Abstract

Metric and Tool Support for Instant Feedback of Source Code Readability

Highlights

  • Software maintenance accounts for a large portion of the entire cost of the software life cycle [1]

  • The suggested readability metric achieves 75.74% of explanatory power, and our experiment showed that readability of most of the methods authored in our tool is higher than that of the methods without our approach

  • We carried out multiple linear regression analysis and nonlinear regression analysis to build the readability prediction function Φ based on the 16 candidate indicators and the average readability from the questionnaire response

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Summary

INTRODUCTION

Software maintenance accounts for a large portion of the entire cost of the software life cycle [1]. We newly suggest indicators for measuring the readability metrics of the source code, and refine and verify them through questionnaires and multiple linear regression analysis Based on these indicators, we establish an equation that can quantitatively measure the readability of a Java method on the fly. Gauge: We developed the tool support that visualizes the readability of the current Java method in the readability gauge and historical changes of the readability through the line graph. The remainder of this paper is structured as follows: Section 2 introduced related work on the software metric for measuring the readability of the source code and previous tool support. Sangchul CHOI et al.: Metric and Tool Support for Instant Feedback of Source Code Readability

RELATED WORK
BUILDING SOFTWARE METRIC FOR MEASURING THE INSTANT SOURCE CODE READABILITY
Conducting a Questionnaire Survey
Defining and Extracting Readability Indicators
Analysing Importance of Readability Indicators
TOOL SUPPORT:
EXPERIMENT
Preliminary Study
Threat to Validity
Findings
CONCLUSION
Full Text
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