A Survey on Impact of Lines of Code On Software Complexity - IT Assignment Help

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Abstract— Size is one of the important attributes of a software product. Lines of Code (SLOC or LOC) is one of the most widely used sizing metrics in industry .The amount of effort needed to maintain a software system is related to the technical quality of the source code of that system. Estimation of effort is complicated and challenging task in software industry. Project size is a measure of problem complexity in terms of effort and time required to develop the products. This paper mainly focuses on Impact of LOC on complexity. SLOC is typically used to predict the amount of effort that will be required to develop a program, as well as to estimate programming productivity or complexity once the software is produced.
 

Keywords—Complexity, Effort, Lines of code

INTRODUCTION

Lines of code (LOC) or source lines of code (SLOC), is a software metric used to measure the size of a computer program by counting the number of lines in the text of the program's source code. LOC is the metric which measure the size of project by counting the number of instructions in the developed program. Obviously while counting the number of source instructions, lines used for commenting the code and the header lines are ignored. In order to estimate the LOC count at the beginning of a project, one would have to make a systematic guess. So sometimes project divided into modules and sub modules until sizes of different modules can be approximately predicted [1][3] .Lines of code (LOC) only measures the volume of code, one can only use it to compare or estimate projects or programs that use the same language, and is coded using the same coding standards. To change one is to change the volume of code.

IMPACT OF LINES OF CODE ON COMPLEXITY
A. Complexity by Size increases
The use of good metrics or tools helps in better estimation. As software grows in importance and size means if lines of code increases in a software then it leads to increases in complexity and makes the calculation difficult [7] .Due to increased number of customers wishes, the complexity of product also increases.This holds especially for software where code size and complexity sometimes increases beyond being manageable .The reason for this trend is that more and more functionality put into software [8]. It is clear that program size is an important complexity factor to measure.[10]

Complexity by Error rates
Complex code or complex lines of code also tends to be bigger than simple code, and that means more opportunity for accidents, omissions and manifestation of code errors. Complex systems are harder to test and therefore are more likely to have untested portions or parts. Complex systems are harder to design securely, implement securely, configure securely and use securely[9][10] Three major kinds of complexity metrics at four different levels of analysis This classification can yield four independent metrics: the average size of the subprograms within each program, the average size of the programs which constitute that system, and two measures of control-structure complexity which have been normalized for size (the density of decision points and the density of branch points)

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