ARC Rules

Many Java programmers believe they do not have to worry about memory management because of automatic garbage collection. In fact, many Java programs run out of memory unexpectedly after performing a number of operations. A memory leak in Java is caused when an object that is no longer needed cannot be reclaimed because another object is still referring to it. Memory leaks can be difficult to solve, since the complexity of most programs prevents us from manually verifying the validity of every reference. In this paper we show a new methodology for finding the causes of memory leaks. We have identified a basic memory leak scenario which fits many important cases. In this scenario, we allow the programmer to identify a period of time in which temporary objects are expected to be created and released. Using this information we are able to identify objects that persist beyond this period and the references which are holding on to them. Scaling this methodology to real-world systems brings additional challenges. We propose a novel combination of visual syntax and reference pattern extraction to manage this additional complexity. We also describe how these techniques can be applied to a wider class of memory problems, including the exploration of large data structures. These techniques have been implemented and have been proven successful on large projects.

The use of a managed, type-safe languages such as Java in real-time and embedded systems can offer productivity and, in particular, safety and dependability benefits over the dominating unsafe languages at reasonable costs. A JVM that has dynamic memory-management needs to provide an implicit memory-management strategy, that is, for example, a garbage collector (GC) or stack allocation provided by the escape analysis of the JVM's compiler: Explicit management of dynamically allocated memory (i.e., by use of functions such as C's malloc() and free()) is vulnerable to programming errors such as neglected or false memory release operations causing memory leaks or dangling pointers. Such operations have the potential to break the soundness of the type system and are therefore usually not available for strongly typed languages. Type-safe languages in combination with static analyses -- which respect hardware as well as system-specific information -- can efficiently be employed to provide a runtime system including memory management (MM) that is specifically suited to an embedded application on a particular hardware device. In the context of this paper, we present novel memory-management strategy we implemented in our KESO JVM. It is a latency-aware garbage-collection algorithm called LAGC. Also, we introduce the static analyses that can assist LAGC. The application developers have to ensure that there is enough time for the GCs to run. Hardware characteristics such as soft-error proneness of the hardware or the memory layout can also be taken into consideration as demanded by the system configuration. This is achieved by integrating the GCs in the design process of the whole system just as any other user application, which is the reason why this approach is called cooperative memory management. The suggested strategies require reasonably low overhead.

This chapter sets out to examine the discourses surrounding the 2009 ratification of the Lisbon Treaty and the consequent processes of Othering and the construction of British national identities. As in the previous chapters, the primary sources utilised in constructing the various discourses and the subsequent contending identities are listed in Appendix 3. As shown in the descriptive account as well as Tables 4.1 and 4.2, the numbers next to each quotation represent the source in the appendix. As also in the previous chapters, quotations marks have either been given in the original source or are quotes of quotations. Unlike the previous empirical chapters, memoirs and biographies have not been used. This is because the event is too contemporary to have been included in many political biographies. The sources that have been utilised, however, can be categorised as follows. Firstly, as before, I make use of the general election manifestoes of the Conservative, Labour and Liberal Democrat parties in the May 2005 general elections. Despite being published three years before the Lisbon Treaty, the manifestoes highlight the political elite attitudes towards Europe and are subsequently important as a vehicle within which identity issues are thrashed out. In addition, I have also included the manifesto of the United Kingdom Independence Party (UKIP) as this party was particularly vocal in the run-up to the adoption of the Lisbon Treaty and had won 12 MEPs in the 2004 European Elections.KeywordsMember StateNational IdentityBovine Spongiform EncephalopathyPrevious ChapterFree Trade AreaThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Memory management is one of the most boring topics in database research. It plays a minor role in tasks like free-space management or efficient space usage. Here and there we also realize its impact on database performance when worrying about NUMA-aware memory allocation, data compacting, snapshotting, and defragmentation. But, overall, let's face it: the entire topic sounds as exciting as 'garbage collection' or 'debugging a program for memory leaks'. What if there were a technique that would promote memory management from a third class helper thingie to a first class citizen in algorithm and systems design? What if that technique turned the role of memory management in a database system (and any other data processing system) upside-down? What if that technique could be identified as a key for re-designing various core algorithms with the effect of outperforming existing state-of-the-art methods considerably? Then we would write this paper. We introduce RUMA: Rewired User-space Memory Access. It allows for physiological data management, i.e. we allow developers to freely rewire the mappings from virtual to physical memory (in user space) while at the same time exploiting the virtual memory support offered by hardware and operating system. We show that fundamental database building blocks such as array operations, partitioning, sorting, and snapshotting benefit strongly from RUMA.

Garbage collectors automatically free memory previously allocated by applications. Generally, they discard unreachable objects from memory, leaving reachable objects intact. However, object reachability does not necessarily imply usability, as an object may be obsolete and still reachable. Such objects are usually referred to as loitering objects. Loitering objects introduce a form of memory leak in a Java application. Predicting, tracing and eliminating loitering objects is a difficult problem. In this paper we address this problem. We present a self-healing approach for dealing with loitering objects. Specifically, the paper proposes an algorithm that can be integrated within the Java garbage collector. The algorithm prevents memory leaks resulting from loitering objects by "paging" suspected live objects to disk and reloading them if they are required. As a proof-of-concept, we have implemented and validated the algorithm for the Java Virtual Machine. This could be a first step towards genuine self-healing of memory management problems.

Java is one of the languages that are popular for high abstraction and automatic memory management. As in other object-oriented languages, Java's objects can easily represent a domain model of an application. While it has a positive impact on the design, implementation and maintenance of applications, there are drawbacks as well. One of them is a relatively high memory overhead to manage objects. In this work, we show our experience with searching for this problem in an application that we refactored to use less memory. Although the application was relatively well designed with no memory leaks, it required such a big amount of memory that for large data the application was not usable in reality. We did three relatively simple improvements: we reduced the usage of Java Collections, removed unnecessary object instances, and simplified the domain model, which reduced memory needs up to 88% and made the application better usable and even faster. This work is a case-study reporting results. Moreover, the employed ideas are formulated as a set of antipatterns, which may be used for other applications.

Both managed and native languages use memory safety techniques to ensure program correctness and as a security defense. A critical element of memory safety is to initialize newly allocated memory to zero before making it available to the program. In this thesis I explore the performance impact of zero initialization and show that it comes with a substantial overhead. I also show that this overhead can be largely removed with new designs that exploit both the language semantics of zero initialization and the hardware semantics of memory hierarchies Programmers increasingly choose managed languages to develop large scale applications. One of the reasons is that managed languages offer automatic memory management (garbage collection), which protects against memory leaks and dangling pointers. Garbage collection encourages programs to allocate large numbers of small and medium size objects, leading to significant overheads of zero initializing objects — on average the direct cost of zeroing is 4% to 6% and up to 50% of total application time on a variety of modern processors. Zeroing incurs indirect costs as well, which include memory bandwidth consumption and cache displacement. Existing virtual machines (VMs) either: a) minimize direct costs by zeroing in large blocks, or b) minimize indirect costs by integrating zeroing into the allocation sequence to reduce cache displacement. This thesis first describes and evaluates zero initialization costs and the two existing designs. The microarchitectural analysis of prior designs inspires two better designs that exploit concurrency and non-temporal cache-bypassing store instructions to reduce the direct and indirect costs simultaneously. The best strategy is to adaptively choose between the two new designs based on CPU utilization. This approach improves over widely used hot-path zeroing by 3% on average and up to 15% on the newest Intel i7-2600 processor, without slowing down any of the benchmarks. These results indicate that zero initialization is a surprisingly important source of overhead in existing VMs and that our new software strategies are effective at reducing this overhead. These findings also invite other optimizations, including software elision of zeroing and microarchitectural support.

A new algorithm is presented that automatically uncovers memory errors such as NULL pointers dereference and memory leaks in C programs. The algorithm is conservative, i.e., it can never miss an error but may report “false alarms”. When applied to several intricate C programs manipulating singly linked lists, the new algorithm yields more accurate results, does not report any false alarm and usually runs even faster and consumes less space than a less precise algorithm.KeywordsFalse AlarmLinked ListShape NodeShape GraphMemory LeakageThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Ada Gem #79 --- A number of tools and libraries exist to monitor memory usage, detect memory leaks and more generally solve issues with memory management. The Gems in this three-part series offer an overview of these issues and explain how you can benefit from these tools in your own development.

At the beginning of computer science memory management was a big issue with applications requiring to fit in the small amount of available memory (close to a few kilobytes). Hardware evolution has made this resource cheap for the past few years. Available memory is now close to a few hundred gigabytes. But the current evolution in the multi/many-core era tends to make some issues come back. The memory available tends not to follow the increasing number of cores making the memory resource per thread rare again. We also encounter new issues with the requirement to manage a bigger space with many more allocated objects. This new aspect increases the probability of memory leaks. It also increases the probability of memory management performance issues. Hence, with MALT we provide a tool to track the memory allocated by an application. We then map the extracted metrics onto the source code, just like kcachegrind does with valgrind for the CPU performance. Compared to most available tools, MALT can also be used to track potential performance losses due to bad allocation patterns (too many allocations, small allocations, recycling large allocations, short-lived allocations...) thanks to the various metrics it exposes to the user. This paper will detail the metrics extracted by MALT and how we present them to the user thanks to a nice web based graphical interface which is missing with most of the available Linux tools.

Go is a concurrent, garbage-collected, statically typed programming language that was developed at Google in 2009. Because of its straightforward, effective, and low learning curve, it is a well-liked option for developing online applications, command-line tools, and scalable network services. Garbage collection, which takes care of memory management automatically for you, is another key component of Go. As a result, there is no longer a requirement for manual memory management, which lowers the possibility of memory leaks and other issues. But it does come with a cost, as the Garbage collector takes CPU and Memory. In this paper, we will run some performance analysis with different GOGC options.

Many programming languages have a system of garbage collection to automate memory management. Problems such as unexpected memory leak still may occur due to the automation of memory management. Weak reference has been proposed as a solution to such problems. However, the use of weak reference often requires consideration of memory release timing, which is difficult for developers. In this study, we investigate the use of weak reference on open source projects. More concretely, we investigated the domain of software projects where the weak reference was used, the timing of the introduction of the weak reference, the usage method, the presence or absence of the test code for weak reference, and the case of failure to introduce weak reference in the Java language. The survey showed that weak references were used in 73 repositories, about one-third of the total 202 repositories, and that weak references were most common in test code.

The ultimate goal of our study is to obtain suggestions for the development of devices capable of the automatic modeling of natural phenomena. It is therefore of fundamental importance to develop a theoretical basis for the description of their optimal performance. In the previous chapters it was stated that an empirical modeling of natural phenomena includes three main tasks: Estimation, storage, and application of a probability distribution. Each of these tasks can be optimized by using the methods described in the previous chapter. The aim of this section is to present the problems and the solutions related with an optimal storage of empirical information about a continuous probability distribution in a system comprised of a finite number of discrete memory units. Such a system can be considered as a basic building block of an automatic modeler of natural phenomena. For example, we can imagine the brain of a biological organism or the digital memory of a computer that continually obtains signals from its surroundings and it optimally stores the corresponding empirical information. The first problem is the estimation of the probability density function of a continuous variable from the empirical data. We have already seen that this can be solved using Parzen’s window. [2] The second problem is the storage of the continuous probability density in a discrete system. This task is generally related with a loss of information and thus the question arises, how one can minimize this loss.KeywordsWindow FunctionExcited NeuronReference VectorDiscrete Random VariableMemory UnitThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

In light of the changing conditions for contemporary academic practice drawn out in the previous chapter, I want to conclude this account of key cultural studies voices by considering a writer who for the great bulk of her career remained suspicious of university affiliation (not to mention the dominant mode of cultural studies practice). Closing this book reflecting on the trajectory of Australian critic Meaghan Morris I am not only paying respect to the feminist ideas which inflect my own approach to cultural studies, I seek to contemplate both the possibilities and challenges Morris indicates for the future of cultural studies and its university location. To the extent that Morris moves towards an association with academia, I will suggest the arguments she makes in choosing this professional path can be seen as further indication of the very different forms of intellectual practice now welcome in the contemporary university. While my previous chapter may have paid an inordinate amount of attention to the problems affecting cultural studies’ location in an increasingly corporatised university, Morris’s perspective balances these realities with a historically mindful assessment of the new opportunities these changes make possible — particularly for women, whose participation in university life has always been subject to others’ discretion.KeywordsCultural StudyAcademic PracticeScholarly DiscourseSpeaking PositionScholarly PracticeThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

In the analysis of copula constructions that I have presented in the previous Chapter, copula be adds nothing to the meaning of the sentence in which it occurs. It denotes the identity function on predicates, λ E.E, and its semantic ‘contribution’ to the VP it heads is limited to the fact that if its complement is an argument DP, it triggers a type-shifting operation which raises the DP from type d to type <e,t>. Instead its contribution is structural. The copula is a V which heads a VP syntactic predicate, which is a constituent at which predicate formation occurs. The complement of be is interpreted as an expression with a free x variable, denoting a set of events. As we saw in the derivations in examples (15) and (27) in the previous Chapter, predicate formation at the VP level introduces a λ,-operator which binds the x variable (in both predicative and identity sentences), thus allowing the constituent to be predicated of the subject. The Hebrew inflectional copula, discussed in Chapter 8, also need make no independent semantic contribution, and similarly denotes the identity function on expressions, but at type <d, <e,t> >. It also triggers a type raising Operation from d → < d, < e,t > > in its complement in identity (equative) sentences.KeywordsMass NounCount NounSmall ClauseVerbal PredicateNominal DomainThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.