A Week of Configuration Management

Configuration Management

Configuration management software attempts to identify and track the elements of a system's configuration so that errors can be found and fixed. Version control is a special sub-case of this which focuses on maintaining multiple branches (development versions used for experimentation or developing new features) and the central trunk (the main version which all branches must eventually be merged with). Defect tracking systems track error reports from identification to the point at which the errors are fixed, and are part of configuration management because fixing the errors usually requires configuration changes.

To use a configuration management system, developers must first check out (download) the project from the SVN repository (the directory on a remote server where the project files are stored). Once this is done, they can edit their local copy of the project files, then commit (upload) the changed files or directories. If a developer adds new files to the project, they must be manually added to the files under version control before being committed to the repository. If others make changes, a developer must update (download new versions) the local copies of the changed files. William Wake explains it in more detail in this graphic.

As we were instructed in class, best practices for configuration management systems include verifying that the system runs and builds correctly before committing any changes. Otherwise, you run the risk of having to hurriedly fix previously undetected mistakes one after the other, as reflected in this log of commit messages:

Rev 53571: "This is a basic implementation that works."
Rev 53572: "By works, I meant 'doesnt work'. Works now.."
Rev 53573: "Last time I said it works? I was kidding. Try this."
Rev 53574: "Just stop reading these for a while, ok.. "
Rev 53575: "Give me a break, it's 2am. But it works now."
Rev 53576: "Make that it works in 90% of the cases. 3:30."
Rev 53577: "Ok, 5am, it works. For real.
Back when I said basic implementation? Scratch that."

(Source: This Stack Overflow thread)

Subversion

Subversion, the successor to the earlier CVS, is an open-source configuration management system that runs on the Berkeley Database, manages tags and branches similarly to folders, and handles all file types in the same way. It is currently an industry standard due to its centralized nature, which helps with access control issues and allows a single project leader to coordinate development; however, many in the open-source community prefer Git's flexibility and multiple workflows over Subversion' centralization.

Many GUI and command-line clients exist to access SVN repositories; I used TortoiseSVN, a Windows client. The GUI was fairly easy to use for my first assignment of revising and committing a preexisting project. For the second project, in which I had to upload my project to Google Code (about which more is written in the next section), I had a little more trouble with the command line interface, and what was ultimately more helpful than the project documentation in figuring out how to add files and do other operations was this general SVN manual, which did a good job of describing SVN's general logic.

Google Project Hosting

To complete my training in configuration management, after uploading my code to Google's remotely hosted repository via TortoiseSVN, I set about configuring the front page and some instructions for users and developers working with my robocode-tjo-meteor robot. The page I set up can be found here, and the source files can be checked out using the instructions here.

Google Project Hosting is fairly easy to add new pages to and configure settings for, using a system of simple menus similar to other Google interfaces I have used in Blogger or Google Sites.

Google Project Hosting allows users to choose Subversion, Git, or Mercurial as their configuration management system, and handles defect tracking by listing open issues on the "Issues" page. The current SVN trunk is viewable in the Source page, and the revision history is also available.

The only real issue I have with Google Project Hosting mostly deals with with element positioning:

• The tables are made with sets of ||s, not tags:Google only detects a table cell if both the opening || and closing || are on the same line (i.e., you never press enter at any point between them).
  For example, typing:
  
||Contents||
||I want this entire sentence to appear
in one table cell||

  results in:
  
  
  If you break this rule, you may end up with several scattered partial table cells. The workaround, typing the text you want to enclose as one long sentence, means that enclosing long sentences or paragraphs in table cells looks ugly in code and is almost unreadable if you use any other HTML tags or wiki markup within the table. I spent hours figuring out how to force Google to recognize the table cells before I realized that the bug was related to newline characters in this way. Google does allow the use of <table> tags, however, so there is a workaround for this.
• The anchor links:There are several things to be aware of when writing these. The support page helpfully explains that spaces need to be replaced with underscores in anchor links. Essentially, what I discovered was this:
  
// In this case I am trying to make an anchor link to header == Foo Bar ==
[# Foo Bar ] // This creates a link to the main URL of the page itself, and reloads it instead of going to the anchor. In some cases it does not work at all. The preceding and trailing spaces are not needed even though they are in the header.
[#Foo Bar] // This will not work either. As mentioned, the space needs to be replaced with an underscore.
[#Foo_Bar] // This will work.

  If you are mostly using this to make a table of contents as I did, there is a faster piece of built-in wiki code that does the job:
  //Set the depth to specify how many layers deep you want the contents to go.
  
• You cannot import images directly:Blogger allows you to import pictures from within the editor and host them on Picasa, in addition to embedding image links to pictures you have hosted elsewhere. This is not possible in Google Code. Though I there are definitely reasons to prefer this approach (Picasa's limitations, privacy concerns, or Blogger's arbitrary display sizes of "large", "medium", and "small"), a similar feature might be nice as an additional option.
  

Despite these minor issues (some of which were aggravated by my misreading of Google's support page), Google Code seemed to provide a decent level of services for being a free service and was an easy way for me to learn the basics of version control in a controlled setting, without the risk of damaging a real enterprise project - and demonstrated the ease with which I could use Subversion systems to store personal projects as well, though perhaps not quite at the level of Joey Hess.

Going In Circles And Then Some: Preparing for a Robocode Tournament

Project Overview

The robot I was attempting to design for the Robocode tournament would have avoided hitting walls altogether, and would have been able to maintain a basic lock on its target. Neither of these goals was accomplished to any useful extent.

Design

• Movement

Ideally, the robot was to have moved 100 pixels each turn, turning itself perpendicular to the headings of any enemies encountered and turning back before hitting walls where possible. I attempted to do this via the avoidBounds method, which was intended to turn the robot away from walls and thus avoid collisions with the walls entirely. As far as I can tell, this instead caused freezing problems whenever the robot managed to be positioned perpendicular to a corner, and in some other cases I was unable to define.

• Targeting

Ideally, the robot was to have rotated its radar 180.0 degrees per turn, turned its body to be perpendicular to an enemy robot once it was scanned, logged its opponent's name, then begun scanning in smaller 22.5-degree intervals as long as it continued to detect that same opponent. Once that opponent was destroyed or had not been seen for two scans, it would resume scanning in increments of 180.0 degrees. In reality, the robot lost targeting locks almost constantly, as its other behaviors caused it to turn too frequently to maintain a consistent heading or back-and-forth pattern of strafing.

• Firing

The robot implements a basic bullet-power calculation algorithm based solely on distance, starting at the maximum of 3.0 for anything less than 100 pixels away, dropping from 2.9 to 2.0 for anything 100-300 pixels away, then to 1.9 to 1.0 for anything 300-500 pixels away, then to 0.9 to 0.5 for anything more than 500 pixels away. It fires whenever it detects the robot it is currently targeting, and targets the same robot for the duration of at least three 22.5-degree scans before giving up and looking for a new target.

Results

(Each robot was fought for 10 rounds.)


Meteor's lack of predictive targeting means that Walls has moved out of range by the time Meteor aims its cannon at where Walls used to be; Meteor has no way of accounting for drastic shifts in direction or velocity on the part of an enemy robot.

Robot Name	Wins Against	Losses Against
SittingDuck	10/10	0/10
Virtually all robots can beat SittingDuck.
Tracker	1/10	9/10
Meteor's primary weakness against Tracker is that it takes too long to scan for changes in motion (Tracker hardly scans at all once it has a lock), and thus fires much less often than Tracker. In addition, when this robot loses track of a target, it completes a 180.0-degree radar rotation, leaving it vulnerable to attack.
Corners	0/10	0/10
Meteor's avoidBounds method backfired here, frequently causing it to spin in circles without firing or moving while Corners swept its radar across the battlefield in increments.
Fire	0/10	0/10
Once again, the problem was that Meteor took too long to aim and fire,getting only a fifth the bullet damage of Fire. Meteor also froze repeatedly in this match.
Crazy	3/10	7/10
Meteor did not perform predictive movement analysis, and had no way of estimating Crazy's movement pattern, whatever it was. I am not sure why Meteor won against Crazy at all.
SpinBot	0/10	10/10
Meteor actually dodged several of SpinBot's projectiles, but it failed to score any hits of its own and usually got stuck against a wall after about thirty seconds, thanks to its freezing bug.
RamFire	2/10	8/10
Once again, Meteor's need to make large turns and radar sweeps each time it lost a targeting lock did it in; this made it easy for RamFire to push Meteor into walls or otherwise obstruct its movement.
Walls	0/10	10/10

Testing

My tests consist of two acceptance tests, TestMeteorVersusCorners and TestMeteorVersusFire, both of which the robot fails (see the Results section); one behavioral test, TestMeteorFiring, that checks whether Meteor.calculateShotPower is functioning correctly; and three unit tests (UnitTestWhichWallOrCorner, UnitTestDistanceToWallOrCorner, UnitTestNewXAndY) for the methods Meteor.whichWallOrCorner (which returns an integer code based on whether the robot is near a wall or corner), Meteor.distanceToWallOrCorner (which calls whichWallOrCorner itself, and determines the distance to a wall or corner) and a combination unit test for the very similar Meteor.newX and Meteor.newY methods, which calculate the point that a particular motion will cause the robot to drive to. UnitTestNewXandNewY does not work, however, due to what are probably errors in how I assumed it was supposed to work.

Lessons

The Robocode design process has revealed a harsh truth about my coding style: specifically, that it tends to produce a lot of code, most of which performs as expected, but most of which goes towards performing some extremely complex task (avoiding walls) which in the long run is not very important. In addition, the sheer length of my code virtually guarantees problems like Meteor's mysterious freezing episodes, which could come from any number of points in the code which control movement and which do not seem to share any common factors. Thus, I have a robot with about 400 lines of code (excluding comments) that cannot beat any of the sample robots with any sort of reliability, is still incapable of detecting when it is near a wall and stopping, and shoots straight but on average takes longer than most of its opponents to do so. The major problem is the freezing bug, which I have repeatedly failed to fix over the course of the last two days. If I had tried to do this over again, I would have spent less time trying to reinvent the wheel and more time modifying example code, as my attempt to implement a wall-avoiding function took so much time there was little left to actually test anything else.

The Robocode API: Rapid Learning With "Code Katas"

Introduction

Learning and practicing new computer skills (a programming language, an IDE, an operating system, etc.) is a task that is often frustrating at best and intimidating at worst, especially when one is having trouble learning the system at its most basic levels. The philosophy of code katas, a form of practice with a name borrowed from Japanese martial arts, seeks to break the learning process down into a series of repeated drills, each one slightly more complex than the last. As the developer completes each drill, he or she gains essential skills along the way. This kind of "effortful practice" produces results faster than unfocused practice because it is focused around specific tasks, ideally just beyond one's current level of competence.

With this in mind, I set out to complete thirteen code katas for the Robocode API:

1. Position01: The minimal robot. Does absolutely nothing at all.
2. Position02: Move forward a total of 100 pixels per turn. When you hit a wall, reverse direction.
3. Position03: Each turn, move forward a total of N pixels per turn, then turn right. N is initialized to 15, and increases by 15 per turn.
4. Position04: Move to the center of the playing field, spin around in a circle, and stop.
5. Position05: Move to the upper right corner. Then move to the lower left corner. Then move to the upper left corner. Then move to the lower right corner.
6. Position06: Move to the center, then move in a circle with a radius of approximately 100 pixels, ending up where you started.
7. Follow01: Pick one enemy and follow them.
8. Follow02: Pick one enemy and follow them, but stop if your robot gets within 50 pixels of them.
9. Follow03: Each turn, Find the closest enemy, and move in the opposite direction by 100 pixels, then stop.
10. Boom01: Sit still. Rotate gun. When it is pointing at an enemy, fire.
11. Boom02: Sit still. Pick one enemy. Only fire your gun when it is pointing at the chosen enemy.
12. Boom03: Sit still. Rotate gun. When it is pointing at an enemy, use bullet power proportional to the distance of the enemy from you. The farther away the enemy, the less power your bullet should use (since far targets increase the odds that the bullet will miss).
13. Boom04: Sit still. Pick one enemy and attempt to track it with your gun. In other words, try to have your gun always pointing at that enemy. Don't fire (you don't want to kill it).

The Robocode project, once managed by IBM and now an open-source, community-driven effort, provides a way to program armed virtual robots and pit them against each other. Robocode robots are controlled by programming three types of behavior: movement, radar scanning, and firing. Though the core concepts are simple, the API is versatile enough that in the hands of experienced developers, Robocode battles can become a serious business indeed.

Look at this genetic algorithm, now look back at mine. Sadly, my code lacks complex algorithms. But the idea behind the code katas is that, with practice, that code is what my code could look like. Each group of katas emphasized a specific skill, whether finding specific points on a map, circling a particular area, tracking and picking targets from among multiple enemies, or controlling the power of the robot's shots based on information acquired about enemy robots.

The first three position methods were easy to implement. The fourth took a little more work, but finding the center was fairly easy after writing methods to calculate the angle between the robot and the center, and the distance of the straightest path to the center, and the sixth was just a variation of the fourth. The fifth method was the hardest of the group for me, and it took a while before I realized that it was returning the wrong angles because the robot was not accounting for its own previous turning when calculating the turn angle. I made heavy use of the Math.atan2 method here, as it was easy to retrieve the x- and y-distances between two points for use in calculating the angle.

The Follow robots were easier to write, since most of the data needed to match the headings of enemy robots could be obtained from pre-made methods, especially the method which retrieves a scanned robot's name for easy tracking. Follow03 was easily implemented by causing the robot to scan continuously for enemies, store their data, and compare the results after each scan.

Most of the Boom robots were also quickly written; Boom01 and 03 only needed to fire automatically. Boom02 was also easily handled using the getName() function. I am still not sure whether or not I implemented Boom04 correctly; it lost its "lock" on the target frequently,
and occasionally aimed in the opposite direction of its target's motion. The problem was probably related to correcting for differences between the gun angle and the robot's heading, something I did not quite get the hang of; since each exercise in a group was based on previous ones, Boom05 could be the exercise where sloppily designed but still previously workable methods finally became unusable.

Overall, the "code katas" were easy ways to pick up basic programming skills, and even some of the errors along the way pointed the way to competitive strategies I might be able to use in the future.