Abstract

Source code analysis is one of the important activities during the software maintenance phase that focuses on performing the tasks including bug localization, feature location, bug/feature assignment, and so on. However, handling the aforementioned tasks on a manual basis (i.e. finding the location of buggy code from a large application) is an expensive, time-consuming, tedious, and challenging task. Thus, the developers seek automated support in performing the software maintenance tasks through automated tools and techniques. However, the majority of the reported techniques are limited to textual analysis where the real developers’ concerns are not properly considered. Moreover, existing solutions seem less useful for the developers. This work proposes a tool (called as FineCodeAnalyzer) that supports an interactive source code analysis grounded on structural and historical relations at fine granular-level between the source code elements. To evaluate the performance of FineCodeAnalyzer, we consider 74 developers that assess three main facets: (i) usefulness, (ii) cognitive-load, and (iii) time efficiency. For usefulness concern, the results show that FineCodeAnalyzer outperforms the developers’ self-adopted strategies in locating the code elements in terms of Precision, Recall, and F1-Measure of accurately locating the code elements. Specifically, FineCodeAnalyzer outperforms the developers’ strategies up to 47%, 76%, and 61% in terms of Precision, Recall, and F1-measure, respectively. Additionally, FineCodeAnalyzer takes 5% less time than developers’ strategies in terms of minutes of time. For cognitive-load, the developers found FineCodeAnalyzer to be 72% less complicated than manual strategies, in terms of the NASA Tool Load Index metric. Finally, the results indicate that FineCodeAnalyzer allows effectively locating the code elements than the developer’s adopted strategies.

Highlights

  • Source code analysis is a core process performed by a software developer during the software maintenance phase [1]

  • 3) Code History Miner To extract the historical relations in the source code elements, we developed a Python-based Code History Miner (CHM)

  • The proposed tool is based on hybrid analysis of software system source code that exploits the structural and historical relations that exist in the source code

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Summary

Introduction

Source code analysis is a core process performed by a software developer during the software maintenance phase [1]. Software maintenance includes adding a new feature and fixing the existing one against a requested or reported by a user or other developer. A feature is requested a user observes that some functionality is missing and should be the part of software application. A. BACKGROUND Source code analysis is a core process a software developer needs to perform in the software maintenance phase [1]. Bug localization, bug fixing, fault testing, feature location, feature/bug assignment, and so forth [54]. These are the common tasks for developers while software maintenance activities. Feature/Bug assignment is the process of assigning a feature/bug to the relevant or appropriate developer [11]

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