Muhammad Saleem
ABSTRACT
Software Development is a complex and multidimensional task. Often software development faces serious problems of meeting key constraints of cost and time. Big projects which are well planned and analyzed, can end up in a disaster because of mismanagement in cost estimation and time allocation. Program slicing has unique importance in addressing the issues of cost and time. It is broadly applicable static program analysis technique which provides mechanism to analyze and understand the program behavior for further restructuring and refinement. In this paper, authors investigate the relationship between program slicing and software development phases on the basis of empirical studies conducted in the past and also establish the fact that how program slicing can be helpful in making software system cost and time effective.
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Index Terms
- Cost effective software engineering using program slicing techniques
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Reviews
Larry Bernstein
This paper is a survey of published data and extrapolations about the effectiveness of program slicing in reducing the size of programs. Reducing program size results in simplified code that is easier to debug. Program slicing decouples code segments whose actions are independent. The paper promises more than it delivers. The references are meager and a simple Google search leads to a rich set of research on program slicing [1]. The paper is difficult to read, but led me to think about program slicing as a way of finding parallelism in programs that could be used for programming multicore computers. Figure 2 has a typographical error and a possible bug, in that a = 3 before slicing, making c = 8, and a = 4 after slicing, making c = 9. Saleem et al. assume that b is unimportant and drop it from the program. Couldn't another slice focused on b be important__?__ They make this same tenuous assumption for all of their slices. The results in Tables 1, 2, and 5 are impressive, yet unsubstantiated. It seems that the improvement cited in Table 5 for improved comprehension is computed by multiplying the 50 percent stated in Section 5.2 by the slice potential reduction in lines of code shown in the fourth column. There is no mention of other slices taken out of the original program and the effort needed to debug them. Yet, I agree that debugging is easier when you eliminate unrelated code. Program slicing is not clearly defined in the paper. Russell [2] points out that it is the set of source lines preceding a statement containing a variable that can affect the value of the variable. The paper states that you may reduce maintenance costs by making sure you do not mix unrelated code by resorting to program slicing, and tries to justify its recommendation by citing the literature. To understand program slicing, skip this paper and read Frank Tip's paper that surveys the technique [3]. Online Computing Reviews Service
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