# Application process for the Community Development Lab

Published on March 23, 2015 by
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The Community and Development Lab is a traditional yearly ROSEdu project where we teach students how to start contributing to open source software. This year we had 117 applicants and had to select only 19 of them. To do this, we gave them an algorithms problem to filter 60 potential candidates which were invited to an interview.

In the Community and Development Lab students have the chance to participate on 9 weekly sessions during which they can learn real industry skills. Every week, there is a 2 hour presentation about different topics, like Linux, Git, Python, OOP, Raspberry Pi, and then for another 2 hours they stay with an assigned mentor and write patches for open source projects.

To select the best students, we gave the students to solve an ACM style algorithms problem on the Infoarena judge. They had to code their solution in C, C++ or Java, submit it online and the judge would run it over 10 tests, checking the output and measuring the time and memory of their implementation. Most of the students who tried to solve this problem were in their 1st or 2nd undergraduate years at Computer Science or Computer Engineering in Bucharest.

## Problem Statement

You can read the Romanian version on Infoarena

Ada, Calin and Andrei got bored of learning algorithms at their University and want to learn more practical stuff. To do this, they have decided to apply at ROSEdu CDL. However, the organisers cannot separate the applicants, so they decided to give an algorithms problem for them to solve. Luckily, you don’t need lots of knowledge about time complexities.

You are given a JSON file that contains a list of objects. Every object contains a list of entries of key-value type, where the value can be a string or an integer. You have to transform it into a CSV.

### Restrictions

• Every JSON line will contain maximum 1,024 characters.
• You have maximum 0.1s of time for every test on a dual core 2.93GHz
• You have maximum 4,906 KB of memory for each test

Example input:

[{
"id": 1,
"language": "Ruby",
"usage": "Mainly by hipsters.",
"power": 4
}, {
"id": 2,
"language": "Python",
"usage": "Computer scientists and some wannabe hipsters.",
"power": 2
}, {
"id": 3,
"language": "C++",
"usage": "Hardcore people who love dangling pointers.",
"power": 100
}, {
"id": 4,
"usage": "A lonely dude in Massachussets.",
"power": 999999
}]

Example output:

id,language,usage,power,
1,Ruby,Mainly by hipsters.,4,
2,Python,Computer scientists and some wannabe hipsters.,2,
3,C++,Hardcore people who love dangling pointers.,100,
4,Haskell,A lonely dude in Massachusetts.,999999,

However, since we want to simulate a real life problem better, the JSON file won’t be formatted with the same whitespace. But, we guarantee it will be correct.

[ { "name": "Ruby on Rails", "commits": 49507, "contributors": 429,
"last commit" : "an hour ago" }, {"name": "jQuery", "commits":  5745,
"contributors" : 213, "last commit":  "4 days ago" }, {"name": "React",
"commits" : 3557,  "contributors": 288, "last commit": "5 hours ago"} ]
name,commits,contributors,last commit,
Ruby on Rails,49507,429,an hour ago,
jQuery,5745,213,4 days ago,
React,3557,288,5 hours ago,

We also guarantee that:

• there are no nested objects
• a string surrounded by quotes will only contain alphanumeric characters
• every object has the same keys
• the keys will be in the same order

## Solutions

I originally thought the solution of this problem to be a finite-state machine. You have just a pointer, go through each character one by one, and you either decide to print it, print a comma or do nothing. You first do this to print the first row of the CSV with the columns, reset the pointer to the top of the file and traverse it again by printing the values. My solution is here and Ada Solcan helped me with a more beautiful version here.

For generating the tests, I hacked a Python script that generated a JSON. Three tests were special because they had random whitespace. One test was a corner case where there was only one object with lots of keys, and another one had lots of objects with a single key.

The problem gathered 2812 submissions from 158 students.

## Statistics about the online submissions

I was expecting more people to fail the problem, but over 50% of the scores are perfect.

The average number of submissions for a perfect problem was 11. We had a participant who submitted 124 times.

The most failed test was number 8. What’s special about it is that it contains a single object, and most of the students assume that after the first object ending curly brace, they will have a comma.

A reason why the last 3 tests have the most failing submissions is that they are really big and most of the students preferred to use getchar for I/O. Doing that, you overwhelm the operating system with lots of calls. A better approach is to use a buffer.

Also, I’ve counted the time students spent solving the problem. The average time for any student was 6 hours and 15 minutes, and the average time for a student who successfully passed all the tests was 3 hours and 45 minutes. To estimate the time spent on solving the problem, I added an hour to the solving time for the first submissions and if the difference between 2 submissions was more than 4 hours, I also added one hour for his next submission. In total, students spent 40 days of time trying to get all the tests passed.

## Hands-on interviews

After we eliminated the students who didn’t have 100 points at the problem and the students who didn’t complete anything on the “What project are you most proud of?” in their application form, only 60 students remained. We sent a call-to-action to the ROSEdu community and the mentors, and 8 people replied that they could help us with the interviews.

Each interview took 30 minutes. For the first part we asked them questions about the non-technical applications, then asked the applicant to talk about how he approached the problem and finally we asked him the dreaded technical questions.

## Technical questions

We would first ask the student to present his solution. Then, we would start asking him what would happen if we modified the problem statement and he would start to have special characters inside the keys, like parentheses or colons. Then we would ask him to tell us how easily it would have been to modify the source code and support those edge cases.

From what I’ve observed, the shorter and cleaner the student’s solution was, the easier for him was to give us a version adapted to the new requirements.

After these warming questions, we would ask him the important one: what would happen if the keys of the objects were not in the same order. For example

[{
"id": 1,
"language": "Ruby",
"usage": "Mainly by hipsters.",
"power": 4
}, {
"usage": "Computer scientists and some wannabe hipsters.",
"language": "Python",
"id": 2,
"power": 2
}]

All the complexities are assuming a comparison of strings is done in O(1).

I took about 20 interviews. Almost every student would find the O(N^2) algorithm. The solution would be to print the keys of the first object, read the second object, and for every key search it naively in the first object.

From here, only half of the students would get a better solution alone. The first hint I gave was to try and see if having the keys in a certain order might help. Some of them caught the idea, sorted the keys and said that they would now use binary search to find the position of the keys in O(N*log(N)).

Then I might ask them if they know a data structure where you could do lookups faster than O(log(n)). Most of them knew about hashes and gave the correct complexity solution. However, when I asked them how does a hash work, they raised their shoulders and had no idea. I then explained them that a simple implementation of a hash is a long array with a smart hash function.

I must say that there were some smart students that knew what hashes were, how they worked behind the scenes and they applied them to this problem naturally without any help. For these students I asked them why would you sometimes prefer a binary search tree rather than a hash. The answer is that a BST uses lower memory. Another topic of discussion would be on how would you implement a hash function for this problem. Two students knew that using a base of 26 for the characters of the keys and then doing modulo of a big prime number would be a simple and elegant solution.

All in all, I was surprised by the lack of how students grasped the concept of a hash and applied it in the problem, but had some interesting discussions with some.

## Acknowledgements

• Ada Solcan, Calin Cruceru and Andrei Dinu for organising the whole CDL
• Gabriel Ivănică, Alexandru Răzvan Căciulescu, Călin Cruceru, Mihai Brănescu, Nicu Bădescu, Vlad Fulgeanu, Dan Șerban, Iulian Radu and the Wyliodrin team for being mentors, teaching voluntarily the students accepted how to contribute to the open source world
• infoarena because they let us host the problem