Testing in resource constrained execution environments

Software for resource constrained embedded devices is often implemented in the Java programming language because the Java compiler and virtual machine provide enhanced safety, portability, and the potential for run-time optimization. It is important to verify that a software application executes correctly in the environment in which it will normally execute, even if this environment is an embedded one that severely constrains memory resources. Testing can be used to isolate defects within and establish a confidence in the correctness of a Java application that executes in a resource constrained environment. However, executing test suites with a Java virtual machine (JVM) that uses dynamic compilation to create native code bodies can introduce significant testing time overheads if memory resources are highly constrained. This paper describes an approach that uses adaptive code unloading to ensure that it is feasible to perform testing in the actual memory constrained execution environment. The experiments demonstrate that code unloading can reduce both the test suite execution time by 34 % and the code size of the test suite and application under test by 78 % while maintaining the overall size of the JVM. Categories and Subject Descriptors: D.2.5 [Software Engineering]: Testing and Debugging-Testing tools; D.3.4 [Programming Languages]: Processors-code generation

Automatic Generation of Load Tests

Load tests aim to validate whether system performance is acceptable under peak conditions. Existing test generation techniques induce load by increasing the size or rate of the input. Ignoring the particular input values, however, may lead to test suites that grossly mischaracterize a system’s performance. To address this limitation we introduce a mixed symbolic execution based approach that is unique in how it 1) favors program paths associated with a performance measure of interest, 2) operates in an iterative-deepening beam-search fashion to discard paths that are unlikely to lead to high-load tests, and 3) generates a test suite of a given size and level of diversity. An assessment of the approach shows it generates test suites that induce program response times and memory consumption several times worse than the compared alternatives, it scales to large and complex inputs, and it exposes a diversity of resource consuming program behavior

Code Cache Management in Managed Language VMs to Reduce Memory Consumption for Embedded Systems

The compiled native code generated by a just-in-time (JIT) compiler in man- aged language virtual machines (VM) is placed in a region of memory called the code cache. Code cache management (CCM) in a VM is responsible to find and evict methods from the code cache to maintain execution correctness and manage program performance for a given code cache size or memory budget. Effective CCM can also boost program speed by enabling more aggressive JIT compilation, powerful optimizations, and improved hardware instruction cache and I-TLB per- formance. Though important, CCM is an overlooked component in VMs. We find that the default CCM policies in Oracle’s production-grade HotSpot VM perform poorly even at modest memory pressure. We develop a detailed simulation-based frame- work to model and evaluate the potential efficiency of many different CCM poli- cies in a controlled and realistic, but VM-independent environment. We make the encouraging discovery that effective CCM policies can sustain high program performance even for very small cache sizes. Our simulation study provides the rationale and motivation to improve CCM strategies in existing VMs. We implement and study the properties of several CCM policies in HotSpot. We find that in spite of working within the bounds of the HotSpot VM’s current CCM sub-system, our best CCM policy implementation in HotSpot improves program performance over the default CCM algorithm by 39%, 41%, 55%, and 50% with code cache sizes that are 90%, 75%, 50%, and 25% of the desired cache size, on average

어플리케이션 다운로딩 시스템을 위한 클라이언트 선행 컴파일러

학위논문 (박사)-- 서울대학교 대학원 : 전기·컴퓨터공학부, 2014. 8. 문수묵.어플리케이션(앱)을 다운로드 받아서 수행하는 시스템은 DTV나 스마트폰처럼 대중적으로 사용되고 있다. 앱을 다운받아서 사용하는 시스템들은 가상 머신을 주류로 사용하고 있다. 가상 머신의 가장 큰 문제점은 인터프리터를 통한 수행에 의한 느린 성능이며, 이 성능의 향상을 위해 주로 사용되는 기술이 적시 컴파일러이다. 적시 컴파일러는 다운받은 앱의 수행 중에 동적으로 머신 코드로 번역하여 사용하는 기법으로, 동적 컴파일레이션 오버헤드를 가지게 된다. 우리는 이 동적 컴파일레이션 오버헤드를 제거하여 성능을 향상시키는 클라이언트 선행 컴파일러를 제안하였다. 클라이언트 선행 컴파일러는 적시 컴파일러가 생성하는 머신 코드를 앱의 종료될 때 지우지 않고 파일형태로 스토리지에 저장하여 이후에 앱이 다시 수행될 때 저장한 머신 코드를 재활용하여 사용함으로써 런타임 컴파일레이션 오버헤드를 제거하게 된다. 저장한 머신 코드를 재활용할 때 머신 코드에 인코딩된 주소값들은 유효하지 않기 때문에 가상 머신의 현재 값에 맞추어 변경해주는 작업이 필요하다. 이 작업은 주소 재배치이다. 주소 재배치는 저장된 머신 코드만으로 수행할 수가 없기 때문에 추가적인 정보를 머신 코드를 저장하는 과정에서 생성하여 파일에 함께 저장해 주어야 한다. 자바의 상수 풀 해석은 주소 재배치 작업을 어렵게 한다. 우리는 이에 대한 해결책을 만들었다. 주소 재배치를 위한 정보들을 저장하기위해 영구 메모를 많이 사용하는 것도 문제가 된다. 따라서 우리는 주소 재배치 정보를 머신 코드 상에 인코딩하고 압축하여 저장하는 방법을 제안했다. 우리의 클라이언트 선행 컴파일러 기법은 오라클사의 CDC 가상머신 참조구현인 CVM에 구현하였다. 우리의 클라이언트 선행 컴파일러는 벤치마크의 성능을 약 12% 향상시켰다. 또한 우리는 클라이언트 선행 컴파일러 기법을 실제로 판매하는 DTV환경에 구축하여 실제 방송국이 사용하는 어플리케이션을 수행해 보았다. 우리의 클라이언트 선행 컴파일러 방식은 사용자의 실제 환경에서 33%의 좋은 성능 향상을 얻었다. 자바스크립트 가상머신인 구글사의 V8 가상머신은 인터프리터 수행없이 적시 컴파일러만을 사용하고 있다. 우리는 V8 가상 머신에 클라이언트 선행 컴파일러는 적용하였지만, 실제 성능 향상을 얻어내지는 못했다. 이것은 V8 가상 머신의 특징인 내부 객체의 적극적인 사용에 의한 결과이다. 내부 객체는 컴파일러가 생성하여 컴파일러 과정에서 사용되며, 자바스크립트 프로그램에서도 접근하여 사용하게 된다. V8 가상 머신의 컴포넌트들은 대부분 내부 객체로 생성되어, 다른 종류의 가상 머신에 비해서 상당히 많은 내부 객체를 생성하고 있다. V8의 적시 컴파일러가 생성하는 머신 코드에서는 이 내부 객체를 직접 접근하여 사용하게 되어, 클라이언트 선행 컴파일러에 의해 어플리케이션이 수행될 때마다 이 내부 객체는 항상 필요하기 때문에 클라이언트 선행 컴파일러는 내부 객체를 재생성해야만 한다. V8 적시 컴파일러의 런타임 컴파일레이션 오버헤드의 대부분이 내부 객체를 생성하는 오버헤드이기 때문에, 우리의 클라이언트 선행 컴파일러는 이 환경에서 충분한 성능 향상을 얻을 수 없었다.App-downloading systems like DTV and smart phone are popularly used. Virtual machine is mainstream for those systems. One critical problem of app-downloading systems is performance because app is executed by interpreter. A popular solution for improving performance is Just-In-Time Compiler (JITC). JITC compiles to machine code at runtime. So, JITC suffers from runtime compilation overhead. We suggested client Ahead-Of-Time Compiler(c-AOTC) which improves the performance by removing runtime compilation overhead. c-AOTC saves machine code of method generated by JITC in persistent storage and reuses it in next runs. The machine code of a method translated by JITC is cached on a persistent memory of the device, and when the method is invoked again in a later run of the program, the machine code is loaded and executed directly without any translation overhead. One major issue in c-AOTC is relocation because some of the address constants embedded in the cached machine code are not correct when the machine code is loaded and used in a different runthose addresses should be corrected before they are used. Constant pool resolution complicates the relocation problem, and we propose our solutions. The persistent memory overhead for saving the relocation information is also an issue, and we propose a technique to encode the relocation information and compress the machine code efficiently. We developed a c-AOTC on Oracles CDC VM, and evaluation results indicate that c-AOTC can improve the performance as much as an average of 12% for benchmarks. And we adopted c-AOTC approach to commercial DTV platform and test the real xlet applications of commercial broadcasting stations. c-AOTC got average 33% performance improvement on the real xlet application test. V8 JavaScript VM does not use interpreter. Apps are executed only by JITC. We adopted c-AOTC to V8 VM. But we cannot get any good performance result because of V8 VMs characteristics. V8 VM components are generated as internal objects. Internal objects are used for compiling and running of JavaScript program. The machine code of V8 VM addresses internal objects which are different for each run. Because internal objects be　accessed in each run, c-AOTC　must recreate those objects. Because most of compilation overhead of V8 VM is internal object creation overhead, c-AOTC　does not get enough improvements.Chapter 1 Introduction 1 Chatper 2 client-AOTC Approach 4 Chatper 3 Java Virtual Machine and Our JITC 9 3.1 Overview of JVM and the Bytecode 9 3.2 Our JITC on the CVM 14 Chatper 4 Design and Implementation of c-AOTC on JVM 16 4.1 Architecutre of the c-AOTC 16 4.2 Relocation 19 4.2.1 Translated Code Which Needs Relocation 19 4.2.2 Relocation Information and Relocation Process 22 4.2.3 Relocation for Inlined Methods 24 4.3 Reducing the Size of .aotc Files 25 4.3.1 Encoding Relocation Information 25 4.3.2 Machine Code Compression 27 4.3.3 Structure of the .aotc File 27 Chatper 5 c-AOTC for DTV JVM platform 29 5.1 DTV software platform 30 5.2 c-AOTC on the DTV 32 5.2.1 Design of c-AOTC on DTV 32 5.2.2 Relocation Problem 35 5.2.3 Example of Relocation 39 5.2.3.1 Relocation Example of JVM c-AOTC 39 5.2.3.3 Relocation Example of DTV c-AOTC 41 Chatper 6 c-AOTC for JavaScript VM 44 6.1 V8 JavaScript VM 44 6.2 Issue and Solution of c-AOTC on V8 JavaScript VM 46 Chatper 7 Experimental Results 51 7.1 Experimental Environment of JVM 51 7.2 Performance Impact of c-AOTC 53 7.3 Space Overhead of c-AOTC 55 7.4 Reducing Number of c-AOTC Methods 60 7.5 c-AOTC with new hot-spot detection heuristics 63 7.5.1 Performance Impact of c-AOTC with new hot-spotdetection heuristics 63 7.5.2 Space Overhead of c-AOTC with new hot-spot detection heuristics 67 7.6 c-AOTC of DTV JVM platform 70 7.6.1 Performance result of DTV platform 70 7.6.2 Analysis of JITCed method of DTV platform 72 7.6.3 Space overhead of DTV platform 74 7.6.4 c-AOTC overhead of DTV platform 75 7.6.5 c-AOTC performance using different xlets c-AOTC file in DTV platform 76 7.7 c-AOTC of V8 JavaScript engine 79 7.7.1 Compilation overhead on V8 JavaScript VM 79 7.7.2 Performance result on V8 JavaScript VM 81 7.7.3 Comparison with c-AOTC of JavaScriptCore VM 83 Chatper 8 Related Work 86 Chatper 9 Conclusion 89 Bibliography 91 초록 99Docto

Adaptive Code Unloading for Resource-Constrained JVMs

Compile-only JVMs for resource-constrained embedded systems have the potential for using device resources more efficiently than interpreter-only systems since compilers can produce significantly higher quality code and code can be stored and reused for future invocations. However, this additional storage requirement for reuse of native code bodies, introduces memory overhead not imposed in interpreter-based systems. In this paper, we present..

Source level debugging of dynamically translated programs

The capability to debug a program at the source level is useful and often indispensable. Debuggers usesophisticated techniques to provide a source view of a program, even though what is executing on the hard-ware is machine code. Debugging techniques evolve with significant changes in programming languagesand execution environments. Recently, software dynamic translation (SDT) has emerged as a new execu-tion mechanism. SDT inserts a run-time software layer between the program and the host machine, provid-ing flexibility in execution and program monitoring. Increasingly popular technologies that use thismechanism include dynamic optimization, dynamic instrumentation, security checking, binary translation,and host machine virtualization. However, the run-time program modifications in a SDT environment posesignificant challenges to a source level debugger. Currently debugging techniques do not exist for softwaredynamic translators. This thesis is the first to provide techniques for source level debugging of dynamically translatedprograms. The thesis proposes a novel debugging framework, called Tdb, that addresses the difficult chal-lenge of maintaining and providing source level information for programs whose binary code changes asthe program executes. The proposed framework has a number of important features. First, it does notrequire or induce changes in the program being debugged. In other words, programs are debugged is theirdeployment environment. Second, the framework is portable and can be applied to virtually any SDT sys-tem. The framework requires minimal changes to an SDT implementation, usually just a few lines of code.Third, the framework can be integrated with existing debuggers, such as Gdb, and does not require changesto these debuggers. This improves usability and adoption, eliminating the learning curve associated with anew debugging environment. Finally, the proposed techniques are efficient. The runtime overhead of thedebugged programs is low and comparable to that of existing debuggers. Tdb's techniques have been implemented for three different dynamic translators, on two differenthardware platforms. The experimental results demonstrate that source level debugging of dynamicallytranslated programs is feasible, and our implemented systems are portable, usable, and efficient

Unconventional Applications of Compiler Analysis

Previously, compiler transformations have primarily focused on minimizing program execution time. This thesis explores some examples of applying compiler technology outside of its original scope. Specifically, we apply compiler analysis to the field of software maintenance and evolution by examining the use of global data throughout the lifetimes of many open source projects. Also, we investigate the effects of compiler optimizations on the power consumption of small battery powered devices. Finally, in an area closer to traditional compiler research we examine automatic program parallelization in the form of thread-level speculation

Proceedings of the 4th International Conference on Principles and Practices of Programming in Java

This book contains the proceedings of the 4th international conference on principles and practices of programming in Java. The conference focuses on the different aspects of the Java programming language and its applications