In computer science, loop dependence analysis is a process which can be used to find dependencies within iterations of a loop with the goal of determining different relationships between statements. These dependent relationships are tied to the order in which different statements access memory locations. Using the analysis of these relationships, execution of the loop can be organized to allow multiple processors to work on different portions of the loop in parallel. This is known as parallel processing. In general, loops can consume a lot of processing time when executed as serial code. Through parallel processing, it is possible to reduce the total execution time of a program through sharing the processing load among multiple processors. The process of organizing statements to allow multiple processors to work on different portions of a loop is often referred to as parallelization. In order to see how we can exploit parallelization, we have to first analyze the dependencies within individual loops. These dependencies will help determine which statements in the loop need to be completed before other statements can start, and which statements in the loop can be executed in parallel with respect to the other statements in the loop. Two general categories of dependencies that will be analyzed in the loop are data dependencies and control dependencies. Description Loop dependence analysis occur on a normalized loop of the form: for i1 until U1 do for i2 until U2 do ... for in until Un do body done ... done done where body may contain: S1 a[f1(i1, ..., in), ..., fm(i1, ..., in)] := ... ... S2 ... := a[h1(i1, ..., in), ..., hm(i1, ..., in)] Where a is an m-dimensional array and fn, hn, etc. are functions mapping from all iteration indexes (in) to a memory access in a particular dimension of the array. For example, in C: for (i = 0; i < U1; i++) for (j = 0; j < U2; j++) a[i+4-j] = b[2*i-j] + i*j; f1 would be i+4-j, controlling the write on the first dimension of a and h2 would be 2*i-j, controlling the read on the first dimension of b. The scope of the problem is to find all possible dependencies between S1 and S2. To be conservative, any dependence which cannot be proven false must be assumed to be true. Independence is shown by demonstrating that no two instances of S1 and S2 access or