Code Metrics For Predicting Risk Levels of Android Applications

Android applications pose security and privacy risks for end-users. Early prediction of risk levels that are associated with Android applications can help Android developers is releasing less risky applications to end-users. Researchers have showed how code metrics can be used as early predictors of failure prone software components. Whether or not code metrics can be used to predict risk levels of Android applications requires systematic exploration. The goal of this paper is to aid Android application developers in assessing the risk associated with developed Android applications by identifying code metrics that can be used as predictors to predict two levels of risk for Android applications. In this exploratory research study the author has investigated if code metrics can be used to predict two levels of risk for Android applications. The author has used a dataset of 4416 Android applications that also included the applications\u27 21 code metrics. By applying logistic regression, the author observes two of the 21 code metrics can predict risk levels significantly. These code metrics are functional complexity and number of directories. Empirical findings from this exploratory study suggest that with the use of proper prediction techniques, code metrics might be used as predictors for Android risk scores successfully

Analysis of source code metrics from ns-2 and ns-3 network simulators

Ns-2 and its successor ns-3 are discrete-event simulators which are closely related to each other as they share common background, concepts and similar aims. Ns-3 is still under development, but it offers some interesting characteristics for developers while ns-2 still has a large user base. While other studies have compared different network simulators, focusing on performance measurements, in this paper we adopted a different approach by focusing on technical characteristics and using software metrics to obtain useful conclusions. We chose ns-2 and ns-3 for our case study because of the popularity of the former in research and the increasing use of the latter. This reflects the current situation where ns-3 has emerged as a viable alternative to ns-2 due to its features and design. The paper assesses the current state of both projects and their respective evolution supported by the measurements obtained from a broad set of software metrics. By considering other qualitative characteristics we obtained a summary of technical features of both simulators including, architectural design, software dependencies or documentation policies.Ministerio de Ciencia e Innovación TEC2009-10639-C04-0

An attribute grammar approach to specifying Halstead's metrics

Attribute grammars have been used in defining programming languages and constructing compilers. Since these are concerned with the syntax and static semantics of the source code of the language, attribute grammars can be effectively used to define source code metrics on it. Most of the source code metrics are based on measuring models of the source code. However, there is no formal way of specifying the mapping of the source code onto the models. This paper attempts to provide an approach using an attribute grammar to demonstrate how Halstead's metrics may be specified in an unambiguous manner on the source code itself

Web service QoS prediction using improved software source code metrics

Due to the popularity of Web-based applications, various developers have provided an abundance of Web services with similar functionality. Such similarity makes it challenging for users to discover, select, and recommend appropriate Web services for the service-oriented systems. Quality of Service (QoS) has become a vital criterion for service discovery, selection, and recommendation. Unfortunately, service registries cannot ensure the validity of the available quality values of the Web services provided online. Consequently, predicting the Web services' QoS values has become a vital way to find the most appropriate services. In this paper, we propose a novel methodology for predicting Web service QoS using source code metrics. The core component is aggregating software metrics using inequality distribution from micro level of individual class to the macro level of the entire Web service. We used correlation between QoS and software metrics to train the learning machine. We validate and evaluate our approach using three sets of software quality metrics. Our results show that the proposed methodology can help improve the efficiency for the prediction of QoS properties using its source code metrics

BugMaps-Granger: A Tool for Causality Analysis between Source Code Metrics and Bugs

International audienceDespite the increasing number of bug analysis tools for exploring bugs in software systems, there are no tools supporting the investigation of causality relationships between internal quality metrics and bugs. In this paper, we propose an extension of the BugMaps tool called BugMaps-Granger that allows the analysis of source code properties that caused bugs. For this purpose, we relied on Granger Causality Test to evaluate whether past changes to a given time series of source code metrics can be used to forecast changes in a time series of defects. Our tool extracts source code versions from version control platforms, generates source code metrics and defects time series, computes Granger, and provides interactive visualizations for causal analysis of bugs. We also provide a case study in order to evaluate the tool

RTTOOL : a tool for extracting relative thresholds for source code metrics

Meaningful thresholds are essential for promoting source code metrics as an effective instrument to control the internal quality of software systems. Despite the increasing number of source code measurement tools, no publicly available tools support extraction of metric thresholds. Moreover, earlier studies suggest that in larger systems significant number of classes exceed recommended metric thresholds. Therefore, in our previous study we have introduced the notion of a relative threshold, i.e., a pair including an upper limit and a percentage of classes whose metric values should not exceed this limit. In this paper we propose RTTOOL, an open source tool for extracting relative thresholds from the measurement data of a benchmark of software systems. RTTOOL is publicly available at http://aserg.labsoft.dcc.ufmg.br/rttool. Keywords: Source code metrics; Relative thresholds; Software quality; Software measurement