4 research outputs found
Parallel Paths Analysis Using Function Call Graphs
Call graphs have been used widely in different software engineering areas. Since call graphs provide us with detailed information about the structure of software elements and components and how they are connected with each other, they could be used in detecting specific structures and patterns in the code such as malware, code clones, unreachable code, and many other software symptoms that could be searched by their structural features. In this work, we have analyzed parallel paths in function call graphs in three Java open-source projects. Parallel paths emerge when there is more than one path between two nodes in the call graph. We investigated the reasons such paths are created and used for and also the problems that result in removing them. Moreover, we have used the results of our analyses to find instances of parallel paths in the projects that we analyzed and suggest some changes to developers based on that. Based on our results, we found three categories of problems associated with parallel paths and four categories of usages of them
JavaScript Dead Code Identification, Elimination, and Empirical Assessment
Web apps are built by using a combination of HTML, CSS, and JavaScript. While
building modern web apps, it is common practice to make use of third-party
libraries and frameworks, as to improve developers' productivity and code
quality. Alongside these benefits, the adoption of such libraries results in
the introduction of JavaScript dead code, i.e., code implementing unused
functionalities. The costs for downloading and parsing dead code can negatively
contribute to the loading time and resource usage of web apps. The goal of our
study is two-fold. First, we present Lacuna, an approach for automatically
detecting and eliminating JavaScript dead code from web apps. The proposed
approach supports both static and dynamic analyses, it is extensible and can be
applied to any JavaScript code base, without imposing constraints on the coding
style or on the use of specific JavaScript constructs. Secondly, by leveraging
Lacuna we conduct an experiment to empirically evaluate the run-time overhead
of JavaScript dead code in terms of energy consumption, performance, network
usage, and resource usage in the context of mobile web apps. We applied Lacuna
four times on 30 mobile web apps independently developed by third-party
developers, each time eliminating dead code according to a different
optimization level provided by Lacuna. Afterward, each different version of the
web app is executed on an Android device, while collecting measures to assess
the potential run-time overhead caused by dead code. Experimental results,
among others, highlight that the removal of JavaScript dead code has a positive
impact on the loading time of mobile web apps, while significantly reducing the
number of bytes transferred over the network
A graph-based approach to detect unreachable methods in Java software
In this paper, we have defined a static approach named DUM (Detecting Unreachable Methods) that works on Java byte-code and detects unreachable methods by traversing a graph-based representation of the software to be analyzed. To assess the validity of our approach, we have implemented it in a prototype software system. Both our approach and prototype have been validated on four open-source software. Results have shown the correctness, the completeness, and the accuracy of the methods that our solution detected as unreachable. We have also compared our solution with: JTombstone and Google CodePro AnalytiX. This comparison suggested that DUM outperforms baselines
A graph-based approach to detect unreachable methods in Java software
In this paper, we have defined a static approach named DUM (Detecting Unreachable Methods) that works on Java byte-code and detects unreachable methods by traversing a graph-based representation of the software to be analyzed. To assess the validity of our approach, we have implemented it in a prototype software system. Both our approach and prototype have been validated on four open-source software. Results have shown the correctness, the completeness, and the accuracy of the methods that our solution detected as unreachable. We have also compared our solution with: JTombstone and Google CodePro AnalytiX. This comparison suggested that DUM outperforms baselines