prioritized” for translation. Prioritized languages will have their remaining untranslated lesson text content auto-translated to make the lessons available in the language as quickly as possible. Auto-translated content will appear with a note explaining the auto-translation. Non-prioritized languages will also be auto-translated after a threshold of translation, e.g. 95%.

Additionally, finish adding computer-aided translation (CAT) support when submitting translation suggestions.

What's Explicitly Out of Scope:

Auto-generation of translated voiceovers
Enable concept card translation
Enable review card translation
Enable auto-translation of images in lessons
- Likely will be more difficult to do successfully compared to translating text
Surfacing auto-translations in Contributor Dashboard
Enable practice question translation

Link to PRD: Language Management and Lesson Auto-translation PRD

Size of this project: medium (~175 hours)

Potential Mentors: @qinghaoyang, @sagangwee

Product Clarifier: @dchen97

Technical Clarifier: @sagangwee

Knowledge/Skills Recommended:

Knowledge and understanding of Python
Knowledge and understanding of TypeScript, Angular, basic HTML, and CSS

Suggested Milestones:

Milestone 1: Complete the backend framework for prioritized languages:
- Add notion of prioritized language in backend storage schemas
- Store list of prioritized languages
- Create beam job to auto-translate remaining text content for a prioritized language
Milestone 2: Surface prioritized languages in the UI and add CAT support:
- Enable the adding of a prioritized language in the contributor dashboard admin page
- Add note to lesson text content that has been auto-translated
- Auto-translate non-prioritized language once translation threshold has been achieved (95%)
- Add computer-aided translation capability to translation contribution modal

Dependency on Release Schedule: Some sections of this proposal may entail writing Beam jobs to update existing server data. The timeline should be arranged so that such jobs can be run and verified during the appropriate release cycle. Note that releases can be delayed by up to a month, and you should account for such delays in your timeline.

Proposal notes:

We’ll likely write a beam job to populate the auto-translations for a language. See the wiki for more details.
Maybe ~80% of the CAT work is already done, including all of the backend changes. We just need to hook it up in the frontend, e.g. see working PR: #12624 and related issue #11434.
- See Computer Aided Translations (CAT) backend milestone PRs.
The CAT backend utilizes the Google Translate API for auto-translations. We can re-use that work here for auto-translations. Alternatively, we can investigate other translate APIs that may offer better translations, e.g. Oppia has done studies in the past that have shown Microsoft to produce preferred translations.

Useful resources: None

2.3. Improvements for translation reviewer experience

Project Description:

Translation reviewers have given feedback that the current contributor dashboard reviewer workflow doesn’t match with most of their needs. This project aims to improve the translation reviewer experience in the contributor dashboard.

Size of this project: large (~350 hours)

Potential Mentors: @chris7716, @sagangwee

Product Clarifier: @dchen97

Technical Clarifier: @chris7716, @sagangwee

Knowledge/Skills Recommended:

Knowledge and understanding of Python
Knowledge and understanding of TypeScript, Angular, basic HTML, and CSS

Suggested Milestones:

Milestone 1:
- Show translation cards according to the order of the content flow in the lesson.
- Link to the exploration editor so that the original lesson can be seen (Mock)
- Show the size of the translation (Mocks in progress)
- Allow translation reviewers to pin/unpin (Mocks in progress)
Milestone 2:
- Allow reviewers to undo the acceptance or rejection of a translation card for up to 30 seconds.
- Show image alt text below the image. (Mocks in progress)
- Notify translation reviewers about new submissions by email. Existing CD reviewer notification system.

Dependency on Release Schedule: None

Proposal notes:

For showing translation cards in order, we can likely make use of the computeBfsTraversalOfStates() function in core/templates/services/compute-graph.service.ts to obtain a lesson's state names in order. We can then sort translation cards by lesson state. Within a state, it’s probably fine to leave translations unsorted, as there’s not necessarily an ordering of content within a state.
To support lesson pinning, we have to make sure the pinned lessons are returned at the top of the list of lessons with translation suggestions in the fetch query here (_get_reviewable_exploration_opportunity_summaries()).
We will likely want to introduce a new storage model to track pinned lessons by language and user. For example:
- PinnedReviewableLessonModel
  - user_id: str. User ID.
  - exp_id: str. Exploration ID.
  - language_code: str. Language code.
To support translation review undo, we will likely want to enqueue suggestion creation in a task scheduled for 30 seconds in the future. If the user decides to undo the translation, we can then delete the task. See core/domain/taskqueue_services.py, core/platform/taskqueue/cloud_taskqueue_services.py, and CloudTasksClient. Useful resources:
PRD

Data validation team

3.1. Fix validation errors

Project Description:

The aim of this project is to fix various problems with data in our existing models. In order to do that, usually you’ll write a Beam job that takes the existing models and fixes them. Also, you’ll need to put in place measures to ensure that these problems don’t reoccur in the future.

Task set 1

Implement a process to ensure that external storage models linked to a storage model are updated in case of storage model deletion (#10809)
Remove traces of "cloned from" from old versions of some explorations (#10828)
Fix datetime fields in LearnerPlaylistModel, CompletedActivitiesModel, UserSubscriptionsModel, and UserSettingsModel (#11616, #12120)
Fix CompletedActivitiesModel and IncompleteActivitiesModel to only reference existing and public explorations (#14968)
Fix ExpUserLastPlaythroughModel (#14972)

Task set 2

Handle deprecated commands (#10807, #10820)
Fix GeneralFeedbackThreadModel entities with missing related GeneralSuggestionModel entities (#11736)
Fix UnsentFeedbackEmailModel entities with missing GeneralFeedbackThreadModels and GeneralFeedbackMessageModels (#14966)
Fix GeneralSuggestionModel entities that are marked as rejected but are missing their final reviewer ID (#14967)
Fix GeneralFeedbackMessageModel.feedback_thread_ids to only reference existing GeneralFeedbackThreadModel (#14971)

Size of this project: large (~350 hours)

Potential Mentors: @lkbhitesh07, @JayVivarekar

Technical Clarifier: @lkbhitesh07, @JayVivarekar

Knowledge/Skills Recommended:

Apache Beam jobs
Python
Responsibility with schedules and good communication, because you will need to coordinate with the Oppia release team to conduct test runs on the backup server, and this can delay the project if not handled responsibly.

Suggested Milestones:

Milestone 1: Fix all tasks from Task set 1.
Milestone 2: Fix all tasks from Task set 2.

Dependency on Release Schedule: The timeline should be arranged so that such jobs can be run and verified during the appropriate release cycle. Note that releases can be delayed by up to a month, and you should account for such delays in your timeline.

Proposal notes:

You need to have at least one PR that either creates some Beam job or fixes some existing Beam job.
When designing the Beam jobs to fix existing issues in our datastore, make sure that those jobs only make modifications that are strictly necessary. Be especially careful with updates or deletions, since it is important to avoid any data loss or corruption. For each task, you should also write a verification Beam job that verifies that the changes were correct. You should also manually verify (on a test server) that the job has done the right thing after it is run. Make sure to also explain what the rollback procedure for the job is (if something goes wrong while running it).
Also, note that, in general, the jobs you write should be designed to be idempotent. That is, running them twice should result in the same outcome as running them once (since this allows us to just rerun them if an error happens within the Beam framework).
In your timeline, make sure that you account for possible delays in the job testing procedure. In particular, note that when you submit the job for testing on the backup server, it might take up to 48 hours to get the results.
In your proposal, please clearly explain how you plan to tackle each task from the list above. There are usually two parts to this: (a) making sure that we fix the current issues in our datastore, and (b) ensuring that those issues don’t reoccur in the future (which often requires doing a careful audit to prove that all possible “loopholes” that would allow them to occur have been plugged). Additionally, here are some suggestions for information to include in your proposal to demonstrate that you understand each of the subtasks; you will also find some helpful tips further down below:
- Task set 1, subtask 1: List all the datastore models and their corresponding external datastore models, explaining how they are connected. Take one of the models as an example and explain how the complete process of prevention will work. You can refer to the second bullet point under the "How to remove a model" guide below for more details. Also explain how you will fix the currently-existing datastore models that are linked to deleted models.
- Task set 1, subtask 2: Explain how you plan to deprecate the "cloned_from" field from the ExplorationRightsModels. How do you plan to remove the explorations having "cloned_from" field as not None? You can refer to "How to remove a field from a model" guide below for the reference.
- Task set 1, subtask 3: How do you plan to find the correct way to update the "created_on" date, what models will you be using in order to get the correct "created_on"? How will you prevent this from happening in the future? For reference you can take a look at this PR which solves the similar problem.
- Task set 1, subtask 4: Mention the complete process that you will be following in order to to complete this task. What do you plan to do with the models which reference deleted or private explorations? How will you prevent this from happening in the future?
- Task set 1, subtask 5: Mention what do you plan to do with each of the validation errors ExpUserLastPlayThroughModel.
- Task set 2, subtask 1: Explain how you will modify the existing structure used for commands so that we can accommodate for deprecations and also changes to existing commands, make the changes generic enough. Focus on one example of deprecation and one example of a change to a command.
- Task set 2, subtask 2: Explain what do you plan to do with the GeneralFeedbackThreadModel which does not have any related GeneralSuggestionModel?
- Task set 2, subtask 3: Mention how you plan to remove the invalid UnsentFeedbackEmailModel, also explain your decision. Invalid here means that the two fields thread_id and message_id do not reference GeneralFeedbackThreadModel and GeneralFeedbackMessageModel respectively. Mention the way to prevent this from happening in the future.
- Task set 2, subtask 4: Explain how you plan to fix the GeneralSuggestionModel that is rejected but is missing final reviewer ID, also explain your decision. Mention the way to prevent this from happening in the future.
- Task set 2, subtask 5: How do you plan to fix the GeneralFeedbackMessageModel referencing non existing GeneralFeedbackThreadModel via thread_id field. Explain your decision.
Tip – How to safely remove a field from a model: You would need to write a beam job for this particular part. Previously we were using this approach to remove a field from the model. Before removing the field make sure that the field is set to None and it is not used anywhere in the codebase. Alongside this you have to remove the field from the model present in the storage layer and update the tests accordingly.
Tip – How to safely remove a model:
- Removing the model via beam job: We will be using "ndb_io.DeleteModels()" to remove all the unwanted models. You will be able to find several examples in the codebase related to this for reference.
- Removal of externally-linked-models when removing storage models – for this, let's look at an example. The ExplorationRecommendationModel stores recommendations link to explorations; suppose we want to remove this model when we remove the ExplorationModel. Note that ExplorationModel is inherited from BaseModel and we have overridden the delete_multi() function inside the ExplorationModel. As you can see by examining the codebase, from editor.ExplorationHandler.delete we make a call to exploration service which in the end makes call to Exploration.delete_multi(). So, now we know where we have to make changes: inside the delete_multi function we first have to fetch the ExplorationRecommendationModel (which we can do using the get_multi() function) and after that, we can call its deletion method too.
Tip – How to analyze what needs to be done: Let us take, as our example, subtask 4 in task set 1. If we take a look at the issue, we can see that there are 2 models (CompletedActivitiesModel and IncompleteActivitiesModel) which in some cases refer to private or deleted explorations. Our job is to make the 2 activities models valid and to make sure that this does not happen in the future. Now, from the issue description, we know that we need to make some changes to both models so that they do not reference invalid explorations (i.e., private or deleted exps). Both models have exploration_ids as one of their fields, which is of typeList[str]. So, in order to fix the currently-existing models, step 1 is to remove the private or deleted explorations from this field. Here, we will do this for CompletedActivitiesModel; the same process works for IncompleteActivitiesModel:
- Make a PCollection of CompletedActivitiesModel models. Make another PCollection of ExplorationModel models, then extract the IDs and put them into the PCollection, something like this. Now convert the latest PCollection you made of exp IDs to an iterable type (you can refer to this example in the codebase).
- Next, iterate over each CompletedActivitiesModel and compare its exploration_ids field with the iterable collection of exp IDs you made in step 1. If an exploration_id from that field is not present in the list, then remove that ID from the exploration_ids field. Now, you have a Pcollection of CompletedActivitiesModel models whose exploration_ids fields contain only explorations which are not deleted.
- Repeat the previous step by creating a PCollection of explorations that are private, and reusing the CompletedActivitiesModel PCollection from the previous step. After removing private explorations, you will put the models to the datastore in order to save them; for that, you can use ndb_io.PutModels().
- You also need to write an audit job to confirm that both of the activities models are valid, so that we can run this on a test server and confirm that the changes you have done are correct.
Tip – How to prevent issues from happening in future: We will continue the example from above. Let us analyze why the issue might have occurred in the first place.
- Suppose both of our activity models refer to deleted explorations – then, one possibility might be that we forget to update the activities models at time of deletion.
- Now that we have a hypothesis for why this happened, we should check that we understand the process for deleting an exploration (mentioned in the "How to safely remove a model" section above). To validate this hypothesis, we can read through the codebase to see what happens when we delete an exploration. As discussed previously, this happens in exp_services.py file in the delete_explorations() function. Take a look at that function and check if you can find anything related to the removal of exp id from the CompletedActivitiesModel.
- Now, go through the codebase and try to see where we are using CompletedActivitiesModel and how it is related to explorations. Try to check how we are populating the CompletedActivitiesModel model in relation to explorations. You will find that, in exp_services.py, there is a function named delete_explorations_from_activities. So, one option might be to use this function from within the delete_explorations function inside the exp_services file.
- To verify this plan, first write down steps to reproduce the error, so that you can see what happens before and after the proposed change:
  - Create an exploration and then publish it. After that create a topic, a story and a chapter. When creating the chapter, you will be able to link the exploration to it; you must have admin rights for this. Finally, in the admin dashboard config tab, add the topic id to the classroom page.
  - Set up DSAdmin locally, which will help you visualize the datastore locally.
  - Create another user, visit the classroom page, and complete the chapter. Now check DSadmin and you will be able to see CompletedActivitiesModel model which was not there before.
  - Come back to the admin user and delete the exploration. Now check CompletedActivitiesModel inside DSadmin again and see if the exploration id still exists there.
- Run the above steps before making the change. Then make the change and run the steps again from the beginning. This will help you determine whether your solution works.
This example shows how to modify the codebase so that such data errors can be prevented in future; you should follow a similar process for other tasks. Notice how we formulate a hypothesis, check it, and use that to reach a suitable conclusion.

Useful resources: None

Developer workflow team

4.1. Dockerize Oppia

Project Description:

We want to package Oppia as a Docker container so that new contributors can get started by running make up after cloning the repository to install all the dependencies and start the local development server. This will be much easier than the current installation process, which is often painful to troubleshoot.

Requirements:

Installation:
- All installations should happen via Docker files. Please avoid using any other scripts.
- You should use Docker compose V2 (since compose V1 has been deprecated (source)) and Compose file V3.
- You should create a Makefile that supports the following Make commands:
  - make run-offline: Starts the Oppia server without checking dependencies. Should not require internet access.
  - make run: Sets up and starts the Oppia server. Also runs the steps in “make update-pip-and-npm-packages”.
  - make install-dependencies: Installs all the necessary dependencies (redis, App Engine, pip libraries, npm libraries, etc.), but does NOT start the server. This does NOT include performing the steps from “make update-pip-and-npm-packages”.
  - make update-pip-and-npm-packages: Updates the locally-installed pip and npm packages to match the versions specified in dependency specification files (e.g. packages.json). Should check that the dependencies match the versions specified in the currently checked-out commit. If they do not, the correct versions should be installed.
  - make clean: Cleans the entire setup. Deletes all the dependencies.
  - make terminal: Opens a terminal accessing the Oppia environment built using Docker. Note: The tests will be run in the standard way (e.g. python -m scripts.run_frontend_tests) from the Docker terminal after running the “make terminal” command.
- The Setup should be quick and easy. It should follow the following steps
  - Install Docker Desktop
  - Clone oppia/oppia
  - Run make install-dependencies
  - Run make run
- The setup should work the same way on Ubuntu, Mac (both M1 and Intel chip) and Windows. In all these platforms, the setup should use no more than 8GB RAM.
- Developers should be able to run tests, use git (e.g. switch branches, push changes, and checkout commits), and use all the other development tools we document in the wiki. The interface for doing so should undergo only minimal changes.
- All dependency management should be handled by Docker and your Makefile. You will need to remove the current dependency-management logic from our Python scripts.
Dependencies for Docker installation:
- The Oppia developers must be easily able to update the local setup when a dependency is updated.
- All dependencies must be pinned to a specific version and come from a trustworthy source. There should be a method to verify the checksum of each dependency that is being installed.
CI/CD test (GitHub actions)
- All CI/CD tests that require the installation of Oppia (check https://github.com/oppia/oppia/tree/develop/.github/workflows) must be migrated to use docker. The docker image should only be set up once, and then stored and reused (cache the docker image) for all the remaining CI/CD tests in that run.

What's excplicitly out of scope:

Here are ideas we have for the future but that you do not need to implement for this project:

Create a repository on Docker Hub to allow quick deployments onto a server. This is to deploy PRs (or the develop branch) onto a server to allow reviewers to test the changes themselves. The setup instructions on the server would be: Run docker pull oppia/oppia

Size of this project: large (~350 hours)

Potential Mentors: @U8NWXD, @gp201

Product Clarifier: @seanlip

Technical Clarifier: @gp201

Knowledge/Skills Recommended: Applicants should be familiar with Python and have some exposure to Docker.

Suggested Milestones:

Milestone 1:
- Under Docker, the server should launch successfully, and all Oppia pages should be functioning correctly. All makefile commands with respect to starting the Oppia server must work (make run, make clean, make update-pip-and-npm-packages, make install-dependencies, make terminal).
- Update the wiki to include instructions on how to setup Docker and setup Oppia using docker
Milestone 2:
- The remaining make command must work (make run-offline). All tests should work locally under Docker. All github actions should be migrated to use a single build step that creates a docker image which is cached and used by the rest of the jobs. All the python scripts should be removed.
- Update the wiki to include instructions on how the Docker setup works for Oppia (Ensure to explain the setup process in detail and each service),how to debug setup issues in Docker and share docker images to other developers. Dependency on Release Schedule: Applicants should be familiar with Python and have some exposure to Docker.

Proposal notes:

We recommend the following approach:

Set up each of Oppia’s dependencies. For example, you might install them as Docker images (preferred) or use a separate Dockerfile to download them from the internet and set up the required dependency. For all Docker containers/services, you should create health checks. Given below are the key dependencies of Oppia and the suggested installation approach for each:
1. Redis (redis:7.0-alpine) (Docker Image)
2. ElasticSearch (elasticsearch:7.17.0) (Docker Image)
3. Google Cloud Datastore (Docker Image)
4. Firebase (Setup using a separate Dockerfile)
5. All the packages from dependencies.json should be moved to package.json. The moved packages should be downloaded via npm (preferred), or by forking the package into Oppia and downloading from the fork. Please check this document for where to move each of the libraries. (Dockerfile)
6. Any remaining third-party dependencies should be installed via npm or pip (Dockerfile).
Note: You do not have to stick to the above method of installation. If you can prove that a different approach would result in improved effectiveness and efficiency in terms of memory occupied, internet data used and speed of setup, you may use that approach instead.
Verify that the Oppia development server can run and works fine under Docker, and catalog any issues that occur for later fixing. In particular, check that:
1. (Redis) The flush memcache button on the /release-coordinator page works (and there is stuff stored in memcache before that button is pressed)
2. (ElasticSearch) The search functionality in the community library page works
3. (Firebase) It’s possible to log in
4. (Google Cloud Datastore) It’s possible to create a lesson and load it
Verify that backend, frontend, e2e tests, linter, mypy, lighthouse, etc. checks can run within the Docker container.
Add a non-required Docker Action to test the docker setup.
Once this works for 20 runs: change all our Github Actions to use docker setup.
Once GitHub Actions works reliably with the docker setup process: move developers to the new setup process (and try to centralize the build step into a single workflow). (Cache only the dependencies. Avoid caching webpack, as this will be taken care of by the “Make CI faster” project.)
Deprecate the python -m scripts.start setup process.

Useful resources: None

4.2. Developer Workflow Release Dashboard

Project Description:

The aim of this project is to create a dashboard for release testers and team leads on the Oppia developer team. The dashboard should be built as a standard App Engine app that supports login. It should show a list of all commits in develop. For each commit, it should show the status of the release candidate (RC) that was built for that commit:

A link to the RC. RC links look like this: http://test-develop-17018.oppiaserver-backup-migration.appspot.com/. These are generated by a deployment script that runs in a private repository. While we can’t add you to this repository, we can answer questions you have about how to get these links.
Did that RC pass acceptance testing, fail acceptance testing, or get skipped?
For all RCs that pass acceptance testing:
- Prod server. Show a button next to the deployable RC (if present) to deploy it to prod. An RC is deployable if it is strictly newer (here “newer” refers to commit order, not the timestamp on the commit) than the currently-deployed RC, all CI tests are passing, all acceptance tests are passing, and no newer RC meets the preceding deployability requirements (i.e. only the newest RC with passing tests is deployable). Deploying the RC should be restricted to members of the team-leads-and-release-coordinators Google Group or allowlist; when the “deploy” button is clicked, it should notify that mailing list and state who authorized the deployment. The deployed version should be formatted on App Engine as {{tag}}-{{commithash}}, where {{tag}} is the release version (e.g. “3.2.1”).
- Test server.
  - If the RC has already been provisioned on a test server, show a link to that test server.
  - If not, show a button to provision a test server on BrowserStack with this RC. This button should be restricted to members of the release-testers Google Group. Once provisioned, it should send an email to the requester and the status in the dashboard should be updated. The deployed version should be formatted on App Engine as {{tag}}-{{commithash}}, where {{tag}} is the release version (e.g. “3.2.1”).

(Note that the team-leads-and-release-coordinators Google Group will be a member of the release-testers Google Group.)

Pagination should be included to allow paging through multiple pages of commits (50 per page), but it is fine not to go back more than 300 commits or so.

Include full documentation on how to update code, test, and deploy new releases of this app. The app will also need unit tests and linting, and to support easy developer setup.

What's explicitly out of scope:

We will provide the correct endpoints to trigger a prod server or test server deployment using GitHub Actions. If those endpoints are not yet ready, you can call a stub.
From a design perspective, it is sufficient that the dashboard has the right information architecture and is reasonably easy to use. You don’t need to make it super pretty.
You don’t need to write any acceptance tests; these will be provided. If they are not ready in time, you can interact with a stub.
We have access to BrowserStack credits as an open source org, so you don’t need to provide the final BrowserStack account. However, you should create your own account and use the free version to develop your prototype and to do any testing or development. You will also need to tell us how to configure the final BrowserStack account.
Note that, in addition to prod/test-server release candidates deployed using this dashboard, our release pipeline also supports manually-triggered ad hoc deployments for testing migration PRs. In such cases, the version on App Engine is formatted as {{username}}-{{PR number}}-{{commithash}}. Supporting such ad hoc deployments using the release dashboard is not part of this project.
We will provide a domain or subdomain for your app, and we can provide hosting via Google Appengine. If you want to host your app elsewhere, you should discuss with us before submitting your proposal.

Size of this project: large (~350 hours)

Potential Mentors: @U8NWXD, @gp201

Product Clarifier: @seanlip

Technical Clarifier: @U8NWXD

Knowledge/Skills Recommended:

Angular, CSS, HTML, and Typescript for frontend development
Python for backend development

Suggested Milestones:

Milestone 1: Create a new repo for the release dashboard and include setup, update, test and deployment instructions, as well as CI checks that run all the tests and ensure that all code is 100% tested before an update can be merged to develop. The release dashboard should show a table with a paginated list of commits, their release candidates, and their acceptance test statuses.
Milestone 2: For the appropriate release candidates, the release dashboard should have buttons that support deploy-to-prod-server and deploy-to-test-server functionality. These buttons should be correctly access-controlled and should send the appropriate notification emails when clicked.

Dependency on Release Schedule: None.

Proposal notes:

Follow existing Oppia code patterns and app conventions, so that the app is easy for the team to maintain. In particular, for authentication, we suggest using Firebase authentication in a similar way to the main Oppia.org app, rather than rolling out a custom username/password system. You should also take care to avoid any security vulnerabilities (e.g. XSS, CSRF). Following Oppia design patterns and conventions will help here, but whether or not you borrow from Oppia, you should make clear what patterns and conventions you will use, and why they are important. You may find automated security scanning tools like CodeQL helpful, but you should not rely on them to replace your own knowledge.

Your app should be independent of the production Oppia deployment at https://oppia.org. This is because if Oppia is broken, we need to be able to access the release dashboard to fix it.

Deploying your app should be straightforward and reliable.

Most important things for the proposal:

Make a table showing types of notification events received, when they’re triggered, where they’re sent from, what their format is and what the app will do with them.
Check that you’re able to do the following from an App Engine app, and describe how you would do so in detail. As a bonus, show proof of a working prototype for these that someone can experiment with:
- Receive a notification from GitHub
- Send an email to a given address (can follow what Web does with Mailgun)
- Send a request to trigger a GitHub Action.
- Send a request to provision BrowserStack.
- Get current status from BrowserStack.
Discuss how you would handle access control for your app. Provide details on how you would get the membership list of a Google Groups mailing list so that you can handle access accordingly.
Break the project down into clear steps and map these steps to a timeline, showing that your proposed project is feasible in the time allotted.

The dashboard does not need to meet accessibility guidelines.

Useful resources: None

4.3. Developer Workflow Telemetry Dashboard

We have decided that we don't have the capacity to support this project this year.

4.4. Make CI faster

Project Description:

Developers often have to wait multiple hours for continuous integration (CI) checks to finish running on their PRs. This delay slows down development and frustrates developers. This project proposes an acceleration of our CI runs and moving CI checks to the pre-push hooks to flag bugs for developers within 45 minutes. This entails several steps:

Get the pre-push tests (that run on the developer’s local machine) to run in under 5 minutes:
- Audit backend unit tests to see which ones take a long time, and refactor those to avoid network/database/disk-access calls in order to shorten their runtime (while still testing what they need to).
- For long backend unit tests that need to be long because they are creating a lot of data to test scalability, add them to a “scalability” list of tests that doesn’t need to get run during pre-push.
- Run only the lint, MyPy, and typescript checks; karma tests (frontend tests); and backend unit tests that were affected by files changed since the last push.
- (If possible) On pre-push, shorten the install and build step or remove it altogether.
Get the CI checks to run in under 45 minutes wall time (i.e. including parallelization):
- Create a single environment at the start that gets used for all other tests. (In particular we currently seem to be running the “install third party deps” step repeatedly, so it might be good to cache folders like oppia_tools.) We’re hoping to get this done before GSoC, but you should confirm that it’s working.
- Create a build artifact that gets reused in all workflows. (Currently, build artifacts can’t be persisted across workflows, but this GitHub action for uploading to GCS might be helpful. Alternatively, all CI checks could be combined into one workflow of multiple jobs, letting you use GitHub Actions artifacts.)
  - Warning: This has the potential to clash with the project to Dockerize Oppia. To avoid any problems, you should plan to do this early (the Docker project won’t get to CI until later in the summer).
- Run the full versions of all pre-push tests (mentioned above).
  - Run these tests first, and block other tests on these. In other words, if any of the pre-push tests fail, then do not run the other CI checks. This may complicate reaching the goal of 45 minutes wall time, but see if you can figure out a way to do it.
- For long-running tests:
  - If the test is essential, find a way to make it shorter. For example, by mocking expensive calls in backend unit tests.
  - If the test is not essential, remove it from CI and put it in an acceptance layer that only runs on some release-candidate builds (see below).
- (optional) As a stretch goal, see if you can get the CI checks down to under 30 minutes of wall time.
Split off less-important long-running tests into acceptance tests:
- Create a GitHub Action that, at regular time intervals, takes the latest release-candidate build on develop that passes all CI checks, runs the acceptance tests on them. Builds that pass all acceptance tests should have a public, machine-readable indication that they did, and builds that cause an acceptance test failure should result in an email or chat notification to the dev workflow team and the release engineering task force.
To increase the number of CI runners we have to parallelize tests across, avoid duplicate CI runs from taking up resources when multiple pushes are done to a PR in quick succession (see https://docs.github.com/en/actions/using-jobs/using-concurrency).

What's explicitly out of scope:

We want builds that pass acceptance tests to have a machine-readable indication of success so that the Release Dashboard can query this indicator. You are not responsible for creating the release dashboard though.
The pre-push runtime only needs to be 5 mins or less on machines that we have supported installation instructions for on the wiki. In particular, you can assume that developers have at least 8 GB RAM.
You may assume that the build step runs in 5 minutes. We should be able to achieve this once the Angular migration is complete, but you are not responsible for completing the migration.

Size of this project: large (~350 hours)

Potential Mentors: @U8NWXD, @gp201

Product Clarifier: @seanlip

Technical Clarifier: @U8NWXD

Knowledge/Skills Recommended:

Familiarity with GitHub Actions and workflows.
Clear understanding of the current Oppia pre-push and CI pipeline.

Suggested Milestones:

Milestone 1: CI checks run in under 45 minutes. Less important tests are split off into an acceptance layer. Duplicate CI runs are avoided.
Milestone 2: Pre-push checks run in under 5 minutes.

Dependency on Release Schedule: None.

Proposal notes:

Most important things for the proposal:

Benchmark the current process (you can do this using data from existing GitHub Actions runs) and explain where you plan to make improvements and how much the improvements will be. Ideally your estimates of how much the improvements will improve runtime would be based on your own testing, but this is not required. At the end, provide a summary of how long the pre-push, CI and acceptance phases are likely to take once this project is completed, and compare those to how long they are now.
- Note: Do not just use the benchmarking in this project spec. Those benchmarks are very rough, and we just used them to scope out a reasonable project. Your proposal should be more rigorous.
Enumerate the changes you would make to the backend tests and the approximate effect that those are likely to have on runtime.
Show a sample PR for how you would make a slow backend test quicker.
Explain the details of how you plan to separate backend tests into categories and allow configuration of which categories to run. Show a proof-of-concept if possible.
Explain how you plan to get the list of files changed since the last push, and how you plan to run only the lint checks, karma tests and backend unit tests that relate to those files.
(Bonus) Explain any ideas you have for shortening the build process in build.py, with proof-of-concept if possible.
Explain your naming convention for workflow build artifacts and how you plan to upload and download them, with proof-of-concept if possible.
Explain how you would write the “acceptance tests” GitHub Action and how the results of these tests would be persisted/broadcasted.
List which tests you will move to the acceptance layer and explain your reasoning.

We put together a possible re-arrangement of CI checks to get runtime (in wall time) below 45 minutes. You may find it a useful resource for ideas about how to cut CI runtime, but you should not consider it authoritative.

In that worksheet, we assumed a PR would have access to 5 GitHub Actions runners. Here’s the reasoning for how we arrived at that number:

It's pretty typical for us to have ~50 PRs open at once. Let's suppose we automatically cancel past CI runs on a PR once a new commit is pushed and PRs are really active (daily pushes). We generally have 2 bursts of pushes, one when people around UTC-0600 (in the US) are active, and one when people around UTC+0530 (in India) are active. Let’s also assume that each burst of pushes is a few hours long so that a full set of CI checks can run at least twice during the burst. Thus, we can estimate that each PR’s CI checks will run alongside 50/4=12.5 other PRs. With 60 test runners, this gives each PR 4.8, or approximately 5, runners on average.

Useful resources:

https://stackoverflow.com/questions/58457140/dependencies-between-workflows-on-github-actions

4.5. Normalize Usage of Feature Flags

Due to changing availability of mentors, we are no longer able to offer this project.

Files

Google-Summer-of-Code-2023.md

Latest commit

History

Google-Summer-of-Code-2023.md

File metadata and controls

Table of Contents

Contributors

Current Projects

Getting started

FAQs

Dates and Deadlines

Types of work related to Oppia projects

GSoC Proposal Template

Tips for writing a good project plan

What should applicants expect from mentors in a proposal review?

Sample proposals from past years

Selection Criteria

Communication

Oppia's Project Ideas List

Learner and Creator Experience (LaCE) team

Contributor Dashboard team

Data validation team

Developer workflow team

Learner and Creator Experience (LaCE) team

1.1. Implementing the “needs guiding responses” section of the lesson analytics dashboard

1.2. Improving the lesson creation experience

1.3. Serial chapter launch

1.4. Learner Dashboard Redesign

1.5. Improvements to Math Interactions

1.6. Improve Accessibility

1.7. User feedback reporting UI on Web

Contributor Dashboard team

2.1. Contributor Dashboard Admin Stats Table

2.2. Prioritized Translation Languages and Auto-Translations

2.3. Improvements for translation reviewer experience

Data validation team

3.1. Fix validation errors

Developer workflow team

4.1. Dockerize Oppia

4.2. Developer Workflow Release Dashboard

4.3. Developer Workflow Telemetry Dashboard

4.4. Make CI faster

4.5. Normalize Usage of Feature Flags