recodex-wiki/Assignments-overview.md

# Assignments overview

Assignments are programming tasks that can be tested by a worker after a user 
submits their solution. An assignment is described by a YAML file that contains information on how to 
build, run and test it.

### Terminology
Following text requires knowledge of basic terminology used by ReCodEx. Please, check [separate page](https://github.com/ReCodEx/GlobalWiki/wiki/Terminology).

### Basics
Job is a set/list of tasks (it is generally a set, but order of tasks have some meaning). These tasks may have dependencies (arbitrary number), which needs to be observed. When recodex-worker processes job, it creates a task graph, where tasks are vertices and dependencies are edges (A -> B means that the task A is on the dependency list of task B) and creates its linear ordering. The graph must be acyclic (otherwise linear ordering will not exist) and the recodex-worker attempts to execute maximal number of tasks possible. Tasks without dependencies can be executed directly, other tasks are executed when all their dependencies have been successfully completed.

Tasks are executed sequentially -- by the linear ordering of the task graph. Parallel tasks (tasks, which are not directly dependent and thus their linear ordering may be arbitrary) are ordered first by their priority (higher number => higher priority) and second by their order in the configuration file. Priority is important for specifying evaluation flow. See sample picture for better understanding.

![Picture of task serialization](https://github.com/ReCodEx/GlobalWiki/raw/master/images/Assignment_overview.png)

Each task has a unique ID (alphanum string like _CompileA_, _RunAA_, or _JudgeAB_ in the picture). These IDs are used to identify tasks (for dependency references, in the log, ...). Numbers in bottom right corner are priorities of each task. Higher number is greater priority. It means, that if task _RunAA_ is done, next must be _JudgeAA_ and not _RunAB_ (that will be also valid linear ordering, but _RunAB_ has lower priority).

### Task
Task is an atomic piece of work executed by recodex-worker. There are two basic types of tasks:
- **Execute external process** (optionally inside Isolate). Linux default will be mandatory in Isolate, this option is here because of Windows.
- **Perform internal operation**. External processes are meant for compilation, testing, or execution of external judges. Internal operations comprise commands, which are typically related to file/directory maintenance and other evaluation management stuff. Few important examples:
   - Create/delete/move/rename file/directory
   - (un)zip/tar/gzip/bzip file(s)
   - fetch a file from the file repository (either from worker cache or download it by HTTP GET or through SFTP).

Even though the internal operations may be handled by external executables (`mv`, `tar`, `pkzip`, `wget`, ...), it might be better to keep them inside the recodex-worker as it would simplify these operations and their portability among platforms. Furthermore, it is quite easy to implement them using common libraries (e.g., _zlib_, _curl_).

**External Tasks**
These tasks are typically executed in isolate (with given parameters) and the recodex-worker waits until they finish. The exit code determines, whether the task succeeded (0) or failed (anything else). A task may be marked as essential; in such case, failure will immediately cause termination of the whole job.

- **stdin** - can be configured to read from existing file or from /dev/null.
- **stdout** and **stderr** - can be individually redirected to a file or discarded. If this output options are specified, than it is possible to upload output files with results by copying them in result directory.
- **limits** - task have time and memory limits; if these limits are exceeded, the task also fails.

The task results (exit code, time, and memory consumption, etc.) are saved into result yaml file and eventually sent back to frontend application to address which was specified on input.

### Directories and Files
For each job execution unique directory structure is created. Job is not restricted to specified directories (tasks can do whatever is allowed on system), but it is advised to use them inside job. In recodex-worker configuration one can specify worker default directory, this is base of every file which is produced by recodex-worker.
Inside this directory temporary files for job execution are created:
- **${DEFAULT}/downloads/${WORKER_ID}/${JOB_ID}** - where the downloaded archive is saved
- **${DEFAULT}/submission/${WORKER_ID}/${JOB_ID}** - decompressed submission is stored here
- **${DEFAULT}/eval/${WORKER_ID}/${JOB_ID}** - this directory is accessible in job configuration using variables and all execution should happen here
- **${DEFAULT}/temp/${WORKER_ID}/${JOB_ID}** - directory where all sort of temporary files can be stored
- **${DEFAULT}/results/${WORKER_ID}/${JOB_ID}** - again accessible directory from job configuration which is used to store all files which will be upload on fileserver

### Configuration
Configuration of the job which is passed to worker is generated from two parts:
- **template** - Common template for similar kinds of tasks. Contains allmost all instructions - when fetch, move, rename files, run commands, judges, ..., task dependencies and priorities. This template can be shared by more problem assignments or every problem (probably in compiller class) can have different one.
- **isoeval config** - includes data for instancioning the template, e.q. input file names, ...
Final configuration for worker is computer generated from those two configs.
Job configuration consist of some general information and then from list of tasks (one or more)

#### Configuration items
If not specified otherwise than its mandatory item! Mandatory items are bold, optional italic.
- **submission** - information about this particular submission
  - **job-id** - textual ID which should unique in whole recodex
  - **language** - no specific function, just for debugging and clarity
  - **file-collector** - address from which fetch tasks will download data
  - _log_ - default is false, can be omitted, determines whether job execution will be logged into one shared log
- **tasks** - list (not map) of individual tasks
  - **task-id** - unique indetifier of task in scope of one submission
  - **priority** - higher number, higher priority
  - **fatal-failure** - if true, than execution of whole job will be stopped after failing of this one
  - **dependencies** - list of dependencies which have to be fulfilled before this task, can be omitted if there is no dependencies
  - **cmd** - description of command which will be executed
    - **bin** - the binary itself
    - _args_ - list of arguments which will be sent into execution unit
  - _stdin_ - file to which standard input will be redirected, used only in external tasks, can be omitted
  - _stdout_ - file to which standard output will be redirected, used only in external tasks, can be omitted
  - _stderr_ - file to which error output will be redirected, used only in external tasks, can be omitted
  - _sandbox_ - wrapper for external tasks which will run in sandbox, if defined task is automatically external
    - **name** - name of used sandbox
    - **limits** - list of limits which can be passed to sandbox
      - **hw-group-id** - determines specific limits for specific machines
      - _time_ - time of execution in second
      - _wall-time_ - wall time in seconds
      - _extra-time_ - extra time which will be added to execution
      - _stack-size_ - size of stack of executed program in kilobytes
      - _memory_ - overall memory limit for application in kilobytes
      - _parallel_ - integral number of processes which can run simultaneously, time and memory limits are merged from all potential processes/threads
      - _disk-size_ - size of all io operations from/to files in kilobytes
      - _disk-files_ - number of files which can be opened
      - _environ-variable_ - wrapper for map of environmental variables, union with default worker configuration
      - _chdir_ - this will be working directory of executed application
      - _bound-directories_ - list of structures reprezenting directories which will be visible inside sandbox, union with default worker configuration
        - **src** - source pointing to actual system directory
        - **dst** - destination inside sandbox which can have its own filesystem binding
        - **mode** - determines connection mode of specified directory, one of values: RW, NOEXEC, FS, MAYBE, DEV

#### Configuration example
This configuration example is written in YAML and serves only for demostration purposes. Therefore it is not working example which can be used in real traffic. Some items can be omitted and defaults will be used.
```
---  # only one document which contains job, aka. list of tasks and some general infos
submission:
	job-id: eval_5
	language: "cpp"
	file-collector: "http://localhost:36587"
	log: true
tasks:
	- task-id: "fetch_input"
	  priority: 2
	  fatal-failure: true
	  cmd:
		bin: "fetch"
		args:
			- "94549d889ae96210ff2a73bd0a5bbe3185f05ff6"
			- "01.in"
	- task-id: "move_test01"
	  priority: 3
	  fatal-failure: true
	  dependencies:
		- compile_test01
	  cmd:
		bin: "mv"
		args:
			- "recodex.cpp"
			- "/tmp/isoeval/1/eval_5/recodex.cpp"
	- task-id: "eval_test01"
	  priority: 4
	  fatal-failure: false
	  dependencies:
		- move_test01
	  cmd:
		bin: "recodex"
		args:
			- "-v"
			- "-f 01.in"
	  stdin: "01.in"
	  stdout: "01.out"
	  stderr: "01.err"
	  sandbox:
		name: "isolate"
		limits:
			- hw-group-id: group1
			  time: 5  # seconds
			  wall-time: 6  # seconds
			  extra-time: 2  # seconds
			  stack-size: 50000  # KB
			  memory: 50000  # in KB
			  parallel: false  # time and memory limits are merged from all potential processes/threads
			  disk-size: 50
			  disk-files: 5
			  environ-variable:
				ISOLATE_BOX: "/box"
				ISOLATE_TMP: "/tmp"
			  chdir: /evaluate
			  bound-directories:
			  	- src: /tmp/isoeval/eval_5
			  	  dst: /evaluate
			  	  mode: RW,NOEXEC
			- hw-group-id: group2
			  time: 6  # seconds
			  wall-time: 7  # seconds
			  extra-time: 3  # seconds
			  memory: 60000  # in KB
			  parallel: false  # time and memory limits are merged from all potential processes/threads
			  disk-size: 50
			  disk-files: 5
...
```

### Parameters And Results
The job may have some input parameters (e.g., default config for Isolate, global parameters for the tested processes, ...). Similarly, the job has some structured results -- for each task (where applicable), it gathers exit code and consumed time and memory.

These parameters are stored in global, structured parameter space. I would suggest something that would map easily on JSON, for instance -- i.e., something that supports structures (named collections), arrays (ordered collections), and basic numeric and string values.

Input parameters have two sources, some defaults are present in the configuration of the worker, another set is provided in the configuration of the job. These sets are merged, job config has a priority.

Parameters are only read by the tasks (they can be used in task parameters). Some simple syntax needs to be used for evaluation of parameter expressions -- e.g., ("${params.tests[1].memoryLimit}"). _Parameters should be stored in worker's global namespace. Task configuration can make references to this structure. Validity should be checked before executing first task from the job. In this structure is only writable section "results" - here are written achieved memory and time limits of each task. Whole structure is send to WebApp with all logs._
 _**TODO:** analysis required -- how complex expressions do we really need_

#### Example result file

```
--- # only one document which contains job, aka. list of tasks and some general infos
job-id: 5
results:
	- task-id: compile1
	  status: OK  # OK, FAILED
	  sandbox_results:
		  exitcode: 0
		  time: 5  # in seconds
		  wall-time: 5  # in seconds
		  memory: 50000  # in KB
		  max-rss: 50000
		  status: RE  # two letter status code: OK, RE, SG, TO, XX
		  exitsig: 1
		  killed:
		  message: "Time limit exceeded"  # status message
	- task-id: eval1
	  status: FAILED
	  error_message: "Task failed, something very bad happend!"
	  .
	  .
	  .
...
```

### Logs
There is one general (mandatory) log, where the job progress is logged. Each row corresponds to one task and it holds only the task name, task exit code (or some other indication whether the task ended OK or not), and optionally things like consumed memory and time.

Other logs (stored in log dir) can be created. They do not have to be declared in advance, but they are specified at each task (if its output is going to a log) and created once some task produces an output that goes to the log.



## Case study

We present some of the courses that might use ReCodEx to evaluate homework 
assignments and outline the setup of the evaluation with respect to the concept 
of stages.

### Simple programming exercises

For example introductory programming courses such as Programming I or Java 
programming.

In the simplest case we only need one stage that builds the program and passes 
the test inputs to its standard input. We will use the C language for this 
example. The build command is `gcc source.c`, the test command is `./a.out`.

### Compiler principles

This course uses multiple tools in a pipeline-like fashion - for example `flex` 
and `bison`.

We create a stage for each of the steps of this pipeline - we run flex and test 
the output, then we run bison and do the same.

### XML technologies

In this course, students choose a topic they model using XML - for example a 
library or a bulletin board. During the semester, they expand this project by 
adding XSLT transformations, XQuery scripts, XPath queries, etc. These are 
tested against fixed requirements (e.g. using some particular language 
constructs).

This course already has a rather sophisticated application for testing homework 
assignments, so we only include it for demonstration purposes.

Because every assignment focuses on a different technology, we would need a new 
type of stage for each one. These stages would only run some checker programs 
against the submitted sources (and possibly try to check their syntax etc.).

### Non-procedural programming

This course is different from other programming courses, because it only teaches 
input/output manipulation by the end of the semester. In their assignments, 
students are mostly required to write a function/predicate that behaves 
according to a specification (e.g. appends an item at the end of a list).

Due to this, we need to take the function submitted by a student and combine it 
with a snippet of code that reads the standard input and calls the submitted 
function. This could be achieved by setting the build command.

### Operating systems

The operating systems course requires students to work on a simple OS kernel 
that is then run in a MIPS simulator called `msim`. There are various tests that 
check if the student's implementation of core OS mechanisms is correct. These 
tests are compiled into the kernel.

Each of these tests could be represented by a stage that compiles the kernel 
with the test and then runs it against different configurations of `msim`.