Georgia Tech - Two More Weeks Down!

So last night I finished module 3 in my AI for Robotics course that I am taking as a part of Georgia Tech's Online MS in Computer Science. Things have somewhat settled down into a routine, with my various classmates working through the course at their own speed. Due to a complete lack of time in pretty much my entire life right now I'm simply trying to keep abreast of the weeks as they are due according to the schedule provided at the start of the term. Problem sets are due each Wednesday, and are submitted through Udacity's software. An instructor then goes through and ports these into something called T-Square, which I understand to be Georgia Tech's grading system. I could be wrong, though.

Assumed background knowledge

One of the things I'm noticing is that the course is starting to assume some background knowledge that not a lot of students may have. This is unavoidable in pretty much any course, as I have found out too often during my stints as a college professor. However, there are some ways this could be mitigated. For example, this is my first course at Georgia Tech, and my understanding is that it is targeted towards the end of the program. I took it because I found the subject interesting, but I could see where this might be causing me some trouble.

One example is that the course makes some decent use of techniques from Linear Algebra. I have a healthy grounding in this thanks to my time at DePaul and a few years spent in the pixel mines, but more often than not this type of math is an elective - at best - for computer science undergraduates. The problem is that there wasn't much in the course description that indicated that this type of math would be used. Statistical analysis is also featured heavily in the course, and while there are ample resources available for coming up to speed most students have no idea that they will need to do so before the course starts. I had around a month before classes began where I could have been preparing myself, but as it was I kind of walked into the course blind.

Interesting Problem Sets

One of the things I do find interesting is that the problem sets at the end of each lecture are actually not a significant portion of the grade. In fact, they're worth 3 points each (compared to a total upwards of 70 points for the two projects), and are graded on a pass-fail basis. To quote the professor, they essentially serve as a kind of "attendance check." That's all well and good, but if I am putting forth effort towards these assignments I'd like to see just a little bit more credit given for my efforts. Not much I can do about that, though, and I can definitely see the instructor's point.

One thing I do like about these problem sets is the use of automated grading. At first it's used in a fragile manner, along the lines of "Does the program output include this string," but the most recent assignment used statistical analysis in its grading to determine if the provided code was correct. It's pretty rewarding to see code that you wrote indicated as correct against an arbitrary data set with around 95% of accuracy.

Moving Forward

One thing I'm kind of leery of is wondering when the lack of prerequisite knowledge is going to bite me. I'm worried about the week 4 subject material, as it depends a lot upon dynamic programming and some aspects of machine learning - to the point where I'm reading chapters from a ML textbook in order to increase my knowledge base. It leads to one of the things I've been most concerned about, which is adequately scheduling time to devote to my courses.

So far the coursework takes me between 2-4 hours a week - a surprisingly low amount. However, I know that this is not the case for other courses, such as Machine Learning which can demand upwards of 40 hours of additional time each week, and in many cases I'm waiting for the other shoe to drop. I suppose at this point all I can do is wait and see, and hope it doesn't get too bad.

I'll try to provide these posts more frequently but, as I mentioned above, life happens :-/

More posts at Elite Gaming Computers!

This week I had a nice contrast in my articles. On the one hand I covered the ASUS Z97-WS, an absolute beast of a motherboard. On the other hand, I covered the Raspberry Pi for emulation and HTPC usage. The contrast pegged my chuckle meter, at least, as I found it interesting to go from "God of POWER!" to "Small but mighty!".

Anyway, check out the articles here:

http://elitegamingcomputers.com/raspberry-pi-htpc-emulator-on-a-budget/
http://elitegamingcomputers.com/the-asus-z97-ws-a-beast-of-a-board/

Georgia Tech OMSCS - Week 1 Recap

I know, it's only Thursday!

So I just finished my first "week" of class for Georgia Tech, and I wanted to get some of my thoughts down on virtual paper. I'd like to chronicle my adventure semi-frequently in this manner, so please bear with me if this isn't your cup of tea.

Some Background

So one of the things I'm willing to admit right off the bat is that I was pretty nervous. Given my prior trials and tribulations trying to even get into the program, I had no idea what to expect. I remember some of the experience of getting my MS the first time around, and some of the courses I took as an undergrad, but I wasn't sure how this experience would compare. What is an education like at a top-10 institution? Would I be able to measure up to the bar and finally put some of my constant inferiority complex to rest?

Well, we'll have to wait a while for the answer to that last one. I'm not very confident by nature, even though I know I have a modicum of programming and communication skills. I'm always looking for ways to "prove" myself, so to speak, and I tend to take on more than I can handle as a result. I am not sure that that personality trait will ever truly go away, and honestly this Georgia Tech experience stems from that whole complex - I had had a couple of bad interview experiences with companies that rhyme with Moogle and Bamazon, and was trying to figure out how to bolster my knowledge and not feel like I was incompetent. I guess this way I'll be able to point at a fancy piece of paper and say "Well, I was good enough for that".

Provided I am actually up to the task, that is.

The experience so far

Anyway, enough navel-gazing. I'm taking CS-8803 - AI for Robotics - and so far the experience has been pretty good. On the one hand the course is delivered almost entirely via lecture. I have mixed feelings about this, and feel another digression is in order. I know that there are different ways people learn, and that some people feel that they learn best visually. I also, though, have taught several classes where the student claims to only learn well visually but, if you really got down to it, what they really wanted was a step-by-step guide on how to do an assignment rather than a lecture that builds the foundations for a concept that they then apply themselves. In other words, they were (in my eyes) using the "I'm a visual learner" mantra as an excuse rather than a legitimate gripe. If you couple this with my NOT being a visual learner (I want nothing more than a big textbook to work through), I tend to be skeptical of the approach to begin with.

I have to say, though, I was pleasantly surprised. Aside from minor frustrations the lectures do a decent job of presenting the material. The way a module works is that a video of the lecture plays up to the point of a "quiz," which in a classroom setting would be the instructor asking a question of the class, and stops to allow you to input an answer into a form that is then checked for correctness. Once the answer is entered (or skipped, if you get stuck) the lecture continues until the next quiz. The lectures themselves vary widely, using video recordings in some cases, recorded whiteboard sessions in others, and still others with the professor simply talking to the students. Of most use to me were the intermittent programming quizzes - the instructor would explain a concept, then say "Ok, now you try to write a function that does this," and suddenly you're presented with a minimal Python IDE to develop code in, along with a test run and evaluation button to determine if your code is correct. It's obvious that a lot of thought went into these lectures, and it comes through in the design of the course.

Frustrations

My frustrations with the course so far are two-fold. First is that the course is programmed in Python - a language I had a passing familiarity with, but which is subject to its own quirks. If the course was in C++ or Ruby I'd have no trouble, but as it is I am learning the language as I go along. On the one hand that's good - I'll have another language under my belt when I finish the class - but it is also frustrating and increases the time I spend on assignments. I'm not sure there's any way around this, though.

The second frustration is with the video-based learning. It is extremely challenging to reference material in a video, particularly when programming. Programming is a lot about copy-and-paste, and you can't paste from a video. I have had this argument with any number of people, and I remain unconvinced - for these type of topics you can provide a video if you like, but the most useful thing to a professional programmer is a text version that allows you to 1: keep it open in a browser next to your IDE for reference, 2: allows you to review without having to hunt through a video, and 3: allows you to learn without needing to break your concentration for audio and visual stimuli. To me this is reminiscent of a problem I had at Enova, which is that for some reason the IT department thought it was a good idea to do all of their internal support tutorials as videos. Videos are an extremely poor choice when adding a VPN key, or when you want to save the information for future reference. If OMSCS is going to be mostly video-based, I suspect I'll be lamenting this for a while to come. But then again, I was able to complete the first week's assignment and understand the material (with one exception, as Bayes rule is still kicking my ass for some reason), so I guess the point is moot.

Communication

The course also has a separate message board on piazza.com, which is used to speak with your fellow classmates and ask questions of the instructor and TA. This is a great feature, I think, and has helped me a couple times. Most of the people in the course are active on the boards and very willing to help, and it is also helpful to see that some people have the same questions I do. Where I've had trouble in the course I've quickly been able to get a response on the message board, as both my fellow students and the instructors are active there.

Self-direction

One of the things I really like at the moment, but could see myself coming to dislike, is that the course is largely self-directed. If I had the time to spare, I could push through the entire course as quickly as possible. While the lectures are organized into "Lessons" that represent a week's worth of work, there is nothing preventing you from moving ahead as you work. On the plus side, this means that I was able to finish the first week's assignment well over a week before it was due, which is great as I maintain a far too busy schedule to begin with. However, I can see this causing problems near the end of the term as if we are looking at a time-based submission and grading process, I won't be receiving feedback on my submissions until they are officially "due". So for example, if I was to power through module 2 right now I wouldn't see any feedback until June 4 at the earliest, by which time the assignment will likely be out-of-mind.

I suppose time will tell on how successful this approach is for me. For now I like that I can work ahead when I have some spare time!

Evaluating my own teaching experience

Another thing the OMSCS experience is allowing me to do is evaluate my own teaching, and see what is effective. I teach college courses online for a couple universities, and seeing how this course is conducted provides some interesting contrasts. From the start, it's obvious that more effort went into the Udacity course design than goes into the courses I typically teach - which has been a constant frustration point for me as, with one exception, I often don't get to design my courses so that they have the material I feel is necessary. However, a lot of the assignments in the class I'm taking now are "did it or not" evaluations - you get points for completing the activity, but no partial points are awarded. I don't know what grading will be like yet (doesn't happen until next week), but I think "all or nothing" assignments are a disservice to the student and fail to recognize that it IS possible to half-understand something.

Conclusion

To sum up, I'm very much in a wait-and-see pattern right now. Some of my frustrations with the format may be exclusively due to this course's design - I've already heard that some of the other courses handle things a lot differently - while others may be due to the format. I guess my opinion will continue to evolve as I run through the experience. I know that's kind of a weak close to this lengthy post, but to be honest that's about how I feel right now - not very strongly on the "good" or "bad" spectrum, just "different."

I do think it will be interesting to come back and read this after I have a few more classes under my belt. So stay tuned, I guess.

Check out my latest posts at Elite Gaming Computers!

I cover SanDisk's new 4TB Solid State Drives at http://wp.me/p2yLe2-4P7
I cover ASUS' new 28" 4k gaming monitor at http://wp.me/p2yLe2-4Pb

Get 'em while they're hot!

Georgia Tech and Me

A few months ago I posted this after receiving a rejection from Georgia Tech's Online Masters in Computer Science program. Since then, after an email exchange with the dean of the school of computing, my rejection was reversed and I was admitted into the summer session, which begins very soon. I've been holding off posting about this, but wanted to give a brief touchbase. My previous post doesn't paint the program in a very good light. Some of that was due to my being hurt at an unjustified rejection, but some of my criticisms are still valid. As I get ready to register for my first course and begin taking classes online, here are a few of my observations on areas for improvement:

• Process deadlines and dates - Once admitted to the program, there are still a lot of questions. For example - I was admitted to the summer term, but I have no idea exactly what the dates for this term are. I have a vague idea of May to July, but none of the admissions material indicates the timeframe for the work I will be performing. Furthermore, the registration dates are not too highly publicized - there is a process where you can check with the registrar via the student portal, but it wasn't even really working until mid last week due to the status of OMSCS applicants. A quick email with a few reminders (alongside the DAILY emails we get with somewhat relevant general Georgia Tech news) would greatly benefit the prospective and admitted students.
• Value for money - I don't speak of the education, as I have yet to experience that (and regardless of my opinions, Georgia Tech's Computer Science program is ranked in the top ten in the nation), but rather during the application process. Form letters are inexcusable when someone has paid an application fee to be considered. This is endemic across academia - pay $50, get a form rejection. If I am paying $50, even if I don't get accepted I feel as though my purchase - which is between 5-10 hours of minimum wage earnings - warrants at least SOME individualized feedback. A personalized note. Tips for improving on the application. ANYTHING other than a generic, lazy form rejection. I understand the fears of providing a base for a discrimination suit, but in an objective measuring system designed to weed out applicants, there needs to be at least SOME room for objective feedback! I find this just as frustrating in the business world when applying for jobs (I am looking at YOU, Google and Amazon - give some freaking feedback and alleviate the single greatest complaint about your interview processes), but at least in those cases the only thing I lose is my time.
• Samples of coursework - I have absolutely zero idea how to prepare for the forthcoming coursework. Any examples of the courses themselves may have been publicized, but the accepted applicants should be reminded of these examples rather than having to resort to google searches of mass media. You're working on developing a system that will serve thousands of students each term - these convenience elements will save thousands of man-hours in help desk questions, support tickets, and overall will reduce general frustration.

Have any of you been accepted to the program? What are your thoughts on the above?

New Freelance Gig

Hey All,

I know it's been pretty quiet here lately, but I've been keeping up with my writing. I lately picked up a new freelance writing gig. I'll be writing content for the blog at Elite Gaming Computers - http://www.elitegamingcomputers.com/blog

You can see my first article here: http://elitegamingcomputers.com/kingstons-hyperx-cloud-gaming-headset/

Theme Story - Directions

Prompt this week was directions from point A to point B. I went a little weird.

First, start your water boiling. You want to get a nice, rolling boil going, so keep those flames hot. Once you've got the boil going, you'll start your journey by tossing in a handful of dirt. Doesn't matter where it comes from, but don't skimp on that handful. Add three oak leaves, with the veins removed, and two acorns. Let the mixture stew for a moment, then put on your protective clothing. Add a fourth-generation honeybee queen, being careful to keep the drones defending her from touching the boil. Using a stick from a sapling of less than two years, stir the mixture three times counter-clockwise. Then, add the saltpeter and step back – you should see a healthy boom.

If the pot survives the explosion. Instantly remove it from heat and let the mixture congeal. Scoop out three spoonfuls onto three separate cheesecloths, and place them at the corners of an equilateral triangle the size of the portal you wish to make. Make sure that the triangle points northwards – a south-pointing triangle is not something you want to experience. Step into the triangle formed by the three cheesecloths and do the hokey pokey but do NOT turn yourself around. Following this, hold your breath for three seconds and jump. If you have completed the recipe correctly, you should break through the ground into Flavortown. If not, you will land solidly on the ground and will lose your access for three years.

Theme Story - He turned the key in the lock...

He turned the key in the lock and opened the door. To his horror, he saw yet another of the damn rooms. Same pulsing green light emitting from the same pillars in each corner, same four doors pointing in each of the cardinal directions, same metal chair at the same table with – once again – nothing on it. Yet. He knew that would change soon enough, just as he knew that once he stepped forward the door would shut and lock behind him. He considered going back and trying the other doors, but after nearly fifty rooms he knew what he would find when he did so. Besides, it had only been four rooms since he had just picked a direction and went. He didn't know if he was making progress – hell, the way this place defied logic he could very well be moving in a circle repeatedly – but with no other options he decided to keep pressing onward.

He pulled out the chair and sat at the table, the screen inset into the surface once again coming to life. The same grid with the same colored dots greeted his angry gaze. He had to struggle to stop himself from tearing his hair out in frustration. He'd solved 47 of these puzzles so far. He found himself irrationally hoping that this one would be the last, or at the very least 50 would mark some kind of change in the scenario. A different room, a different puzzle, even a different light color in the glowing pillars would be preferable! Some indication that his actions were producing some effect somewhere. Anywhere.

He swiped his finger along the grid, connecting the colored dots without overlapping. This one was fairly simple, as were the others – the entire process took fifteen seconds. Upon completion, another key rose from the table. He placed the original key into his pocket with the rest of the growing collection, and palmed the new key. He rose from his chair and moved towards the door directly opposite the table - he'd taken to referring to this direction as North, but he had no real way to tell where he was even headed. He put his hand on the door handle, inserted the key, took a breath, closed his eyes, and turned the handle.

He waited a second to open his eyes, hoping to see anything different, but once again he was met with the same room. The 49^th room, with the 49^th puzzle, and the 49^th key. He sighed heavily, and moved to the chair. He plopped down with a despair as deep as his frustration had been in the last room. Fifty, he told himself. Just make it to fifty and something will change. He idly solved the puzzle on the table and grabbed the proffered key that resulted. Moving once again in the same direction, he approached the North door and inserted the key. With another steadying breath he turned the key in the lock and opened the door of the fiftieth room.

No change. Same green glow, same table, same chair, same four doors. He stepped through the door and sat in the chair, regarding the puzzle before him with a surly look. He swiped his finger around the grid, connecting the dots together, retrieving the key from the tiny slot in the table. He stood and approached the fiftieth door. He placed the key in the lock and, after a brief pause, turned it and opened the door...

… and blinked in the sudden light. Not green this time, but bright white emanating from every corner of the room. The table was round this time, the chair wooden, but the room was still surrounded by four doors in each of the cardinal directions. He crossed the threshold and a siren blared, causing him to jump out of his skin. He had no idea what it signified, but was oddly comforted by the fact that someone felt the need to signify something. A siren like that is placed for other people to hear, not for the sole occupant trapped in a maze. He approached the table and pulled out the chair. The surface lit up revealing the same grid. No, it was different this time – there was one more square in each direction, and one additional color to connect. He had apparently reached the next level. He leaned back, but oddly felt no anger or frustration. He was making progress at last. He solved the puzzle quickly and grabbed the key that emerged from the table, making his way to the North door once again. He inserted the key in the lock and turned the knob. Telling himself that if there is progress there might be an end, he pulled the door open and moved into the next white room. 

An Open Letter to Georgia Tech's Online Masters in Computer Science Program

NOTE - This situation has now changed. I leave this post here because I do not believe in shying away from my own words. I think that many of my points are still valid, the brash tone notwithstanding. Look up posts with label "Georgia Tech" for more information

To whom it may concern,

I just received my application decision, and I was turned down for admission to the online Masters in Computer Science program. I must say that I was surprised. From the FAQ on the OMSCS web site, I see the following requirements:

Preferred qualifications for admitted OMS CS students are an undergraduate degree in computer science or related field (typically mathematics, computer engineering or electrical engineering) from an accredited institution with a cumulative GPA of 3.0 or higher. Applicants who do not meet these criteria will be evaluated on a case-by-case basis; significant professional or other work experience with supporting recommendations may qualify as an adequate substitute for the appropriate academic credentials, however work experience will not take the place of an undergraduate degree. Georgia Tech will not admit applicants into the OMS CS degree program without the minimum qualifications for success. The Georgia Tech minimum criteria used in determining each applicant's eligibility for consideration shall include:

1. Evidence of award of a bachelor's degree or its equivalent (prior to matriculation) from a recognized institution, demonstrated academic excellence, and evidence of preparation in their chosen field sufficient to ensure successful graduate study; and
2. For international applicants, satisfactory scores on the Test of English as a Foreign Language (TOEFL).

In essence, the requirements applicable to me as a domestic applicant are: A bachelor's degree in computer science with a GPA of at least 3.0, demonstrated academic excellence, and preparation in the field sufficient to demonstrate successful graduate study. Let's cover each of these in turn:

A bachelor's degree in Computer Science - Achieved.
A GPA of at least 3.0 - Achieved
Demonstrated academic excellence - I have a master's degree from DePaul in computer graphics, which I completed with a 3.93 GPA while working full time. In other words, I graduated with distinction from a challenging program that I underwent while working 40 or more hours a week. I am pretty sure that demonstrates academic excellence. Not to mention that my undergraduate GPA was more than sufficient to earn me an invitation to Upsilon Pi Epsilon and would have given me the opportunity to graduate with honors, had I received the paperwork early enough.
Preparation in the field sufficient to demonstrate successful graduate study - Aside from 10 years experience as a software engineer, I have shown evidence of previous successful graduate study by successfully performing graduate studies. Setting aside my letters of recommendation, my success in my master's degree and my continuing efforts as adjunct faculty at various colleges should sufficiently demonstrate this requirement.

In short, I have met your base requirements, I have experience as a professional in computer science, and I have a demonstrated track record of academic excellence at the graduate level. So why, I ask, was my admission denied?

Let's look at your letter, which I assume was a form letter:

"Admission to the program is extremely competitive, and I am sorry to report that we are unable
to admit you"

This is the first thing that caught my eye. Here is a direct quote from the OMS CS website:

"Applicants who meet the minimum criteria will be conditionally admitted into the degree program and must pass their first two OMS CS foundational courses with a grade of B or better to be fully admitted."

One of these things is not like the other. You can't have an "Extremely competitive" admission, and then turn around and say you will conditionally admit all applicants who meet the minimum criteria. That is not how the English language works - accepting everyone who meets the minimum requirements precludes the words "Extremely competitive". Not to mention that the letter I received directly contradicted this statement (not the first time that your information conflicted during the admissions process, either). Moving on:

"While you may have some experience in computing, we do not believe that you are currently prepared for success in this program, which is extremely demanding in a broad range of Computer Science"

Some experience in "computing"? Like a graduate degree in "computing", and ten years of experience as a developer across a variety of industries? And you judged my ability in this area based on what - transcripts from a bachelor's degree? Did I not mention Big O notation, or list my favorite data structures? Perhaps it's the fact that I have been teaching students in this area for over two years - did that result from me not having sufficient computing experience, or not being prepared for success? I highly doubt your judgment on my "computing" experience when you have seen no samples of my work, and when you use terms like "computing" to describe the actual study of "computer science."

"We encourage you to take courses in Computer Science that may better prepare you for a future application of admission to this program."

How is it determined that I need to take more courses in Computer Science, anyway? Did someone test my knowledge when I wasn't paying attention? Did they see samples of my code that I wasn't aware of? What part of computer science do I need a refresher on? Should I just pick a class at random and go for it?

In short, one of two things is happening: I missed some secret requirement that I didn't meet, or my application was not sufficiently evaluated. I would like to request more information on my denial of admission, or more specific feedback (you've had three months to respond to people - a three months which you have repeatedly pushed back for questionable reasons - more than sufficient time to personalize the responses to less than 2,000 people (much less, given that this was a second round of admissions)) on how I can better improve. Were my grades too excellent in graduate school the first time around? Did I have too much employment experience?

Thanks for your time, and while I am extremely disappointed in your shortsightedness I do wish you the best of luck with the OMS CS program. I had hoped to be an advocate for this novel way of presenting the course, but after going through the application process I now have serious doubts about how it can succeed when handled as it has been.

Matt Billock

Concrete Coding Corner - Agile Estimation

In the last concrete coding corner post, I spent a lot of time talking about goals and metrics and how they relate to non-concrete endeavors such as writing and programming. One thing I deliberately left out was the obvious. Sure, I can develop any number of metrics to tell me how much progress I am making, but what do I do to tell how much progress is left?



In the business world (where most of my experiences in this area lie), companies are run on quarterly budgets that take into account resource allocation and potential projects. These projects usually have some sort of figure attached to them that represents a Return On Investment, or ROI. The goal then is to have ROI be as high as possible, while the resource allocation budget to produce that ROI needs to be as low as possible. For manufacturing processes, there are a number of factors that play into this – designers, prototyping, manufacturing, material resources, and so on. Physical costs, such as the base metal required to manufacture the body of a vehicle, are pretty much fixed. You can potentially swing a one-time decrease through intense negotiation, but you introduce yourself to potential shortfalls in quality to meet the new price. Not to mention that negotiating those kinds of reductions can be an extremely time-consuming and exhausting process.



The other aspect of any project is the, for lack of a better word, “flexible” cost. This is the cost for more ephemeral tasks, such as programming or architecture, where you cannot necessarily know how long the task will take before you begin. A project manager or product owner looks at their cost reduction options and sees this, thinking to themselves “Getting Joe to work a bit harder for a while will get this done faster, and be easier than reducing physical costs. Let's do that!” Without data to back up assertions that the goals imposed as a result are not achievable through reasonable effort, the programmer is left in the lurch – they have no power to change the situation, and thus often end up working long hours to meet the seemingly arbitrary goals.



The Problem
The primary problem with the “just work more” approach is obvious to anyone who has done creative work for any length of time – creative work is exhausting. Performing that kind of work for any length of time can feel very much like running a marathon, conflating the mental and physical worlds into a conglomeration of perceived Herculean effort. After X number of hours, with X being different for every individual, it is simply not possible to produce at the same quality level as it was possible before X hours had elapsed.



The practical upshot of this is that quality of output for creative endeavors decreases as the time spent on that task in a session increases. This is the central point that is missed when attempting to procure more effort out of employees who derive their primary work product from the expense of mental effort – longer hours means more bugs and issues, which means longer hours to fix them. It's an infinite loop of increasing required effort, which often ends up costing more to complete than if the employee had been allowed to go at their own pace.



Note that the video game industry is horrible in this regard. Long hours (60-80 hour weeks or more) are the norm in that industry as projects move towards the completed stage. Project managers in the game industry are often constrained by hard dates – such as the holiday season – that they have no way to negotiate around, and so when you cannot manipulate your end date the only thing remaining is to attempt to manipulate the amount of effort performed each week. In many cases, this results in months of extremely long hours, where programmers and artists are pushed relentlessly to meet deadlines that are forever seeming farther away. Additionally, the cumulative exhaustion of weeks of long hours seeps in, resulting in the remaining amount of work increasing despite the longer hours as bugs introduced into the system by a tired programmer required effort to fix.



Having spent time in the game industry, I wish I could say that the above was an apocryphal example, but examples abound throughout the industry, and things rarely seem to improve. The marketing and funding realities of the industry make this a problem that is tricky to solve. Some companies have large enough cash reserves that they can simply ignore the calendar and say “It'll be done when it's done,” but most others need the infusion of cash provided by a completed project to continue to do things like pay rent, electricity, and employees (often in that order).



Analyzing the issue
The game industry has a situation that arises from external constraints, but it also is a byproduct of creative work – there is no way to know how long a task is going to take before it is started. Sure, you can have a ballpark. For example, I've written two books so far, and each took about 30 days for the final draft. Given that, it's reasonable to assume that if I were to write a third book, it would also take about 30 days for the final draft.



Except when it doesn't.



This is the most frustrating thing about programming to non-programmers. Two tasks can seem extremely similar, but one may take five minutes while another would take a week. The reasons why are numerous – fractured code bases, incompatible patterns, and so on – but ultimately there is no obvious reason that a layman can point to and say “Oh, that's why that took so long!” This problem, when repeated multiple times over the course of a project, can sour the relationship between a project manager and a programmer, taking what was originally a productive and respectful interaction process and making it confrontational. It is usually not the result of any intentional slight by the programmer or intentional misinterpretation by the PM, but instead it's an issue of trust.



Every time a programmer claims that a task will take longer than originally expected, or that they have been delayed, the PM has no choice but to assume that the delays are intentional as they have no insight whatsoever into the development process. This may not be an overt assumption, but it certainly occurs on some subconscious level and factors into decision making and interactions. This injects stress and discord into the process, which builds up over the course of a project and results in negative perceptions. A project could be on the most efficient possible track to completion, making strides that no other team could possibly make with the same material, but once the perception is soured that effort will never be seen as sufficient.



Addressing the Problem
The problem, as we've already mentioned, is that the PM has no way to know when a given task will be completed. The frustrating thing is that oftentimes, neither does the programmer. Sure a programmer can make an educated guess, but there are always factors outside of their control that play into the end result. Thus, the first approach to addressing the problem is to rely solely upon the guesses of the programmer. The programmer takes a look at a task before he begins, and gives an estimate of the effort required to complete that task. As a project manager is concerned with dates and timelines, they often push for time-based estimates (“It will take four hours”), and many programmers agree to the system.



Problem Solved, Right?
Once a unit associated with time has been decided upon, everything very quickly goes to hell. If a task that should “only take four hours” suddenly takes 40, then there is a perceived deficit. A project manager looking at a project plan sees the extra 36 hours of effort and is forced to conclude that “The project is now 36 hours behind.” This amount grows or shrinks as effort continues, and the perception of the project manager changes each time. If a task takes less time than expected, then the programmer is “making good progress” and the project is “on track.” If a task takes more, then the programmer is “introducing delays” and the project is “delayed.”



Notice the attribution of effort here. This all ties back to the choice of time as a base unit. Once you are estimating in terms of hours, the natural human tendency is to start watching the clock. We've been trained to pay close attention to time periods – 8 hours of work, 1 hour for lunch, 30 minutes to commute, and so on – that we subconsciously monitor the amount of time taken. When something takes longer than stated, it is frustrating and unsettling. By tying the estimates of a programming task into this time-based system on a granular level, we introduce the same predilections and perceptions into the evaluation of progress. It removes the ability to look at a task objectively and say “we are making X amount of progress.” Instead, everything is cast in terms of time. Time elapsed, time remaining, time behind, and when looking at the time associated with a project subjective judgments are added into the project status. Choosing an estimate in terms of time has resulted in looking at the project at a micro level, removing the ability to see the forest through the trees. The subjective perceptions of “late” and “early” that have been pounded in to us from our youngest years come into play, and color our perception of the project's progress.



Aggregate Data
One of the reasons behind this is that it is far too easy to look at a project as a series of finite tasks. Once these tasks have a discrete time associated with them, it is far too easy to take each task as an element in isolation. Good project managers, though, recognize that each task is only part of a larger whole. They strive to look at a project in aggregate – that is, as a combination of all of the tasks. They see the four hour task taking 40 hours, but then realize that the project is still 25% completed with one quarter of the budgeted time elapsed.



Thus, we see the path to our solution. An individual four hour task may run long, and may result in a delay. But on average, four hour tasks will typically take four hours. Some may be shorter, some much longer, as that is the nature of creative endeavors. However, looked at over a span of time, it is possible to develop a translation. If the average of all “four hour” tasks is 4.5 hours, that gives us a reliable predictive measure. We now know that if the programmer estimates a task at 4 hours, it will take 4.5 hours on average. This allows us to adjust our estimates and determine where the project actually lies.



A Problem of Units
At its core, with this translation table we've improved upon the primary concern – developing accurate estimates of project effort. However, we haven't addressed the soft factors of the issue. By associating progress with hours of effort, we are still tapping into that primal clock-watching urge, and thus still adding in the subjective judgements that go along with it. This is the problem with any time-based estimate system – it is tied to a known and familiar system, and even though it may operate on a varying scale, there is a subconscious perception of variation that permeates the project, regardless of the intentions. Because “hours” was chosen as the unit, this is tied back to real world elapsed time, and we end up with a slightly improved version of the same problem.

As it is, we now actually have the seeds of a potential solution. We've identified that looking at effort in aggregate provides us with more accurate estimates of project completion. We've also identified that expressing estimates in terms of time introduces needless subjective judgments into the process. We finally know that despite our best efforts, we do eventually have deadlines to meet – we cannot continue to just work forever.



A Different Approach
What we are really doing when estimating a task is building a view of the entire project. A project is the sum of its parts, and having broken a project down into constituent tasks it thus follows that a project's total effort is the sum of the efforts of all of its tasks (it is more complicated than that, but usually the point holds well enough). So by adding up all of the estimates associated with a project, we can determine a total estimate for the entire project. In a time-based system, this is expressed in terms of hours and days.



However, at this point we are working simply with numbers. We've established that due to the nature of creative work estimates are by definition non-concrete. So instead, we apply analytics to find out what “four hours” actually means in terms of calendar time. At this point, we're simply doing number analysis – averaging numbers together to produce a measure in terms of time. Since we have the same units on both sides of the equation, it follows that when these values on either side of the equation differ, then one of the choices of units is thus incorrect. It should be obvious that 4.5 hours does not equal 4 hours, so one of those figures must not really be “hours” as we know them.



Let's instead refer to the right side of that equation as points. Instead of 4.5 hours = 4 hours, we have 4.5 hours = 4 points. By removing the hours from the right hand side of that equation, we've suddenly addressed the subjective issue with our measurement system so far – we took away the time base in order to find the actual value, and as a result hit upon a number system that allows us to assign arbitrary values to tasks that develop meaning as a project progresses.



Building upon this gives us a more reliable means of estimation. Instead of assigning an hour estimate to each task, we assign a point value. The point value is indicative of the general effort required to complete the task, just as the estimate in hours was, but by removing the time value we remove subjective expectations. We assign higher numbers to challenging tasks, and lower numbers to easier tasks, knowing that on average the effort expended for each classification of task will average out to the same amount of effort, even if one specific task takes longer than another.



Tying it All Together
As we noted earlier, deadlines are inescapable. We cannot simply work forever. Thus, status reporting becomes a matter of determining how much longer the project will take to complete. We have a method of assigning difficulty to our tasks by giving them point values, and the point values are arbitrary units and thus remove all subjective judgments and perceptions. So our task at this point is to tie these points back into time periods.



This is actually what we were hoping to accomplish with our original estimation scheme – determine the amount of time it will take to complete a project. We simply hit upon the wrong units, and thus added a lot of extra cruft to our project plan. By trying to tie points back to hours, we become too granular – the points completed per hour varies far too much from task to task to give a worthwhile measurement. So the only option is to expand our averaging time window. This becomes an arbitrary choice, but I've seen the most success with week-long and two-week-long periods, known in the agile methodology as “Sprints”. You add up the points completed during each sprint, then keep a running average of the efforts completed. In doing so you tie the point values back into time values while also accounting for the aggregate variance of the data. For example – if I have a project that is has 170 units remaining, and I have been averaging 17 points completed per one-week sprint, I can say with a fair degree of confidence that there are 10 weeks remaining in the project.



This 17 number – the average point value completed during a sprint – is known as “velocity.” A project's velocity is used to relate the overall project duration back to the time required to complete it. By increasing the unit of measurement and divesting our estimates from subjective measures, we've introduced a more reliable system of estimation – simply divide points remaining by velocity. What this does is twofold. First, it gives you a quick and dirty estimate of the time remaining in a project that, over several weeks, tends to become very accurate as the amount of data to measure increases.



The second thing that it gives you is the ability to say no. Take, for example, a project that is starting to trend towards long hours. If you archive your data properly, you can point to previous examples where such an approach only made matters worse. Instead of “well, that will be pretty hard on the team,” you can instead say “We tried this before, and added 50 points of work while only achieving 47 from the increase in face time. How do you think it will be different this time around?” By looking at the point value of each task to be completed, some negotiation can take place and instead of giving subjective measurements and impressions, you can provide specific feedback with actionable data. Of course in some cases this won't do a damn bit of good, as the project deadlines may be particularly unforgiving, but in aggregate this approach should produce an environment that is collaborative and built upon a reliable history, as opposed to a relationship founded on distrust and fostered in a confrontational environment.



What does this mean for writing?

Ultimately, this method obtained from programming can be applied to any creative endeavor that can be assigned a subjective judgment of “easy” or “hard.” Simply break a project down into constituent tasks, then assign a point value to each task representing its difficulty. Of course after a certain point the tasks become repetitive – how many ways can “Write this scene!” be phrased, after all? However, one thing I have found when applying this approach to my own efforts is in support of my previous post on metrics – once you start putting your mind to measuring your progress in a more objective manner, you are able to get a better feel for how things are actually going with the project. While you may or may not have deadlines to work towards, and you may or may not have people waiting on your progress, the concrete proof of your progress is often enough to help you break through any bumps on the road, and stave off periods of despair over how long a given project is taking.

Theme Story - A Milestone Birthday

Brian took another swig of his drink, grimacing as the cheap bourbon set his mouth on fire yet again. He preferred the smoother Irish whiskeys, but in a bar in Kentucky your drink choice was more or less a foregone conclusion – particularly when someone else was buying. He looked over his glass at John and, catching his eye, raised it in the traditional salute of thanks. Niceties achieved, he set the beverage down to give the ice some time to melt and mellow the flavor.

Thirty. He couldn't believe it had been so long. By some accounts his life was half over, and even the most optimistic estimates only reduced the deduction to thirty-three percent. Sixty years if he was lucky, of which the last fifteen to twenty were likely just biding time. So call it forty years reliably. He took another swig – too soon, as the heat on his tongue was happy to inform him – and tried not to dwell on how he was spending yet another night punishing his liver in the same tavern. Perhaps if they had tried to class up the place a bit he could have stood the monotony – sand some of the walls smooth, maybe stain the wood a darker color than the tannish-brown that didn't so much reflect the light as absorb it before casting it out into the world. Of course that would offend the clientele, the hearty salt-of-the-earth folk who liked their bars slapdash, their camaraderie boisterous, and their whiskeys blazing.

And their music twangy, as Brian was reminded by the jukebox happily blaring the latest blues-inspired nothing from a country-western group whose last chart-topper was released a decade ago. His melancholy allowed him to scoff at the clear efforts of musicians past their prime, but his past years in the country had helped him to develop an appreciation for the style, finding some small comfort of home in the chord structures if not the banal lyrics. He'd tried once, a couple years ago, to get the jukebox to do more than lament the lives of cheating boyfriends and lost tractors, but the death glares that he'd earned as the opening bars of the one Rush tune that was available on the machine played had been enough to abash him of any future attempts at culture.

He took another swig, this time more satisfied with the spirit. Sure the ice watered it down a bit, but sometimes that was the only thing that made the drink tolerable. He smiled to himself as he remembered the hazy days of college, the quantity-versus-quality binges Friday after class. Had that really been nine years ago? It was odd – the gray hairs didn't bother him at all, but when Brian realized how long it had been since he'd been a student he shuddered with the weight of age. He still felt like that wayward scholar most days, no idea where he was headed but doing his best to not appear that way. Somehow fake-it-til-you-make-it never made it past step one, and one of his more pervasive ridiculous fears was that someone would expose his attempts at maturity for the pathetic facade that they were.

Someone asked him a question, and Brian took a second longer to process than was proper. With a small shake of his head he gave a non-committal response, and received a hearty clap on his back to go with the chuckles at the birthday boy who was showing his inebriation so soon after the party's start. Conversation resumed, and Brian went back to staring at his glass. Was this what forty would feel like? Fifty? He went to take another swig, but suddenly noticed that the glass was empty. Setting it down, he leaned forward on his hands as he pondered.

Thirty years gone. Seven years a professional, and what did he have to show for it? A slice of the American dream, sure. For what that mattered, at least. The small house on the edge of town was often a harsher task master than his manager, with the grass that never stopped growing and the vermin that never stopped burrowing. A job that was decidedly middle-class, which in essence meant he was able to come out enough ahead every paycheck to set aside a meager amount for those waiting years in the coming autumn of his life. No loving wife, but a parade of women of increasing age, with accelerating desires and relationship goals that never seemed to align with his long-term plans. Plans towards which he had, so far, made zero progress.

Another contained puddle of bourbon had materialized at his elbow, and he gave a grateful smile to Katy – the kind purveyor of the current round, and even kinder woman who was the most recent of those trying to find a place to fit in with him. Not that he had women lining up, but rather he understood what they were looking for and how to provide it. He took a sip and shook his head. That last bit was unnecessarily harsh. Katy was sweet, and even if she felt the same pressures that had been put on him by others of the fairer sex she gave no indication of the pushiness that others had been all to happy to unlimber on him once things started to show signs of progress. He thought he appreciated that more than anything – sure she was looking for a future, but she wasn't using the strong-arm to make it happen.

Brian took another swig, smiling again as raucous laughter filled the table in response to some joke or another. He'd never been much for birthdays, he realized that, and his friends seemed to tolerate that well enough, but he knew he was on the edge of stretching patience. He grit his teeth, smiled, and jumped into the conversation – feeling out of place and awkward, but still knowing what was expected of him and fulfilling those expectations as best he could.

Perhaps the next thirty years would hold the wisdom he seemed to be missing, or the sudden achievement of greatness. He sipped the bourbon, made a random joke. Doubtful, but he figured he'd give 'em his best shot.