DC microgrids are gaining popularity due to high efficiency, high reliability and easy interconnection of renewable sources as compared to ac system. Control objectives of dc microgrid are: (i) ensure equal load sharing (in per unit) among sources and (ii) maintain low voltage regulation of the system. Conventional droop controllers are not effective in achieving both the aforementioned objectives simultaneously. Reasons for this are identified to be the error in nominal voltages and load distribution. Though centralized controller achieves these objectives, it requires high speed communication and offers less reliability due to single point of failure. To address these limitations, this paper proposes a new decentralized controller for dc microgrid. Key advantages are high reliability, low voltage regulation and equal load sharing, utilizing low bandwidth communication. To evaluate the dynamic performance, mathematical model of the scheme is derived. Stability of the system is evaluated by eigenvalue analysis. The effectiveness of the scheme is verified through detailed simulation study. To confirm the viability of the scheme, experimental studies are carried out on a laboratory prototype developed for this purpose. Controller Area Network (CAN) protocol is utilized to achieve communication between the sources.

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We present an algorithm and a system for generating input events to exercise smartphone apps. Our approach is based on concolic testing and generates sequences of events automatically and systematically. It alleviates the pathexplosion problem by checking a condition on program executions that identifies subsumption between different event sequences. We also describe our implementation of the approach for Android, the most popular smartphone app platform, and the results of an evaluation that demonstrates its effectiveness on five Android apps.

Many microorganisms, including spermatozoa and forms of bacteria, oscillate or twist a hairlike flagella to swim. At this small scale, where locomotion is challenged by large viscous drag, organisms must generate time-irreversible deformations of their flagella to produce thrust. To date, there is no demonstration of a self propelled, synthetic flagellar swimmer operating at low Reynolds number. Here we report a microscale, biohybrid swimmer enabled by a unique fabrication process and a supporting slender-body hydrodynamics model. The swimmer consists of a polydimethylsiloxane filament with a short, rigid head and a long, slender tail on which cardiomyocytes are selectively cultured. The cardiomyocytes contract and deform the filament to propel the swimmer at 5-10 mm s À 1 , consistent with model predictions. We then demonstrate a two-tailed swimmer swimming at 81 mm s À 1 . This small-scale, elementary biohybrid swimmer can serve as a platform for more complex biological machines.

Abstract. We discuss how to perform symbolic execution of large programs in a manner that is both compositional (hence more scalable) and demand-driven. Compositional symbolic execution means finding feasible interprocedural program paths by composing symbolic executions of feasible intraprocedural paths. By demand-driven, we mean that as few intraprocedural paths as possible are symbolically executed in order to form an interprocedural path leading to a specific target branch or statement of interest (like an assertion). A key originality of this work is that our demand-driven compositional interprocedural symbolic execution is performed entirely using first-order logic formulas solved with an off-the-shelf SMT (Satisfiability-Modulo-Theories) solver -no procedure in-lining or custom algorithm is required for the interprocedural part. This allows a uniform and elegant way of summarizing procedures at various levels of detail and of composing those using logic formulas.We have implemented a prototype of this novel symbolic execution technique as an extension of Pex, a general automatic testing framework for .NET applications. Preliminary experimental results are encouraging. For instance, our prototype was able to generate tests triggering assertion violations in programs with large numbers of program paths that were beyond the scope of non-compositional test generation.

We present Apposcopy, a new semantics-based approach for identifying a prevalent class of Android malware that steals private user information. Apposcopy incorporates (i) a highlevel language for specifying signatures that describe semantic characteristics of malware families and (ii) a static analysis for deciding if a given application matches a malware signature. The signature matching algorithm of Apposcopy uses a combination of static taint analysis and a new form of program representation called Inter-Component Call Graph to efficiently detect Android applications that have certain control-and data-flow properties. We have evaluated Apposcopy on a corpus of real-world Android applications and show that it can effectively and reliably pinpoint malicious applications that belong to certain malware families.

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Abstract. We present JPF-SE, an extension to the Java PathFinder Model Checking framework (JPF) that enables the symbolic execution of Java programs. JPF-SE uses JPF to generate and explore symbolic execution paths and it uses off-the-shelf decision procedures to manipulate numeric constraints.