MS Computer Science (MSCS) program at UPLB (Part 1)

(Last update: 19 January 2024)

If you are considering applying to the Master's Degree in Computer Science program at UPLB, here are some things you might want to know based on my experience and observations.

Who should take this degree program?

"The Master of Science in Computer Science (MSCS) degree program addresses the need for advanced formal training of professional leaders in Computer Science. Candidates are expected to acquire a broad knowledge of the discipline and be able to undertake critical inquiry and independent research."

This program is ideal for those who want to become professors or researchers. The MSCS program can also be treated as a 'bridge' program if you want to get into a PhD program. If you are an industry practitioner, you might want to take the Master of Information Technology(MIT) program (non-thesis) instead. As much as possible, you should have good grades during undergrad to increase your chances of getting accepted and completing the regular program. 

What prerequisite knowledge is required? 

This program requires that you've completed a BSCS/BSIT/BSIS program from a 'recognized' HEI. Here are some of the courses you should have good grades in (2.0 or better).

* Discrete Mathematics

* Statistics

* Data Structures and Algorithms

* Programming Languages

* Databases

* Operating Systems

* Computer Networks

* Automata and Language Theory

You should also be proficient in programming.  Web programming is a must if you plan to minor in IT. 

Being proficient in Linux and Python is a plus. 

If you are interested to join our group, I prefer students who have good background in machine  organization/architecture and low-level programming (assembly and C), operating systems admin/internals, and computer networks.

Program requirements

The program requires at least 34 units to complete, divided into the following.

* Core Courses (12 units) - required

- Programming Languages, Advanced Computer Systems, Advanced Data Structures and Algorithms, Computational Complexity Theory

* Major Courses (6 units) - select two(2) from the following courses

- Databases,  Automata and Language Theory, Scientific Computing, Digital Image Processing, Management Information Systems, Parallel Processing, Special Topics

* Minor Courses (9 units) - select three(3) courses from one of the following graduate programs

- Mathematics, Statistics, Economics, Agriculture, Forestry, Information Technology, Environmental Science

* Seminar (1 unit)

* MS Thesis (6 units) 

In addition to passing the courses above (with a grade of 2.0 or higher), you also need to pass the Comprehensive Exam. 

Who are the professors currently teaching the graduate CS/IT courses?

(as of Academic Year 2023-2024)

* Patrick Albacea (Programming Languages, Operating Systems)

* Fermin Roberto G. Lapitan (Web App Dev)

* Joseph Anthony Hermocilla (Cybersecurity, Modern Distributed Systems)

* Concepcion Khan (Information Systems, Knowledge Management)

* Val Randolf Madrid (AI/ML, Machine Vision)

* Danilo Mercado (Enterprise Systems, Cybersecurity)

* Jaderick Pabico (AI/ML, Parallel Programming)

* Reginald Recario (Databases)

* Jaime Samaniego (Data Structures, Algorithms, Computational Complexity Theory, Automata)

Part-time or full-time mode?

If your home institution, funding institution, or employer will allow it, choose full-time. The advantage of full-time mode is that you can focus on the coursework and still have plenty of time to research.

Choosing your adviser/supervisor

Use your first semester, or even before applying to the program, to scout for a suitable adviser. Ask other students. Visit research group websites of professors. Check the publications of professors. Attend talks. Talk directly to a possible adviser via email or in person. 

Note that you will be assigned a temporary registration adviser upon admission to handle enrolment/registration matters. If a professor has accepted you as advisee even before admission, then he/she will automatically be your registration adviser.

Choosing your adviser is a tricky task. The following are some guidelines on how to select an adviser (based on my opinion).

* Choose an adviser who 'specializes' in the area that you are interested in.

You want an adviser who can guide you in your research. Some advisers are generalists, but choosing a specialist is best.

* Choose an adviser who is 'easy to work with.' 

Some advisers can be challenging to work with. Some are too intimidating and too demanding with unreasonable expectations. Some are not even available for regular consultations.  

* Choose an adviser who has connections outside of ICS or UPLB.

If your adviser is active and visible in the research/scientific community, it will enlarge your network and open up opportunities for collaboration. Some advisers are also involved in externally-funded projects, which can be a good source of a thesis topic.

* Choose an adviser who is ethical.

Your reputation will also be affected if your adviser is involved in unethical research/publication practices.

You also need to select 2-3 professors who will be part your Guidance Committee, with one member from your chosen minor field.

Choosing your minor

Most students choose Information Technology(IT) as their minor. However, it is actually up to you, based on the research area that you want to pursue. For example, a Forestry, Environmental Science, or Economics minor is best if you are interested in Modeling and Simulation or Machine Vision. A Statistics or Mathematics minor will be excellent for a Data Science or AI/ML track. 

How are the classes conducted?

Lectures and assignments make up most of the classes. Some IT courses have a separate laboratory class. Unlike in undergrad, reading research papers and writing reviews are incorporated into the class activities. I often hear current students complain about too much readings in their classes. Do not apply to this program if you do not like reading and reviewing research papers. Individual/group programming projects and reporting are required in some courses. A midterm exam and a final exam are also used for assessment. Remember that you need to get a grade of 2.0 or higher. Unlike in undergrad, you must be motivated to study independently and not depend on the professor. Some professors don't give lectures at all and only assign readings and programming assignments.

What are other skills you need to develop?

You will need to develop the following:

* Oral and written communication skills, especially scientific/technical writing

* Critical reading of  research papers and writing reviews - one way to do this is by maintaining a blog 

* Reporting and presentation skills

* Learning new tech stacks and programming languages

* LaTeX 

Another important skill that you need to develop is networking or in general socialization. In addition to your adviser, you need a kind of support group where you can bounce off your ideas and not feel alone.

Comprehensive Exam

Once you've completed the coursework, you will take the Comprehensive Exam. The exam will cover the following areas: Theory, Systems(my specialization), and Applications. Questions will come from professors who taught or specialize in the particular area. 

Your first semester

You should spend your first semester to familiarize yourself to the graduate school environment. You will take at least two core courses during your first semester of first year: Advanced Computer Systems  (CMSC 215) and Advanced Data Structures and Algorithms (CMSC 244). If you are a full time student, you can take additional courses (up to 12 units). As mentioned above, scout for a possible adviser during your first semester. Also choose your minor and look for Guidance Committee members. I recommend that you attend a research methods class even if it is not required to develop your research skills. 

How long will it take to finish?

It usually takes 3-4 years to complete the program, especially for part-time students. Sometimes it will take longer because of the thesis (I will have a separate post to discuss it). That is why I recommend the full-time mode. The UPLB Graduate School has a proposed 'optimistic' timeline below. This timeline may be possible in other disciplines. However, this is quite difficult to achieve in MSCS.

Facilities and resources for students

We have a shared GS Room where graduate students can stay and work. There are iMacs available, but bringing your own laptop/device is better. Some professors have their own lab space where you can work if they are your adviser. Our main graduate teaching laboratory is PC Lab 1, with 16 Ubuntu boxes. We have a few servers for running compute-intensive tasks. The UPLB Main Library has access to a wide collection of research resources, including those published by ACM and IEEE. Technical reports from ICS are available at Peak-One.

How to fund your study?

The tuition fee is currently PHP 1000.00/unit. For the tuition fee alone, you will need at least PHP 34,000.00! If you have enough money, you can fund your study on your own. You can also avail of financial assistance.   

Additional information 

* The GS Policies, Rules & Regulations Document: https://gs.uplb.edu.ph/gs-policies-rules-regulations/

* GS Faculty Guide: https://www.uplbgraduateschool.org/img/resources/Faculty%20Guide%20(07272018)%20(1).pdf

* Student Handbook: https://www.uplbgraduateschool.org/img/resources/Student%20Handbook%20(07272018)%20(2).pdf 

* Tuition and other fees: https://gs.uplb.edu.ph/admission/fees/

* Financial Assistance: https://gs.uplb.edu.ph/current-students/financial-assistance/ 

How to apply?

Now that you know something about the MSCS program, visit https://gs.uplb.edu.ph/admission/how-to-apply/

Closing Thoughts

Be sure that you really need/want the MSCS degree!!  If you did not finish your undergrad from UP, you might be 'shocked' by the academic environment here.  You need to spend some time adjusting and focusing.  Your classmates will probably be instructors from ICS, and they will be really good in your classes.  Do not be intimidated by them.  Just do your best and excel.  Most of them are friendly and fun to work with in group projects.  Choose your major adviser and Guidance Committee wisely.  In Part 2, I will talk about the thesis, research, and publications.

(Photo by Unseen Studio on Unsplash)

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How to succeed in group programming projects?

Group programming projects will test a student's technical skills and ability to work in a team. This post will discuss how to succeed in group programming projects. 

The Answer: Choose an excellent group leader!

In group projects, the role of the group leader is very important. Although technical expertise is a desired quality for a group leader, leadership skills, project management skills, and communication skills are more important to ensure the success of the group project. (I am speaking from experience here because I've always been selected as the group leader when I was an undergrad :) ). 

Common issues in group projects

* Technical skill level gap - some members are already good in programming, others are not

* Communication - team members have different expectations(one member wants a 1.0 while others want 1.25 only), work habits(night owls vs. early birds), etc.
* Schedule - cannot find a common time to meet and work on the project

* Code management - did not use git (When I was in college there was no git. I maintain the authoritative copy of our project source code on floppy disks :) )

* Procrastination - can cause delays, some group members are not working on tasks assigned to them (though everyone procrastinates)

Role of the group leader

In general, the role of the group leader is to handle the issues mentioned above.

* Set goals and processes - provide a sense of direction for the successful completion of the project, includes setting up the project code repository and project management tools
* Facilitate communication - identify channels of communication, set meetings, follow up, etc.  
* Assign tasks - based on the abilities of the members, members should be honest about their technical skill level
* Monitor progress - updates from group members, can be done through tools
* Provide assistance - technical, etc.  
* Manage conflicts - need to make decisions at some point

* Seek help(of prof) if needed

* Trust and respect the group members 

* Maintain a work log

Character of the group leader

A group member should not accept the nomination as group leader if he/she does not possess these qualities.

* Effective communicator 
* Collaborative - group leader should ensure that every member of the team can contribute, no matter how small the contribution is
* Adaptable - be able to make adjustments based on circumstances
* Positive and cool attitude 
* Accountable - and responsible

* Empathetic - "not everyone is as good(or bad) as you"

* Organized

* Accept the fact that a low project grade may be given because some group members did not deliver

* Accept the fact that a group member may be more technically skilled than he/she is - ask for suggestions, set aside the "ego" associated with being the group leader

* Must not expect that everyone in the group will be able to contribute 'equally' with the same level of 'complexity' of output 

 

Role of the group member

Of course without the contribution of group members the project will not move forward.  (May not always be true because a highly technical, grade-conscious, and introvert group leader may 'make buhat' the group but secretly fail everyone else in the team in the peer eval :) ). 

* Trust and respect the group leader - the group leader is doing a lot more stuff than group members

* Accept tasks that he/she is willing to commit to

* Commit to work on the assigned tasks

* Communicate with the group leader and other group members 
* Seek help(of prof) if needed

* Maintain a work log

* Accept the fact that a low project grade may be given because the group leader and other members did not deliver

* Accept the fact that the group leader and other members may not be technically skilled than he/she is - make suggestions, volunteer to work on more complex tasks

* Not be a freeloader

Appendix: Example work log

(Photo by Annie Spratt on Unsplash)

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UPLB Student Registration Systems: 1996-2022

(Please note that this post is just based on my recollection of events. Here's my 2012 post about UPLB student registration.)

I have been part of UPLB for more than 20 years already, both as a student and as a faculty member. I have witnessed two main modes of the student enrollment (aka registration), manual and automated. In this post I'll try to discuss the different systems I observed and experienced. I will not be specific about dates since I am not good with it. Let's get started.

Simply put, the registration process enables students to select the subjects they will take for the incoming semester. The official document that contains this is the Form 5. One interesting aspect of the registration process in UPLB is that there is no guarantee that a student will be able to get all the subjects he/she needs for the incoming semester. This is due to a lot of factors, e.g. limited number of slots per section, schedule conflict with other subjects, and seasonal subjects.  

When I was a student in the mid '90s, there was a hybrid enrollment process. Students submit a Write-In paper form that contains the subjects and sections they want to enroll for the upcoming semester. The Write-In form will be encoded to the computer and used as input to a FORTRAN program called REGIST, which was developed by Dr. Ricolindo L. Carino of the Institute of Computer Science (ICS).  To my knowledge, this process was in place until I graduated in 2002.

After graduation, I became an instructor in ICS where my colleague Rodolfo N. Duldulao Jr. (Duldz) started developing an in-house system to track enlistment to Computer Science subjects. The system used the Apache-MySQL-PHP tech stack for web apps. This in-house system became popular and was extended to provide an online mechanism for the Write-In process in the entire UPLB. This online system became SystemOne (S1). More features were eventually added to S1 which was deployed during registration period. Note that the initial course assignments in S1 were still generated by REGIST. 

REGIST attempts to "solve"  course/student assignment (or student sectioning problem as I formulated it in my MS thesis). It became an academic research topic for a few MSCS students. Approaches such as Tabu Search, Ant Colony Optimzation, Simulated Annealing, Genetic Algorithms, and Multiagent Systems (my study) were tried but they never really replaced REGIST.

S1 evolved to become the main system for online Write-In and eventually for enlistment of courses to serve the entire UPLB students. After Duldz left UPLB, another colleague, Rommel V. Bulalacao (Bulacs), took over the development and operations of S1. Bulacs was a volunteer developer of S1 while he was still a student. REGIST however remained to be the main system for automagically assigning students to classes. Several improvements were also made by Bulacs for S1v2. Dr. Carino still provided support, though limited, for REGIST through the Registrar's office. I also coauthored a short paper which identified the performance bottleneck in S1v2 prompting its rewrite to a more modern tech stack, Node.js. This rewritten version (S1v3) however was short-lived. 

When Alfredo E. Pascual became UP president, he initiated the e-UP program. There was a strong push to deploy a unified enterprise system to support all university operations, including registration. This led to the deployment of the Student Academic Information System (SAIS) in UPLB. Key persons in SAIS deployment in UPLB were Dr. Jaime L. Caro(ITDC) and Dr. Myrna Carandang(UPLB Registrar). SAIS is still the current system being managed and operated by ITDC with a local team in UPLB housed in the Registrar's Office. SAIS is more of a "shopping cart" application where students "add to cart" the subjects they want to enlist. There is no global course demand prediction as with the case of REGIST. This resulted to a lot of problems. One of which is that regular students were unable to enlist in subjects because there is no "hard constraint" to prioritize them. Another is that departments were not able to properly predict course demand to adjust their course offerings. 

I also recall a system being deployed in Graduate School by a team led by Mr. Li Bolanos. I don't have the details  about the system though but I think it was written using PHP and MySQL. 

More recently, under UPLB Chancellor Dr. Jose Camacho Jr., an ad hoc committee was formed to oversee the development and implementation of the UPLB DX Academic Management Information System to replace SAIS. The committee is chaired by my colleague who is also the University Registrar, Prof. Margarita Carmen S. Paterno (Marge). Other colleagues involved are Prof. Danilo J. Mercado (ITC Director), Prof. Reginald Neil Recario, and Prof. Monina Carandang. Mr. Li Bolanos is also a part of this team. A version of DX AMIS for Teacher's Prerogative (using PHP-Postgres on VPS) was deployed during the First Semester AY 2022-2023. However, SAIS is still the main app for registration.

All deployed systems, from S1 to DX AMIS, encountered availability problems during peak hours of the registration period due to large amount of network requests.

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Thoughts on Learning and My Teaching Philosophy

I've been teaching in UPLB since 2002 (that's >20 years already!). I haven't really put into writing my thoughts about learning and my teaching philosophy.  Here are some items (which will be updated from time to time because things happen and change): 

• Since this is UPLB, I assume that my students are really smart (but some will be "slow"). Of course, some students will be smarter than me. This is one reason I like teaching here.
• Since I teach Systems subjects, I want my students to work on hands-on activities and experiment (build, break, and rebuild stuff).
• I don't believe in "learning styles". I believe that students can learn any topic (no matter what their learning styles are) if they really give time and effort to learn the topic. They can always ask for help on difficult topics. Even if I am a boring lecturer, for sure they will learn something.
• My role is just a facilitator of learning (and possibly a source of inspiration), not the source of knowledge. Students are free to explore other knowledge sources outside the syllabus and the classroom. Using AI Tools is welcome in my classes.
• I don't tolerate academic dishonesty. It is better for students to fail (then retake the subject) than to cheat in graded activities such as exams. However, I don't police students on this matter. For me policing is a waste of my time. I have  high respect for students who fail because they did not resort to academic dishonesty. Also, a student can just drop the course if he/she is failing rather than resort to academic dishonesty. 
• High grades matter only if students will apply to grad school or apply for a teaching position after they graduate. Students should aim for the "learning" and "mastery" as well as skills development. High grades will just be an end result in the pursuit of "learning" and "mastery". 
• Some students are "grade conscious" (or GC) which means they want/beg for a grade of 1.0! If they want high grades, sure I can give it to them as long as they turn in excellent work. This is the reason I give bonus points, though some students don't avail of these bonus points. 
• Feedback is not just the score students get from graded activities (wrongly termed as "learning assessment"). If students code worked on the given test cases, that is already feedback. If a student wants feedback, he/she needs to talk to me directly during class and consultation hours. The only way I can help "slow" students is if they intentionally ask for my help. Otherwise they are on their own. 
• Not all students currently taking BSCS are really interested in computing(or a Nerd) . I am biased towards students who are passionate about computing. Thus course materials, difficulty, and delivery are more geared towards challenging these passionate students to the best of my abilities.
• I want my classes to be "world class", thus I try to adhere to the ACM curriculum recommendations when creating and delivering course content. I also consult course websites of other top universities and incorporate topics and approaches in my syllabus.
• I try to focus on teaching the fundamentals. However, computing is a rapidly evolving field so I try to teach the state of the art given the resource constraints and bureaucracy.
• Textbooks are important in my classes. I prefer to use free or open source textbooks. I give paper readings from time to time to encourage students to do research.
• I encourage students to ask questions, even the simplest or 'stupidest' questions. 
• I prefer to create videos that are more than 15 minutes. TL;DR/TL;DW is not for me and should not be for my students. I don't want my students to take 'shortcuts'.
• I want my students to do great work without desiring for my validation. 

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DevStack on Ubuntu 20.04

I need a small IaaS cloud infra for my CMSC291: Modern Distributed Systems class this semester so I decided to set up an OpenStack instance on one of SRG's servers running Ubuntu 20.04. I have used OpenStack in the past so I'm quite comfortable using it.

What is DevStack?

"DevStack is a series of extensible scripts used to quickly bring up a complete OpenStack environment based on the latest versions of everything from git master. It is used interactively as a development environment and as the basis for much of the OpenStack project’s functional testing."

                                                                                    - https://docs.openstack.org/devstack/latest/

[1] I thought the process will be straightforward but unfortunately minor tweaks were needed. Below is the configuration of the host.  

[2] This is the commit hash that worked for me, make sure to checkout this particular commit : d9e2d10d28ebc70129ed90ac9afe11591e7bb7d3

[3] Get the IP address of the host (using ifconfig) and export it as HOST_IP environment variable. Let's say the IP address is 192.168.3.100.

        $export HOST_IP=192.168.3.100

[4] Prepare the local.conf file as described in the doc.

[5] Edit lib/neutron_plugins/ovn_agent. 

Change OVS_RUNDIR=$OVS_PREFIX/var/run/openvswitch 

to OVS_RUNDIR=$OVS_PREFIX/var/run/ovn

[6] Unstack and Clean.

        $sudo apt install neutron-metadata-agent

    $sudo apt install neutron-openvswitch-agent

    $sudo pip install uwsgi

    $./unstack.sh

    $./clean.sh

    

[7] A few directories need to be removed as well as do some other stuff:

    $sudo rm /var/run/ovn/openvswitch
   $sudo /usr/share/openvswitch/scripts/ovs-ctl restart

   

    edit tools/dbcounter/dbcounter.py

[8] Stack. This may take a while so grab a cup of coffee.

         $./unstack.sh

    $sudo rm -fr /var/run/ovn

    $./stack.sh
        

A successful installation after ~12 minutes!

[9] Launch an instance.

[10] TODO: Configure Floating IP addresses and add glance images.

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YouTube channels/playlists for systems and cybersecurity topics

Here are some good materials available on YouTube for free.

(Last update: 2022-04-20)

Computer Systems and Operating Systems

• Operating Systems by Mythili Vutukuru
• ACM SIGOPS
• USENIX
• Introduction to Computer Systems at CMU
• Digital Design and Computer Architecture by Onur Mutlu

Computer Networks, Distributed Systems, and Cloud Computing

• Distributed Systems by Lindsey Kuper
• Distributed Systems at MIT 
• Virtualization and Cloud Computing by Mythili Vutukuru
• Distributed Systems Reading Group
• Distribute My System
• Jim Kurose's Networking Videos
• The Networking Channel

Databases

• CMU Database Group 

Cybersecurity

• PWN College
• HackerSploit
• Sam Bowne
• The Cyber Mentor
• John Hammond
• LiveOverflow
• Introduction to Cryptography by Christof Paar
• Solutions to Web Security Academy Labs by Machael Sommer
• Open Analysis Live 
• IppSec
• GynvaelEN

 

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Humans of Computer Systems

Professor Murat  has an interesting section in his blog called the Humans of Computer Systems. I've been thinking about documenting my own "history in computing/systems" so I decided to answer some of the questions in HCS.

Programming

How did you learn to program?

I first learned to program using programmable calculators which I borrowed from my rich high school classmates. I was amazed how using variables saves time when computing some formula. Some of my classmates even have graphing calculators. I usually borrow their calculator and the manual overnight to try it out. I then learned BASIC on my own when my father brought home an IBM PS/2 laptop. I learned other programming languages in school. 

Tell us about the most interesting/significant piece of code you wrote.

When I was in college and taking an assembly language programming course, I wrote a text editor in C, which I called ASMEdit.  It allows me to assemble and link inside the editor. For me, this was an interesting project since I learned how to use pointers to functions to implement the menu system. I also learned to call external programs, TASM.EXE and TLINK.EXE, inside another program. I also implemented syntax coloring for the assembly instructions. This project was developed for the MS-DOS operating system.

Who did you learn most from about computer systems?

I learned about computer systems in my undergraduate OS class, mostly by reading the dinosaur book by Silberschatz et. al. It was in this class that was able to use a Unix OS called Solaris running on Sun hardware. My undergraduate SP/Thesis adviser was a systems and networks guy so I also learned a lot from him. I even learned a lot more about systems when I switched to linux desktop starting with Red Hat 7.3. 

Who is the greatest programmer you met, and what is impressive about them?

Some of my college classmates were really good programmers. They can easily implement advanced data structures and algorithms, especially graph and network algorithms. There was no Stack Overflow then.

What is the best code you have seen?

Over time, I realized that there is actually no best code. I do admire readable and maintainable code. OS kernel source code is quite messy.

What do you believe are the most important skills to be successful in your field?

Desire to learn new things. Oral and written communication. Working in a team. Navigating the academic politics.

What quality or ability do you value most in a computer systems person?

The desire to learn and experiment or tinker with various things. The ability to "see" the big picture at the same time can work on the specifics. Courage to break things.

Personal

Which of your work/code/accomplishments are you most proud of?

I am proud that I was able to get tenure at the university. This gave me the freedom to work on various areas in computer systems that interest me without worrying too much about job security despite the low pay. The ICS-OS paper actually gave me tenure. I enjoyed working on it and using it in my classes.

What comes to you easy that others find hard? What are your superpowers?

Understanding systems. Connecting/integrating things together.

What was a blessing in disguise for you? What seemed like a failure at the time but led to something better later for you?

I was not accepted in the private company that I applied to after graduation. My rejection in that company led me to apply as an Instructor in the university since I also want to pursue graduate studies. 

What do you feel most grateful for?

I feel grateful for everything I have right now. 

What does your perfect day look like?

Learning something new. Helping some people. Exercising and playing sports.

What made you most happy in the last year?

I was able to survive despite the pandemic. Though anxiety kicks in from time to time.

Work

What was your biggest mess up? What was the aftermath?

Some colleagues were pissed when they lost internet access because my private cloud setup has an exposed DHCP server which assigned IP addresses to their machines. We were able to isolate and resolve the problem but it was already late in the afternoon.

What was your most interesting/surprising or disappointing interaction at work?

I need to babysit the son of my colleague on a weekend because he needs to argue/discuss with another colleague about the "draconian" network access filtering.

What do you like most about your job/profession?

The freedom to tinker. The opportunity to share what I know. The chance to mentor and help others. Working with smart people. Playing the publications game. Navigating academic politics.

What would be the single change that would improve your work environment most?

Improving the research culture. Most of my colleagues are great teachers but they disregard the research aspect of the profession. CS is a fast-changing field. We need to keep up with the advances.

Technical

What do you think are the hardest questions in your field?

System reliability and performance. Ethics. Should we build this system because we can?  Is there one operating system to rule them all?

What are you most disappointed about the state-of-the-art in your field?

Sometimes the state of the art is just an incremental step or just scaling up. 

What are the topics that you wish received more attention? What do you think is a promising future direction in your field?

System reliability and performance. Ethics. 

What is your favorite computer systems paper? Why?

*XEN and the Art of Virtualization *A view of cloud computing *MapReduce: Simplified Data Processing on Large Clusters

I reread these papers from time to time.

Story

Is there an interesting story you like to tell us?

Yes.

Tell us your story.

I wrote an EXE non-overwriting computer virus bundled with ASMEdit I described above. My classmates and instructor who copied the program had no idea of the presence of the virus. The virus just replicates though, there is no destructive payload. AV then were signature-based so they never detected the virus I wrote.

Rant your heart out.

We are in a research university. Why are we not reading at least one research paper per week? :)

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Experiences in remote learning

Last semester was my first experience in remote teaching. Class preparation was quite different compared to when there was no COVID-19. I described the technical aspects of my preparation in a previous post. 

The semester started well and everyone is excited and hopeful. The course staff was able to release the revised course guide, videos, and other materials early in the semester. Communication with students was done using Slack and Zoom. Exercise submission was accomplished using GitHub and Google Classroom. Video materials were uploaded to YouTube. (You can check out my playlists).

Things got problematic in the middle of the semester. Typhoons started coming, internet connectivity became unstable, and personal problems arise. It was hard for us and the students to focus and hold synchronous sessions. 

We originally planned to give synchronous exams via Google Forms. Unfortunately, some students were badly affected by the typhoons so we decided to remove the lecture exam requirement. We gave the weight to the laboratory exercises which became the basis of the grades. We also relaxed the due dates of the submission of laboratory exercises so that students will still be able to submit at a later date. Interestingly, the administration released a "no fail" policy.

I am happy that most of the students were able to submit their exercises and get high grades. However, it is quite hard to assess whether they really learned from the courses and they did their tasks with integrity.

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Virtual international academic conferences and workshops

A lot of major academic conferences in computing are being held online/virtual these days. The conferences and workshops I was able to attend so far include the following:

• ACM SIGMETRICS 2020
• ACM HPDC 2020
• SEED Workshop
  
• EuroSys 2021
• CHEOPS Workshop 
• HotStorage 2021
• SIGCOMM 2021

These conferences waived the registration fees this year. I hope to add more to this list.

If you are interested, here is a list of upcoming conferences from various professional organizations:

• https://www.acm.org/conferences
• https://www.usenix.org/conferences
• https://www.computer.org/conferences/calendar

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On remote learning/teaching

Remote learning poses some new challenges to students and instructors. As an instructor, the question that I always ask is "How can I effectively and efficiently deliver my courses to students?" I've been using technologies in teaching already   so it is a little bit easier for me to transition to remote learning. The challenge I think is in the assessment and enforcing academic honesty. 

Coming up with the course guide was the first step.  It contains the "outline" for the semester with topics, learning outcomes, and laboratory activities specified per week. Materials such as video lectures will be prerecorded or delivered live and uploaded. Exams will be delivered online, multiple choice type. Additional materials such as slides and handouts will be made available for download also. Communications will be done through email and messaging tools.

Thus, this semester the following tools occupy my screen most of the time:

• Google Classroom - general class housekeeping
  
• Github/Github Classroom - lab/programming activities
  
• OBS Studio - recording/streaming lectures
  
• Youtube - storage and streaming of lectures
  
• Zoom - video conferencing
  
• Shotcut - video editing
  
• Veikk A30 Tablet - for use in whiteboard app
• Openboard - whiteboard app
  
• Kahoot - quiz engine
  
• G Suite - documents, presentations, spreadsheets, storage, calendar
  
• Slack - messaging/collaboration
• Gmail - email

 

 

Green screen setup

 

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A review of my CMSC 131 class offering

Last semester I taught, for the first time, the Introduction to Computer Organization and Machine Level Programming course for undergrads. Traditionally this course mainly teaches students x86 (32-bit) assembly language programming in an Ubuntu environment using NASM. I decided to "upgrade" the course by directing the course towards systems programming and introducing x86-64 assembly language. My main reason for the upgrade is to prepare the students for their Operating Systems class which they will take later and which I also teach. In order to achieve this goal, I needed textbooks to guide me which led me to use the following:

• [CS:APP2e]: Randal E. Bryant and David R. O'Hallaron (2011). Computer Systems: A Programmer's Perspective (2nd ed.).Prentice Hall.(Video Lectures)
• [ALPU]: Ed Jorgensen (2019).x86-64 Assembly Language Programming with Ubuntu.Creative Commons.

CS:APP was created by professors from CMU and is widely used in many top universities. I used the slides provided by the book. But in my lectures, I have several open terminals to demonstrate the actual operation of the codes. ALPU is a good book also with simple exercises at the end of each chapter.

The topics (based on the CS:APP2e contents) I was able to cover in the lecture are the following:

• A tour of computer systems
• Representing and manipulating information
• Machine-level representation of programs
• Memory hierarchy
• Linking

In the lab, I was able to cover most of the chapters in ALPU, excluding DDD, Macros, Stack Buffer Overflow, I/O Buffering, Floating Point, and Parallel Processing.

I introduced GDB in the lab to help students debug their programs. I also used GitHub Classroom for distributing boilerplate code and code submission.

In my lectures,  the emphasis is on how the GCC compiler translates C source code into assembly language and how the processor executes the machine code. I always have terminals open to fire up GCC and GDB during lectures.

For future improvement of the offering of this course, I recommend the following:

• Use same syntax in both the lecture and lab. CS:APP2e uses AT&T syntax while ALPU uses Intel syntax.
• CS:APP2e is still 32-bit with a little introduction to 64-bit. It may be possible to use the 3rd edition which I believe is purely 64-bit.
• Most of the programming exercises do not accept input and produce output interactively. A GDB command/script file can be used to provide input and produce output by explicitly stating the variable names, memory addresses, or registers. Checking of programming exercises can be automated using GDB command scripts.
• Introduce assembly language programming in Windows environments using Microsoft Native Build Tools.
• Introduce ARM assembly language programming using an emulator or RPi.

I would like to thank Prof. Rizza DC. Mercado and Prof. Kendall Jaen for sharing their teaching materials. It was fun teaching this course and I learned some new topics in depth.

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How to determine research potential

(Last update: 19 January 2024)

As professors, we are often on the lookout for graduate/undergraduate students (or junior faculty) with research potential to join our research groups.  We want to encourage these students to pursue graduate studies in order to further advance the field by becoming researchers or professors in the future.

We base our evaluation initially on their grades from the courses they took. Our belief/claim is that the higher the General Weighted Average (GWA) of a student, the higher the research potential.  

Research potential, as described in Costromina et. al. (2014), is a multidimensional and multilayered system of individual psychological traits (motivational, cognitive, and behavioral characteristics) that act together to allow an individual to conduct research activity efficiently and fruitfully.  These traits are described below:

Motivational

• Intolerance for ambiguity - capacity to experience positive feelings in new, unstructured, and varied situations
• Satisfaction in solving problems - capacity to feel gratification from the process of finding ways and means for coping with scientific tasks
• Intellectual curiosity - the conscious desire to receive information about objects and to enjoy learning
  
• Intolerance for novelty - reveals thirst for experimentation, innovations, etc.

Cognitive

• Flexible thinking - can overcome conventional thinking
  
• Critical thinking - capacity to reveal mistakes and inconsistency, to correct errors, justify the validity of hypothesis
  
• Logical thinking - ability to use facts and laws to confirm the accuracy of conclusions promptly
  
• Quick thinking - ability to understand the situation and to make decisions in a timely manner
  
• Original thinking - capacity to propose new, unconventional ideas
  

Behavioral

• Self-organization - structuring of a researcher's personal activity to reach objectives
• Self-control - following research procedures and completing work tasks
• Adaptability - reduces time necessary to accept the changing conditions of a research task
• Assertiveness - maintaining stability while working in unstable conditions

Costromina et. al. (2014) conducted a study to compare undergraduates, master's students, and professors along the above dimensions. In their conclusion, they were able to obtain data on the high predictive validity of theoretical abilities in defining students' level of research potential.

"Theoretical thinking abilities are the aggregate of analytical and synthesizing

skills aimed at identifying common features and qualities of objects, as well as abili-

ties aimed at generalization and abstract thinking. These abilities function at a high

level along with a broad vocabulary range, and they reflect one’s ability to think in

the abstract."


At the undergraduate level, intolerance for novelty, self-control, adaptability, assertiveness and critical thinking are the characteristics that should have been developed, according to the study.

It seems, therefore, that the use of GWA as first screener of a student's research potential is valid. In addition however, a student should also be evaluated based on the traits described above.


Reference

• Kostromina, Svetlana & Bordovskaia, N.V. & Rosum, S.I. & Moskvicheva, Natalia & Iskra, Natalia. (2014). Research potential and cognitive features of students. Psychology in Russia: State of the Art. 7. 122-136. 10.11621/pir.2014.0411.

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SRG Authorship Guiding Principles

This post aims to address authorship in research papers produced within our research group. I think that authorship guidelines should be discussed early in the research project or graduate study in order to avoid complications later. I've witnessed colleagues and other individuals who abuse authorship by giving 'honorary' authorships, excluding names from the list of authors, and changing authorship order. The work by Solomon, Programmers, Professors, and Parasites: Credit and Co-Authorship in Computer Science, provides a good discussion of this topic. It presents the following principles that I will adopt for our group.


1. Authorship credit should be distributed only to those researchers directly involved with the paper or project in question. Researchers with indirect or minimal involvement may be mentioned in an additional "acknowledgements" section if necessary. All contributors should appear on paper; "ghost writing" is an invalid way even for a busy researcher to produce publications.

- Should you include your adviser and your committee members?
- Should you include project leader, project staff, research assistants?
- Should you include your research group leader?
- Should you include ALL members of your research group?
- Should you include your special someone?

2. All authors should be paired with short descriptions of their contributions to the project. These descriptions need not be on the title page but should apparent for anybody seeking further information about the research presented. This principle extends to the acknowledgements list. In general, any individuals or organizations mentioned by the paper should be identified to avoid "honorary" authorship and make explicit the division of work leading to the final results.

3. The list of authors should be divided by level of contribution. Within each division, authors should be ordered by the amount they contributed to the particular paper in question. Truly equal co-authorship relationships should be marked as such, with none of the authors identified as a "corresponding" author. The lack of a single corresponding author can be addressed by creating a simple email that alias that contacts all the principal authors simultaneously. Those researchers who would be considered "inventors" should be marked as such for the purposes of verifying future patent applications.

4. Upon publication, authors should be required to sign that the work in the paper is at least partially their own and that no other authors should be given credit.

5. Any and all decisions involving authorship should involve the mutual consent of all authors, which should be established via individual contact.

6. Any discovered cases of authorship fraud should be dealt with in much the same way as data fabrication. Once they are caught, authors should be required to explain their incorrect practices in a published statement and rectify any disadvantages suffered by parties not receiving appropriate credit.


References:

[1] Solomon, Justin. (2009). Programmers, Professors, and Parasites: Credit and Co-Authorship in Computer Science. Science and engineering ethics. 15. 467-89. 10.1007/s11948-009-9119-4.

[2] Allison Gaffey. (2015). Determining and negotiating authorship. Retrieved October 6, 2019 from https://www.apa.org/science/about/psa/2015/06/determining-authorship.    

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Notes from "It's not how good you are, it's how good you want to be"

• All creative people need something to rebel against, its what gives their lives excitement.
• There is no instant solution, the only way to learn is through experience and mistakes.
• Aim beyond what you are capable of.
• People who are conventionally clever get jobs on their qualifications (past), not on their desire to succeed, (the future).
• Do not seek praise. Seek criticism.
• If you accept responsibility, you are in a position to do something about it.
• If you give away everything you have (ideas), you are left with nothing. This forces you to look, to be aware, to replenish.
• Don't look for the next opportunity. The one you have in hand is the opportunity.
• Accentuate the positive. Eliminate the negative.
• Do not put your cleverness in front of the communication.
• Don't promise what you can't deliver.
• Give your client what he wants and he may well give you what you want.
• Don't take no for an answer. Work out a new approach.
• When it can't be done, do it. If you don't do it, it doesn't exist.
• If you can't solve a problem, its because you're playing by the rules.
• The pesron who makes mistakes is unlikely to make anything.
• It is wrong to be right, because people who are right are rooted in the past, rigid-minded, dull and smug.
• It is right to be wrong. Being wrong isn't in the future, or in the past. 
• Don't be afraid of silly ideas.
• Play your cards right.
• It's not what you know, it's who you know.
• Don't give a speech. Put on a show.
• Getting fired can be a positive career move.
• Rough layouts sell the idea better than polished ones.
• If you get stuck, draw with a different pen.
• Don't be afraid to work with the best.
• Do not try to win awards.

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How to solve problems

Some notes from the book How to Think Like a Mathematician by Kevin Houston. I found this chapter in the book interesting because I was able to relate to the  process when solving competitive programming problems.

Definitions

• Exercise - something that can be solved by a routine method
• Problem - something that will require more thought; will require the application of routine methods learned in exercises

"The best way to learn how to solve problems is to solve problems."

Sample Problems

1. How many zeroes are at the end of 100! (100 factorial)
2. Suppose that X and Y are two infinite sets. Find a formula that relates |X|, |Y|, | X intersection Y| and |X union Y|.
3. Show that the equation x^2 + y^2 = z^n has positive integer solutions for every n = 1,2 ,3, ...

Polya's four-step plan

Understanding the problem

1. Understand all the words and symbols in the problem - Know the meaning of the symbols as well as the important definitions and theorems
2. Guess - use your intuition - Make an educated guess
3. What do you know about the hypothesis and conclusion? - Write down what you know about the hypothesis and conclusion
4. Work backwards and forwards - You can start with the conclusion and think what it would imply.
5. Work with initial and special cases - Some problems have an index (n in P3). Solve for the initial cases to get a 'feel'.
6. Work with a concrete case - For abstract problems, look at a concrete case. Create instantiations of the variables. (P2)
7. Draw a picture - Venn diagrams (P2)
8. Think about a similar problem - Recall problems you've solved before that may be related to the problem you are solving.
9. Find an equivalent problem - Reformulate a problem, say to show that two functions are equal, they can be represented as a new function with difference of zero.
10. Solve an easier problem - In P1, solve 10! first to get a feel.
11. Rewrite in symbols or word -

Devising a plan

1. Break the problem into pieces -
2. Find the right level - there are many ways to approach a problem so select the right one
3. Give things names - "Let X be ..."
4. Systematically choose a method - A proving problem can be solved solve using different approaches.

Executing a plan

1. Check each step - don't use intuition

Looking back

1. Check the answer - Test.
2. Find another solution
3. Reflect - Think about what solved the problem.

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Internship at KAIST

This Midyear (June 24-August 16, 2019), I am a research intern at the Computer Architecture Laboratory of the School of Computing in KAIST under the supervision of Prof. Youngjin Kwon.  KAIST ranks high in the areas of Systems that I am really interested so this internship is a very good opportunity for me. My teammate for the internship project is Jongyul Kim who is a PhD student in the lab. We are working on improving the performance of distributed storage systems using RDMA, programmable NICs, and NVM.

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Sections I read in an SP paper

A Special Problem (SP) paper is a form of documentation for capstone projects of students. It is in the format of a journal article. As a panel member, it is only during the SP presentation itself that I get a copy of the SP paper of the presenter. So given the limited amount of time to read the paper, I only read certain parts of it before the presentation starts.

First I read the title to identify the general area(e.g. web/mobile app, ML, algorithms) of the project. Second,  I read the abstract to get an overview view of the work. Third I focus on the objectives to know the specifics of what should be achieved by the project. Lastly, the results and discussion to check whether the objectives were met.

It is unfortunate that some advisers don't bother to read/edit the SP papers of their students before the presentation. Nonetheless, the four sections I mentioned above, I think, should be written with care.

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PCSC 2019 Experience

This year's PCSC 2019 was held at the National University in Manila. According to the organizers, approximately 200 participants registered. There were three of us from UPLB. Although I did not present a paper, I enjoyed the presentations. Most are in the field of AI, ML and algorithms. It was good to see familiar faces in the computing research field in the country.  In the picture below is Dr. Roxas, the current president of the Computing Society of the Philippines delivering the opening remarks.

 

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Video: Data Link Layer Lecture

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Citation and References

During the early days of my career as instructor,  I did not pay much attention to the concepts of copyright and licenses. However, I realized that an understanding of these concepts is important to prevent complications in the future. (See previous post)

Side note:
--
Copyright - safeguards the ownership of an intellectual property
License - document that lets someone use the intellectual property
--

Now, as an assistant professor, I need to prepare materials for teaching and research which include the following:

• course syllabus
• course website
• handouts
• exams
• quizzes
• presentations
• research papers
• programs/software
• blog
• grant proposals
• audio/video
• figures/photos
• letters
• computer programs

In preparing these, I use resources that are published online, either by their authors or by third party publishers. These resources are by default copyrighted and thus permission from the authors should be obtained first. However, obtaining permissions may be a tedious task, thus authors indicate the license (such as Creative Commons) to these materials. At the least, authors of these materials should be properly acknowledged.

For research papers and grant proposals, there is usually a standard to follow. In my field, which is Computer Science, the ACM Citation Styles and Reference Formats [1] is widely used. This guideline can also be applied in course websites, course syllabus, blogs, and handouts. A "References" section is placed at the end of these materials which contains the list of other materials cited. In presentations, borrowed images and pictures must also be cited. At the minimum, the following information are needed for a reference entry (d-a-t-t-u):

• date/year of publication
• author/publisher (can be a person, organization, legal entity)
• title
• type  
• url/source

Examples:

[1] Joseph Anthony C. Hermocilla. 2018. CMSC 137: Data Communicatons and Networking (First Sem 2018-2019).  Retrieved September 9, 2018 from https://jachermocilla.org/teaching/137/2018-1/.
 
[2] McMillan, T. 2009. Fantail vector [JPG Image]. Retrieved September 9, 2018 from http://www.kiwiwise.co.nz/photo/fantail-vector.

[3] Marie Betel B. de Robles, Joseph Anthony C. Hermocilla, and Miyah D. Queliste. 2017. Buffer Overflow Exploitation on 64-bit Linux Systems [Google Slides Presentation]. Retrieved September 9, 2018 from http://srg.ics.uplb.edu.ph/resources/presentations.

[4] Joseph Anthony C. Hermocilla. 2018. Homework 3: Environment  Variables, Processes, and Threads [PDF Handout]. Retrieved September 9, 2018 from https://jachermocilla.org/teaching/125/2017-2/hw3.pdf

[5] Joseph Anthony C. Hermocilla. 2018. Homework 3: Environment  Variables, Processes, and Threads [Printed Handout].


Some authors find it cumbersome to cite because the information needed are not readily available. It seems that the best way then is to provide a "Reference as:" or "Citation:" element or section in your own materials which include the minimum information, d-a-t-u, above.

References:

• [1]ACM, Inc. 2018. Citation Styles and Reference Formats. Retrieved September 9, 2018 from https://www.acm.org/publications/authors/reference-formatting.

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