Evaluating maintainability of android applications

According to International Data Corporation (IDC), Android accounted for 81% of all smartphone shipments in the third quarter of 2013. With the increase in smartphones, mobile application installs from Google Play have reached more than 48 billion app installs as revealed by Sundar Pichai, senior vice president, Chrome and Apps at Google I/O 2013. Thus, Android application development has become increasingly popular with the need of an effective software solution for application development and testing. While most Android applications are developed in Java, the Android framework is quite different fromm typical Java frameworks. Thus, while development or testing of Android applications, the user needs to be aware of all the terms and concepts specific to the Android framework such as activity, views and the Android SDK in general.

In software testing process, test data generation represents an important step for high quality software, even for mobile devices. As proposed in previous works, a potential source for random data generation is represented by the UI layout files that are used for almost all mobile platforms (Android, iOS, Windows Phone/Mobile). This paper continues the previous work and presents a test data generation system based on Android layout files. The test data generator uses DSL files as input and generates test data that conform to several testing principles. The generated test data could be stored in XML files or any format required by the testing frameworks.

Android is an operating system source which offers flexibility and support for most mobile applications, and easy access to social networks. It is important to understand the complexity of design, development, implementation, and testing of Android apps. A number of challenges may be faced in testing android applications, including the lack of testing processes and methods, testing experts being unavailable, poor in-house testing environment, and time restrictions. Mutation testing is a fault-based testing technique, applied by generating mutants and running the application with these mutants to analyze the killed and equivalent mutants. We defined a set of mutation operators according to the features of android applications: apps with content sharing, apps with multimedia, apps with graphics, and apps with user location and maps. We identified 42 mutation operators. In addition, we implemented a new tool, “µ-Android,” which automatically generates mutants and retrieves results to prove the efficiency of the test cases and enable the new operators.

Recently, with the purpose of helping developers reduce the needed effort to build highly secure software, researchers have proposed a number of vulnerable source code prediction models that are built on different kinds of features. Identifying security vulnerabilities along with differentiating non-vulnerable from a vulnerable code is not an easy task. Commonly, security vulnerabilities remain dormant until they are exploited. Software metrics have been widely used to predict and indicate several quality characteristics about software, but the question at hand is whether they can recognize vulnerable code from non-vulnerable ones. In this work, we conduct a study on static code metrics, their interdependency, and their relationship with security vulnerabilities in Android applications. The aim of the study is to understand: (i) the correlation between static software metrics; (ii) the ability of these metrics to predict security vulnerabilities, and (iii) which are the most informative and discriminative metrics that allow identifying vulnerable units of code.

The potential of fish in the sea is a hope for fishers. During fishing, fishers must go around and map the fishing location because the distance and direction of the ship to the fishing location is not yet known accurately. Fishers only rely on the experience and information from other fishers to find out the location of fish distribution, and this will cause boat fuel losses because of the uncertain goals. In this research will shown the making process of the design of mobile navigation applications to find the location of the fish distribution. The device works based on information data in the form of latitude and longitude data from the Center for Marine Research and Observation. By entering the fish distribution data, the distance and direction of the location can be known. Android mobile application called Mobile Virtual Assistant (MVA) works by using smartphone GPS data, maps, and gyroscope compass sensors to locate fish distribution and data analysis will be compared with the Android application "Polaris Navigation" to find out the coordinates. From 10 tests, the Android Virtual Mobile Assistant application successfully headed to the destination location with a different accuracy of 24 meters from the Mobile Navigation Apps coordinate point detector. So it can be concluded that the android mobile application that is made can read the coordinates accurately.

Student Chat Box Android App for College Related Activity

Statistics show that more than 80 applications are installed on each android smartphone. Vulnerability research on Android applications is of critical importance. Recently, academic researchers mainly focus on single bug patterns, while few of them investigate the relations between multiple bugs. Industrial researchers proposed a series of logic exploit chains leveraging multiple logic bugs. However, there is no general model to evaluate the chaining abilities between bugs. This paper presents a formal model to elucidate the relations between multiple bugs in Android applications. To prove the effectiveness of the model, we design and implement a prototype system named AppChainer. AppChainer automatically identifies attack surfaces of Android applications and investigates whether the payloads entering these attack surfaces are “chainable”. Experimental results on 2138 popular Android applications show that AppChainer is effective in identifying and chaining attacker-controllable payloads. It identifies 14467 chainable payloads and constructs 5458 chains both inside a single application and among various applications. The time cost and resource consumption of AppChainer are also acceptable. For each application, the average analysis time is 317 s, and the average memory consumed is 2368 MB. Compared with the most relevant work Jandroid, the experiment results on our custom DroidChainBench show that AppChainer outperforms Jandroid at the precision rate and performs equally with Jandroid at the recall rate.

Programming environments for smartphones expose a concurrency model that combines multi-threading and asynchronous event-based dispatch. While this enables the development of efficient and feature-rich applications, unforeseen thread interleavings coupled with non-deterministic reorderings of asynchronous tasks can lead to subtle concurrency errors in the applications. In this paper, we formalize the concurrency semantics of the Android programming model. We further define the happens-before relation for Android applications, and develop a dynamic race detection technique based on this relation. Our relation generalizes the so far independently studied happens-before relations for multi-threaded programs and single-threaded event-driven programs. Additionally, our race detection technique uses a model of the Android runtime environment to reduce false positives. We have implemented a tool called DroidRacer. It generates execution traces by systematically testing Android applications and detects data races by computing the happens-before relation on the traces. We analyzed 15 Android applications including popular applications such as Facebook, Twitter and K-9 Mail. Our results indicate that data races are prevalent in Android applications, and that DroidRacer is an effective tool to identify data races.

As smart building becomes increasingly popular, it enables many interesting applications, such as smart lock, elderly monitoring and remote healthcare.This paper will introduce one sub-system in the smart building: smart power system.This smart power system consists of an Android application, a cloud server and a smart socket.In addition, human-device interaction methods in this system are studied.

Software metrics are created and used by the distinctive programming associations intended for assessing, guaranteeing program excellence, activity, and software recovery. Software metrics have turned into a basic part of programming growth and are utilized in each period of the product development life cycle. Software metrics essentially measure programming items like plan source code and help us in taking technical and administrative choices. The desire of this examination is to play out the relative investigation of static and dynamic metrics. In any case, software quality characteristics, for example, performance, execution time and dependability rely upon the dynamic exercises of the product artifact. Due to every one of these variables, we favor dynamic metrics instead of customary static metrics. With the assistance of customary static metrics, we are not capable to analyze different actualities of programming. There are various types of this OO static and dynamic equipments. In this paper we have played out a similar investigation of different OO static and dynamic metrics tools and find out the hybrid too is counted as best one extraction of both, static and dynamic characteristics from mobile Android applications. The source code and a Docker compartment is utilized by open source tool in only three phases pre-static, static and dynamic examination.

In the past few years, party has played a more and more important role in people's daily life. However, it is not that easy to organize a satisfying party, for the reason that the organizer must consider many details and every member's personal need. In order to help people with this kind of problem, a new and effective tool is needed and we think that an application can be a perfect solution. In this paper, we develop a new Android application, which simplifies the organizing of parties. We also design a specific recommendation algorithm, which helps to offer the organizer some suitable party places, based on people's previous choice, the position of the user, and the evaluations from some review sites. Moreover, using the database deployed on the cloud, our application provides convenience for party members to vote for time or places and for organizers to collect the voting information. The friendly user interface and the use of specific map API make the application more applicable.

We present a complete end-to-end dynamic analysis system for finding data races in mobile Android applications. The capabilities of our system significantly exceed the state of the art: our system can analyze real-world application interactions in minutes rather than hours, finds errors inherently beyond the reach of existing approaches, while still (critically) reporting very few false positives. Our system is based on three key concepts: (i) a thorough happens-before model of Android-specific concurrency, (ii) a scalable analysis algorithm for efficiently building and querying the happens-before graph, and (iii) an effective set of domain-specific filters that reduce the number of reported data races by several orders of magnitude. We evaluated the usability and performance of our system on 354 real-world Android applications (e.g., Facebook). Our system analyzes a minute of end-user interaction with the application in about 24 seconds, while current approaches take hours to complete. Inspecting the results for 8 large open-source applications revealed 15 harmful bugs of diverse kinds. Some of the bugs we reported were confirmed and fixed by developers.

With the tremendous increase of Android malware, we need an automatic way of collecting Android applications and identifying the malware before they get installed on the end-user devices. In this paper, we propose a honeyclient for Android applications that will collect and classify Android applications. We first present an overview of the honeyclient. Then, we survey the different ways of infecting Android mobile devices which will shed the light on the honeyclient’s design. Finally, we describe every component of the honeyclient, namely a crawler to build a list of suspicious URLs, a client to visit the suspicious URLs, extract Android applications and analyze them, and a malware detector to classify the collected Android applications. We use a light version of the Android browser to visit the suspicious URLs enabling us to scale the visits up and an Android emulator to analyze the Android applications. As for the malware detector, we use a combination of misuse and anomaly detector allowing us to detect already known malware and new variants.

Abstract: The Android application that can identify older people who may fall. Android is an operating system that Anyone can easily construct their own application on an open source platform. Families and medical experts are often concerned about older people falling. According to experts, falls are the seventh rank for death cause in the US. Adults 68 and older who fall untreated run the risk of major health problems because 21% of falls necessitate emergency medical attention and 11% of falls will result in the fractures. This is the rationale for the creation of a system for the elderly that can detect falls and alert the caregiver. The software keeps tabs on the person and notifies the caregiver if anything is wrong. This Android app's ability to send alarm messages to the caregiver with the necessary information is one of its important features. Important details like their geolocation and directions are included in the alert messages. The individual has the authority to put an end to a false alarm before taking any further action. This project is to help the elderly. Through a user-friendly interface, the smartphone application can spot possible falls and provide alerts to families, doctors, and other caregivers.

The number of applications on online mobile application stores is increasing\nat a rapid rate. Smart-phones are used by a wide range of people varying in\nage, and also in the ability to use a smart phone. With the increasing\ndependency on smart-phones, the paper aims to determine whether the popular\napplications on Google Play, the official store for Android applications, can\nbe used by people with vision impairment. The accessibility of the applications\nwas tested using an external keyboard, and TalkBack, an accessibility tool\ndeveloped by Google. It was found that several popular applications on the\nstore were not designed keeping accessibility in mind. It was observed that\nthere exists a weak positive relationship between the popularity of the\napplication and its accessibility. A framework is proposed that can be used by\ndevelopers to improve the accessibility of an application. The paper also\ndiscusses the programming aspects to be considered while developing an Android\napplication, so that the application can be used by sighted as well as visually\nimpaired users.\n