A practical example of pseudocode

Figure 1.3 shows the pseudocode of a resource allocation algorithm called SRPMP. In cluster computing, there are many situations where there are parallel tasks that need to be run on a set of available resources, collectively called a resource pool. This algorithm assigns tasks to a resource and creates a mapping set, called Ω. Note that the presented pseudocode captures the logic and flow of the algorithm, which is further explained in the following section:

1: BEGIN Mapping_Phase
2: Ω = { }
3: k = 1
4: FOREACH Ti∈T
5:     ωi = RA(Δk,Ti)
6:     add {ωi,Ti} to Ω
7:     state_changeTi [STATE 0: Idle/Unmapped] → [STATE 1: Idle/Mapped]
8:     k=k+1
9:     IF (k>q)
10:       k=1
11:    ENDIF
12: END FOREACH
13: END Mapping_Phase

Let's parse this algorithm line by line:

1. We start the mapping by executing the algorithm. The Ω mapping set is empty. 
2. The first partition is selected as the resource pool for the T₁ task (see line 3 of the preceding code). Television Rating Point (TRPS) iteratively calls the Rheumatoid Arthritis (RA) algorithm for each T_i task with one of the partitions chosen as the resource pool.
3. The RA algorithm returns the set of resources chosen for the T_i task, represented by ω_i (see line 5 of the preceding code).
4. T_i and ω_i are added to the mapping set (see line 6 of the preceding code).
5. The state of T_i is changed from STATE 0:Idle/Mapping to STATE 1:Idle/Mapped (see line 7 of the preceding code).
6. Note that for the first iteration, k=1 and the first partition is selected. For each subsequent iteration, the value of k is increased until k>q.
7. If k becomes greater than q, it is reset to 1 again (see lines 9 and 10 of the preceding code).
8. This process is repeated until a mapping between all tasks and the set of resources they will use is determined and stored in a mapping set called Ω.
9. Once each of the tasks is mapped to a set of the resources in the mapping phase, it is executed.