A Survey on Impact of Lines of Code on Software Complexity. Bhatia, S. and Malhotra, J. In Advances in Engineering and Technology Research (ICAETR), 2014 International Conference On, pages 1–4. IEEE / Dept. of CSE, GNDU, Jalandhar, India.
A Survey on Impact of Lines of Code on Software Complexity [link]Paper  doi  abstract   bibtex   
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. [Excerpt: Open Issues and Future Scope] [::] Implementation of a specific logic differs based on the level of experience of the developer or programmer Hence, LOC differs from person to person. An experienced developer may implement software in fewer lines of code than another developer of relatively less experience does, though they use the same language [::] Sometimes between two programs with equal LOC count, a program having complex logic would require much more effort to develop than a program with very simple logic. [::] LOC measure correlates poorly with the efficiency of the code. Larger code size does not necessarily imply good quality or higher efficiency. Some programmers develop lengthy Code and complicated code as they do not make efficient use of the available instruction set. [] Many applications will be designed which have expected to have less lines of code so that software complexity can be reduced. Looking at rising demand for successful software quality and also for the implementation, it is safe to conclude that in the coming years, metric of software importance will increase multifold as industry leaders like embrace newer and more stringent approaches to monitoring, improving as well as delivering better software quality in products or projects as well as processes. Future research directions include improvement in existing metrics based on the nature and magnitude of the problem statement. [Conclusion] If lines of code increase then complexity of software also increases which also affects the cost of software projects. With increases in lines of codes bugs in software also increases which decrease the performance of software and also increases the complexity of software. COCOMO model, SLIM model uses lines of code as input size. SLOC metric is most useful in Software Estimation but some restrictions or limitations that are involved in SLOC Metric make it vurnable for relying on it. Many effort estimation metrics takes the input as the software size, which can be measured with class point, function point, LOC. But the complexity part of software or program has not properly addressed by most effort estimation metrics, whose presence may affect the overall estimation result or performance.
@inproceedings{bhatiaSurveyImpactLines2014,
  title = {A Survey on Impact of Lines of Code on Software Complexity},
  booktitle = {Advances in {{Engineering}} and {{Technology Research}} ({{ICAETR}}), 2014 {{International Conference}} On},
  author = {Bhatia, Sonam and Malhotra, Jyoteesh},
  date = {2014-08},
  pages = {1--4},
  publisher = {{IEEE / Dept. of CSE, GNDU, Jalandhar, India}},
  issn = {2347-9337},
  doi = {10.1109/icaetr.2014.7012875},
  url = {https://doi.org/10.1109/icaetr.2014.7012875},
  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.

[Excerpt: Open Issues and Future Scope]

[::] Implementation of a specific logic differs based on the level of experience of the developer or programmer Hence, LOC differs from person to person. An experienced developer may implement software in fewer lines of code than another developer of relatively less experience does, though they use the same language

[::] Sometimes between two programs with equal LOC count, a program having complex logic would require much more effort to develop than a program with very simple logic.

[::] LOC measure correlates poorly with the efficiency of the code. Larger code size does not necessarily imply good quality or higher efficiency. Some programmers develop lengthy Code and complicated code as they do not make efficient use of the available instruction set.

[] Many applications will be designed which have expected to have less lines of code so that software complexity can be reduced. Looking at rising demand for successful software quality and also for the implementation, it is safe to conclude that in the coming years, metric of software importance will increase multifold as industry leaders like embrace newer and more stringent approaches to monitoring, improving as well as delivering better software quality in products or projects as well as processes. Future research directions include improvement in existing metrics based on the nature and magnitude of the problem statement.

[Conclusion]

If lines of code increase then complexity of software also increases which also affects the cost of software projects. With increases in lines of codes bugs in software also increases which decrease the performance of software and also increases the complexity of software. COCOMO model, SLIM model uses lines of code as input size. SLOC metric is most useful in Software Estimation but some restrictions or limitations that are involved in SLOC Metric make it vurnable for relying on it. Many effort estimation metrics takes the input as the software size, which can be measured with class point, function point, LOC. But the complexity part of software or program has not properly addressed by most effort estimation metrics, whose presence may affect the overall estimation result or performance.},
  keywords = {*imported-from-citeulike-INRMM,~INRMM-MiD:c-13971341,~to-add-doi-URL,complexity-vs-uncertainty,cyclomatic-complexity,lines-of-code,software-errors,uncertainty}
}
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