TOAST: Automated Testing of Object Transformers in Dynamic Software Updates

Dynamic software update(DSU)patches programs on the fly.It often involves the critical task of object transformation that converts live objects of the old-version program to their semantically consistent counterparts under the new-version program.This task is accomplished by invoking an object transformer on each stale object.However,a defective transformer failing to maintain consistency would cause errors or even crash the program.We propose TOAST(Test Object trAnSformaTion),an automated approach to detecting potential inconsistency caused by object transformers.TOAST first analyzes an update to identify multiple target methods and then adopts a fuzzer with specially designed inconsistency guidance to randomly generate object states to drive two versions of a target method.This creates two corresponding execution traces and a pair of old and new objects.TOAST finally performs object transformation to create a transformed object and detects inconsistency between it and the corresponding new object produced from scratch by the new program.Moreover,TOAST checks behavior inconsistency by comparing the return variables and exceptions of the two executions.Experimental evaluation on 130 updates with default transformers shows that TOAST is promising:it got 96.0%precision and 85.7%recall in state inconsistency detection,and 81.4%precision and 94.6%recall in behavior inconsistency detection.The inconsistency guidance improved the fuzzing efficiency by 14.1%for state inconsistency detection and 40.5%for behavior inconsistency detection.

GridDroid--An Effective and Efficient Approach for Android Repackaging Detection Based on Runtime Graphical User Interface

Repackaging brings serious threats to Android ecosystem.Software birthmark techniques are typically applied to detect repackaged apps.Birthmarks based on apps'runtime graphical user interfaces(GUI)are effective,especially for obfuscated or encrypted apps.However,existing studies are time-consuming and not suitable for handling apps in large scale.In this paper,we propose an effective yet efficient dynamic GUI birthmark for Android apps.Briefly,we run an app with automatically generated GUI events and dump its layout after each event.We divide each dumped layout into a grid,count in each grid cell the vertices of boundary rectangles corresponding to widgets within the layout,and generate a feature vector to encode the layout.Similar layouts are merged at runtime,and finally we obtain a graph as the birthmark of the app.Given a pair of apps to be compared,we build a weighted bipartite graph from their birthmarks and apply a modified version of the maximum-weight-bipartite-matching algorithm to determine whether they form a repackaging pair(RP)or not.We implement the proposed technique in a prototype,GridDroid,and apply it to detect RPs in three datasets involving 527 apks.GridDroid reports only six false negatives and seven false positives,and it takes GridDroid merely 20 microseconds on average to compare a pair of birthmarks.

Co-simulation and Experimental Study for Wingspan of Flapping Wing Micro Aerial Vehicle

The 3D model of flapping wing mechanism and veins is constructed in 3D computer aided design (CAD) software UG.Then the co-simulation model is established by using multibody dynamics software ADAMS and MATLAB.The validation of this co-simulation model is verified by comparing the simulation results with final experiments.The simulation results and experiments reveal that the relation between flapping frequency and driving voltage of motor is approximately linear under various wingspans.The variance of flapping frequency among different wingspans augments gradually with increasing voltage.Furthermore,the simulation results suggest that flapping frequency is sensitive to wingspan and decreases with increasing wingspan of veins,and the relation between flapping frequency and moment of inertia of veins is also approximately linear for various voltages.