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An Algebraic Circuit for a multivariate polynomial P is a computational model for constructing the polynomial P using only additions and multiplications. It is a syntactic model of computation, as opposed to the Boolean Circuit model, and hence lower bounds for this model are widely expected to be easier to prove than lower bounds for Boolean circuits. Despite this, we do not have superpolynomial lower bounds against general algebraic circuits of depth 3 (except over constant-sized finite fields) and depth 4 (over any field other than F2), while constant-depth Boolean circuit lower bounds have been known since the early 1980s. In this paper, we prove the first superpolynomial lower bounds against algebraic circuits of all constant depths over all fields of characteristic 0. We also observe that our super-polynomial lower bound for constant-depth circuits implies the first deterministic sub-exponential time algorithm for solving the Polynomial Identity Testing (PIT) problem for all small-depth circuits using the known connection between algebraic hardness and randomness. [ABSTRACT FROM AUTHOR]

The paper discusses algorithmic priority inversion in mission-critical machine inference pipelines used in modern neural-network-based perception subsystems and describes a solution to mitigate its effect. In general, priority inversion occurs in computing systems when computations that are "less important" are performed together with or ahead of those that are "more important." Significant priority inversion occurs in existing machine inference pipelines when they do not differentiate between critical and less critical data. We describe a framework to resolve this problem and demonstrate that it improves a perception system's ability to react to critical inputs, while at the same time reducing platform cost. [ABSTRACT FROM AUTHOR]

The article discusses a research paper that applies online resource allocation algorithms to refugee resettlement, aiming to improve refugees' integration into local communities and employment prospects. By utilizing concepts from algorithm design, such as balancing resource utilization and maintaining capacity for future refugees, the authors were able to enhance the employability metric for resettlement agencies like the Hebrew Immigrant Aid Society (HIAS) by approximately 10%. This research not only addresses critical societal issues but also highlights the potential of algorithms to positively impact real-world outcomes for vulnerable populations, encouraging collaboration between algorithm designers and practitioners on important societal problems.

Recommender systems personalize content by recommending items to users. Item recommendation algorithms are evaluated by metrics that compare the positions of truly relevant items among the recommended items. To speed up the computation of metrics, recent work often uses sampled metrics where only a smaller set of random items and the relevant items are ranked. This paper investigates such sampled metrics in more detail and shows that they are inconsistent with their exact counterpart, in the sense that they do not persist relative statements, for example, recommender A is better than B, not even in expectation. Moreover, the smaller the sample size, the less difference there is between metrics, and for very small sample size, all metrics collapse to the AUC metric. We show that it is possible to improve the quality of the sampled metrics by applying a correction, obtained by minimizing different criteria. We conclude with an empirical evaluation of the naive sampled metrics and their corrected variants. To summarize, our work suggests that sampling should be avoided for metric calculation, however if an experimental study needs to sample, the proposed corrections can improve the quality of the estimate. [ABSTRACT FROM AUTHOR]

The Burrows-Wheeler Transform (BWT) is an invertible text transformation that permutes symbols of a text according to the lexicographical order of its suffixes. BWT is the main component of popular lossless compression programs (such as bzip2) as well as recent powerful compressed indexes (such as the r-index7), central in modern bioinformatics. The compressibility of BWT is quantified by the number r of equal-letter runs in the output. Despite the practical significance of BWT, no nontrivial upper bound on r is known. By contrast, the sizes of nearly all other known compression methods have been shown to be either always within a polylog n factor (where n is the length of the text) from z, the size of Lempel--Ziv (LZ77) parsing of the text, or much larger in the worst case (by an nε factor for ε > 0). In this paper, we show that r = O (z log² n) holds for every text. This result has numerous implications for text indexing and data compression; in particular: (1) it proves that many results related to BWT automatically apply to methods based on LZ77, for example, it is possible to obtain functionality of the suffix tree in O (z polylog n) space; (2) it shows that many text processing tasks can be solved in the optimal time assuming the text is compressible using LZ77 by a sufficiently large polylog n factor; and (3) it implies the first nontrivial relation between the number of runs in the BWT of the text and of its reverse. In addition, we provide an O (z polylog n)-time algorithm converting the LZ77 parsing into the run-length compressed BWT. To achieve this, we develop several new data structures and techniques of independent interest. In particular, we define compressed string synchronizing sets (generalizing the recently introduced powerful technique of string synchronizing sets11) and show how to efficiently construct them. Next, we propose a new variant of wavelet trees for sequences of long strings, establish a nontrivial bound on their size, and describe efficient construction algorithms. Finally, we develop new indexes that can be constructed directly from the LZ77 parsing and efficiently support pattern matching queries on text substrings. [ABSTRACT FROM AUTHOR]

In this paper, we describe multi-itinerary optimization (MIO)--a novel Bing Maps service that automates the process of building itineraries for multiple agents while optimizing their routes to minimize travel time or distance. MIO can be used by organizations with a fleet of vehicles and drivers, mobile salesforce, or a team of personnel in the field, to maximize workforce efficiency. It supports a variety of constraints, such as service time windows, duration, priority, pickup and delivery dependencies, and vehicle capacity. MIO also considers traffic conditions between locations, resulting in algorithmic challenges at multiple levels (e.g., calculating time-dependent travel-time distance matrices at scale and scheduling services for multiple agents). To support an end-to-end cloud service with turnaround times of a few seconds, our algorithm design targets a sweet spot between accuracy and performance. Toward that end, we build a scalable approach based on the ALNS metaheuristic. Our experiments show that accounting for traffic significantly improves solution quality: MIO finds efficient routes that avoid late arrivals, whereas traffic-agnostic approaches result in a 15% increase in the combined travel time and the lateness of an arrival. Furthermore, our approach generates itineraries with substantially higher quality than a cutting-edge heuristic (LKH), with faster running times for large instances. [ABSTRACT FROM AUTHOR]

The threshold theorem is a seminal result in the field of quantum computing asserting that arbitrarily long quantum computations can be performed on a faulty quantum computer provided that the noise level is below some constant threshold. This remarkable result comes at the price of increasing the number of qubits (quantum bits) by a large factor that scales polylogarithmically with the size of the quantum computation we wish to realize. Minimizing the space overhead for fault-tolerant quantum computation is a pressing challenge that is crucial to benefit from the computational potential of quantum devices. In this paper, we study the asymptotic scaling of the space overhead needed for fault-tolerant quantum computation. We show that the polylogarithmic factor in the standard threshold theorem is in fact not needed and that there is a fault-tolerant construction that uses a number of qubits that is only a constant factor more than the number of qubits of the ideal computation. This result was conjectured by Gottesman who suggested to replace the concatenated codes from the standard threshold theorem by quantum error-correcting codes with a constant encoding rate. The main challenge was then to find an appropriate family of quantum codes together with an efficient classical decoding algorithm working even with a noisy syndrome. The efficiency constraint is crucial here: bear in mind that qubits are inherently noisy and that faults keep accumulating during the decoding process. The role of the decoder is therefore to keep the number of errors under control during the whole computation. On a technical level, our main contribution is the analysis of the small-set-flip decoding algorithm applied to the family of quantum expander codes. We show that it can be parallelized to run in constant time while correcting sufficiently many errors on both the qubits and the syndrome to keep the error under control. These tools can be seen as a quantum generalization of the bit-flip algorithm applied to the (classical) expander codes of Sipser and Spielman. [ABSTRACT FROM AUTHOR]

Memory leaks in web applications are pervasive and difficult to debug. Leaks degrade responsiveness by increasing garbage collection costs and can even lead to browser tab crashes. Previous leak detection approaches designed for conventional applications are ineffective in the browser environment. Tracking down leaks currently requires intensive manual effort by web developers, which is often unsuccessful. This paper introduces BLeak (Browser Leak debugger), the first system for automatically debugging memory leaks in web applications. BLeak’s algorithms leverage the observation that in modern web applications, users often repeatedly return to the same (approximate) visual state (e.g., the inbox view in Gmail). Sustained growth between round trips is a strong indicator of a memory leak. To use BLeak, a developer writes a short script (17–73 LOC on our benchmarks) to drive a web application in round trips to the same visual state. BLeak then automatically generates a list of leaks found along with their root causes, ranked by return on investment. Guided by BLeak, we identify and fix over 50 memory leaks in popular libraries and apps including Airbnb, AngularJS, Google Analytics, Google Maps SDK, and jQuery. BLeak’s median precision is 100%; fixing the leaks it identifies reduces heap growth by an average of 94%, saving from 0.5MB to 8MB per round trip. [ABSTRACT FROM AUTHOR]

An important problem in terrain analysis is modeling how water flows across a terrain and creates floods by filling up depressions. In this paper, we study a number of flood-risk related problems: given a terrain Σ, represented as a triangulated xy-monotone surface with n vertices, a rain distribution, and a volume of rain ψ, determine which portions of Σ are flooded. We give an overview of efficient algorithms for these problems as well as explore the efficacy and efficiency of these algorithms on real terrains. [ABSTRACT FROM AUTHOR]

The article addresses the topic of algorithm design in the solid-state drive (SSD) model of computation, noting its limitations as well as its benefits. The author references an accompanying paper which addresses one shortcoming in particular -- the phenomenon of "write amplification" -- by proposing a more accurate theoretical model of SSDs that incorporates read, write and erase operations.

The article discusses the development of the algorithm known as norms to address the statistic problem known as nearest neighbor, referencing papers in the "Annual Symposium on Foundations of Computer Science" and "Proceedings of the ACM Symposium on Theory of Computing" journals. An overview of researchers' designing of normed spaces is provided. The uses of data analysis and expander graphs, including in regard to measuring the distance from data points, are discussed.

This paper consists of three interrelated parts. In the first part forms are introduced as an. abstraction and generalization of business paper forms. A set of facilities for the manipulation of forms and their contents is Out-Lined. Forms can be created, stored, found, viewed in different media, mailed, and located by office workers. Data on forms can also be processed in a completely integrated way. The facilities are discussed both abstractly and in relation to a prototype system. In the second part a faculty is outlined for the specification and implementation of automatic form procedures. These procedures specify actions on forms which are triggered automatically when certain preconditions are met. The preconditions, actions, and specification method are based on forms. The discussion is centered on our implementation of such a specification framework. Finally, in the third part, techniques for the analysis of office flow are specified. An algorithm is outlined for the categorization of forms into classes depending on the local routing and actions on the forms. In this way, we can obtain the paths that forms take and analyze the system for correctness and loading characteristics. [ABSTRACT FROM AUTHOR]

This paper provides performance results using the SPERRY UNIVAC 1100 Series linear programming product FMPS to solve a set of 16 real-world linear programming problems. As such, this paper provides a data point for the actual performance of a commercial simplex algorithm on real-world linear programming problems and shows that the simplex algorithm is a linear time algorithm in actual performance. Correlations and performance relationships not previously available are also provided. [ABSTRACT FROM AUTHOR]

Most results in the field of algorithm design are single algorithms that solve single problems. In this paper we discuss multidimensional divide-anti-conquer, an algorithmic paradigm that can be instantiated in many different ways to yield a number of algorithms and data structures for multidimensional problems. We use this paradigm to give best-known solutions to such problems as the ECDF, maximal range searching, closest pair, and all nearest neighbor problems The contributions of the paper are on two levels. On the first level are the particular algorithms and data structures given by applying the paradigm. On the second level is the more novel contribution of this paper a detailed study of an algorithmic paradigm that is specific enough to be described precisely yet general enough to solve a wide variety of problems. [ABSTRACT FROM AUTHOR]

Optimal decision table conversion has been tackled in the literature using two approaches, dynamic programming and branch-and-bound. The former technique is quite effective, but its time and space requirements are independent of how "easy" the given table is. Furthermore, it cannot be used to produce good, quasioptimal solutions. The branch-and-bound technique uses a good heuristic to direct the search, but is cluttered up by an enormous search space, since the number of solutions increases with the number of test variables according to a double exponential. In this paper we suggest a heuristically guided top-down search algorithm which, like dynamic programming, recognizes identical subproblems but which can be used to find both optimal and quasioptimal solutions. The heuristic search method introduced in this paper combines the positive aspects of the above two techniques. Compressed tables with a large number of variables can be handled without deriving expanded tables first. [ABSTRACT FROM AUTHOR]

n this paper an algorithm to detect logical errors in a limited-entry decision table and in loop-free programs with embedded decision tables is developed. All the conditions in the decision tables are assumed to be inequalities or equalities relating linear expressions. It is also assumed that actions in a decision table are linear in variables which occur in the condition stub of the decision table (or tables) to which control is transferred from the table. The algorithm is based on determining whether a set of linear inequalities has or does not have a solution. The algorithm described in the paper is implemented in Fortran IV. [ABSTRACT FROM AUTHOR]

The article discusses the construction and maintenance of Big-Data analytics systems as of March 2013, focusing on machine-learning methods and statistical methods while describing the Hazy project for algorithm management. Topics include trained systems, interfaces between algorithms and systems, the GeoDeepDive application for the statistical analysis of geological research papers, and the Bismarck project for infrastructure abstractions. Data sets, probabilistic logic programming, debugging, convex programming, and scalability are mentioned.

Although there has been much interest in computational photography within the research and photography communities, progress has been hampered by the lack of a portable, programmable camera with sufficient image quality and computing power. To address this problem, we have designed and implemented an open architecture and application programming interface (API) for such cameras: the Frankencamera. It consists of a base hardware specification, a software stack based on Linux, and an API for C++. Our architecture permits control and synchronization of the sensor and image processing pipeline at the microsecond timescale, as well as the ability to incorporate and synchronize external hardware like lenses and flashes. This paper specifies our architecture and API, and it describes two reference implementations we have built. Using these implementations, we demonstrate several computational photography applications: high dynamic range (HDR) viewfinding and capture, automated acquisition of extended dynamic range panoramas, foveal imaging, and inertial measurement unit (IMU)-based hand shake detection. Our goal is to standardize the architecture and distribute Frankencameras to researchers and students, as a step toward creating a community of photographer- programmers who develop algorithms, applications, and hardware for computational cameras. [ABSTRACT FROM AUTHOR]

The ancient oriental game of Go has long been considered a grand challenge for artificial intelligence. For decades, computer Go has defied the classical methods in game tree search that worked so successfully for chess and checkers. However, recent play in computer Go has been transformed by a new paradigm for tree search based on Monte-Carlo methods. Programs based on Monte-Carlo tree search now play at human-master levels and are beginning to challenge top professional players. In this paper, we describe the leading algorithms for Monte-Carlo tree search and explain how they have advanced the state of the art in computer Go. [ABSTRACT FROM AUTHOR]

Recognizing objects in images is an active area of research in computer vision. In the last two decades, there has been much progress and there are already object recognition systems operating in commercial products. However, most of the algorithms for detecting objects perform an exhaustive search across all locations and scales in the image comparing local image regions with an object model. That approach ignores the semantic structure of scenes and tries to solve the recognition problem by brute force. In the real world, objects tend to covary with other objects, providing a rich collection of contextual associations. These contextual associations can be used to reduce the search space by looking only in places in which the object is expected to be; this also increases performance, by rejecting patterns that look like the target but appear in unlikely places. Most modeling attempts so far have defined the context of an object in terms of other previously recognized objects. The drawback of this approach is that inferring the context becomes as difficult as detecting each object. An alternative view of context relies on using the entire scene information holistically. This approach is algorithmically attractive since it dispenses with the need for a prior step of individual object recognition. In this paper, we use a probabilistic framework for encoding the relationships between context and object properties and we show how an integrated system provides improved performance. We view this as a significant step toward general purpose machine vision systems. [ABSTRACT FROM AUTHOR]

The article refers to a 1971 research paper by Steve Cook, "The Complexity of Theorem-Proving Procedures" and focuses on computational complexity. The Polynomial Time (P) versus Nondeterministic Polynomial-Time (NP) problem in computer science is discussed, as well as the theory of efficient algorithms for a solution to NP-complete problems. Integer programming, approaches to proving that P≠NP such as diagonalization, circuit and proof complexity with Boolean operators, brute force and heuristics, NP-complete optimization and the limits of approximation, hardness assumptions in cryptography, and the elimination of randomness are mentioned.

Autonomous helicopter flight is widely regarded to be a highly challenging control problem. As helicopters are highly unstable and exhibit complicated dynamical behavior, it is particularly difficult to design controllers that achieve high performance over a broad flight regime. While these aircraft are notoriously difficult to control, there are expert human pilots who are nonetheless capable of demonstrating a wide variety of maneuvers, including aerobatic maneuvers at the edge of the helicopter's performance envelope. In this paper, we present algorithms for modeling and control that leverage these demonstrations to build high-performance control systems for autonomous helicopters. More specifically, we detail our experiences with the Stanford Autonomous Helicopter, which is now capable of extreme aerobatic flight meeting or exceeding the performance of our own expert pilot. [ABSTRACT FROM AUTHOR]

What can you do with a million images? In this paper, we present a new image completion algorithm powered by a huge database of photographs gathered from the Web. The algorithm patches up holes in images by finding similar image regions in the database that are not only seamless, but also semantically valid. Our chief insight is that while the space of images is effectively infinite, the space of semantically differentiable scenes is actually not that large. For many image completion tasks, we are able to find similar scenes which contain image fragments that will convincingly complete the image. Our algorithm is entirely data driven, requiring no annotations or labeling by the user. Unlike existing image completion methods, our algorithm can generate a diverse set of image completions and we allow users to select among them. We demonstrate the superiority of our algorithm over existing image completion approaches. [ABSTRACT FROM AUTHOR]

The article discusses the interaction between computer science and game theory. A 1995 paper by E. Kalai highlighted connections between game theory and such areas as graphs, complexity in game playing, and operations research. In 2008 developments proceed along six lines of inquiry, among them compact game representations, algorithms and mechanical design, and logical considerations inherent in games. Future progress could entail ways of thinking that go beyond the role of the Nash equilibrium in game theory.

The article seeks improved measurement and understanding of static and dynamic complexity. The information needed to make decisions must be conveyed in physical symbols like marks on paper, sounds, and electrical pulses. In the earliest physical systems, the carriers of information were, for example, mechanical links in steam engine governors, punched holes in Jacquard weaving looms, or electrical connectivity in thermostats. It was possible to establish a mathematical link between the physical meaning of the information and the physical performance of the system. Establishing such a direct link between information meaning and system performance in a value chain is much more difficult because it is not a simple system. A value chain represents a complex system in which every decision of every component impacts, in complicated and sometimes unpredictable ways, total system performance. Computational or algorithmic complexity is often used for classifying manufacturing planning and control problems.

This article presents correspondence from computer scientists related to technical problems. One paper presents commentary on the movement of large amounts of information in the form of data and commands in the form of instructions into and out of the computer's processing module. The cache store unit is an optional circuit that improves the effective access and cycle time of store operations. Cache takes advantage of the general programming characteristic of locality of reference. Improvements in disk access times have also failed to keep up with improvements in processor times. Cache memory has been used to compensate for some of the differences in performance between the processor and its data storage facilities. Therefore, how cache is implemented can have a significant impact on system performance and literally can make or break a particular system. The importance of cache between the processor and main memory can easily be demonstrated by simple examination of current technology. The current generation of general-purpose-high-speed computers have processor cycle-times around 15 to 25 nanoseconds.

The macroanalysis of algorithms consists of choosing a dominant operation of an algorithm and expressing execution time as a function of the number of times this operation is used. In contrast, the microanalysis of programs consists of expressing the execution time as a function of the time needed to execute each of the operations in the program. Approaches are described whereby one may, with the help of a computer, perform microanalyses of programs by constructing their time-formulas. Time-formulas are symbolic formulas that express execution times as functions of variables representing the time needed to perform common, elementary operations, e.g., addition, assignment, subscripting, loop overhead. By binding the variables to numeric values corresponding to a specific machine, one can estimate program execution times without resorting to empirical tests. This paper reviews methods of microanalysis and discusses some programs that have been analyzed using the suggested approaches. These include Strassen's matrix multiplication algorithm, deterministic parsers, and a certain class of straight-line programs. The desirable software tools for performing microanalysis are also discussed. [ABSTRACT FROM AUTHOR]

Time and state descriptions form the core of a simulation model representation. The historical influence of initial application areas and the exigencies of language implementations have created a muddled view of the time and state relationships. As a consequence, users of simulation programming languages work in relative isolation; model development, simulation application, model portability, and the communication of results are inhibited and simulation practice fails to contribute to the recognition of an underlying foundation or integrating structure. A model representation structure has been forged from a small set of basic definitions which carefully distinguish the state and time relationships. This paper focuses on the coordination of the time and state concepts using "object" as the link. In addition to clarifying the relationships, the structure relates the concept of ""state-sequenced simulation" to the variations in time flow mechanisms. In conclusion, some speculations are offered regarding alternative algorithms for time flow mechanisms. [ABSTRACT FROM AUTHOR]

This paper presents a model of an I/O subsystem in which devices can be accessed from multiple CPUs and/or via alternative channel and control unit paths. The model estimates access response times, given access rates for all CPU-device combinations. Central to the model's algorithm is the estimation of the rotational position sensing (RPS) miss probabilities by means of the maximum entropy principle. [ABSTRACT FROM AUTHOR]

This paper describes a collision avoidance algorithm for planning a safe path for a polyhedral object moving among known polyhedral objects. The algorithm transforms the obstacles so that they represent the locus of forbidden positions for an arbitrary reference point on the moving object. A trajectory of this reference point which avoids all forbidden regions is free of collisions. Trajectories are found by searching a network which indicates, for each vertex in the transformed obstacles, which other vertices can be reached safely. [ABSTRACT FROM AUTHOR]

This paper describes efficient new heuristic methods to color the vertices of a graph which rely upon the comparison of the degrees and structure of a graph. A method is developed which is exact for bipartite graphs and is an important part of heuristic procedures to find maximal cliques in general graphs. Finally an exact method is given which performs better than the Randall-Brown algorithm and is able to color larger graphs, and the new heuristic methods, the classical methods, and the exact method are compared. [ABSTRACT FROM AUTHOR]

A broadcast packet is for delivery to all nodes of a network. Algorithms for accomplishing this delivery through a store-and-forward packet switching computer network include (1) transmission of separately addressed packets, (2) multidestination addressing, (3) hot potato forwarding, (4) spanning tree forwarding, and (5) source based forwarding. To this list of algorithms we add (6) reverse path forwarding, a broadcast routing method which exploits routing procedures and data structures already available for packet switching. Reverse path forwarding is a practical algorithm for broadcast routing in store-and-forward packet switching computer networks. The algorithm is described as being practical because it is not optimal according to metrics developed for its analysis in this paper, and also because it can be implemented in existing networks with less complexity than that required for the known alternatives. [ABSTRACT FROM AUTHOR]

This paper discusses the computation of matrix chain products of the form M1 X M2 X ... X Mn where Mi's are matrices. The order in which the matrices are computed affects the number of operations. A sufficient condition about the association of the matrices in the optimal order is presented. An O( n) algorithm to find an order of computation which takes less than 25 percent longer than the optimal time Topt is also presented. In most cases, the algorithm yields the optimal order or an order which takes only a few percent longer than Topt (less than I percent on the average). [ABSTRACT FROM AUTHOR]

This paper presents pseudochaining as a new collision-resolution method. Pseudochaining is half way between open addressing and chaining. It owes its name to the fact that link fields are present in each cell of the hash table which permits "chaining" of the first overflow items in the table. The efficiency of the method is derived and a tradeoff analysis is given. [ABSTRACT FROM AUTHOR]

Certain defects, such as jagged edges and disappearing detail, have long been an annoyance in digitally generated shaded images. Although increasing the resolution or defocusing the display can alternate them, an understanding of these defects leads to more effective methods. This paper explains the observed defects in terms of the allasing phenomenon inherent in sampled signals and discusses prefiltering as a recognized cure. A method for evaluating filters is presented, the application of prefiltering to hidden-surface algorithms is discussed, and an implementation of a filtering tiler is shown accompanied by examples of its effectiveness. [ABSTRACT FROM AUTHOR]

This paper investigates the performance of 35 dynamic memory allocation algorithms when used to service simulation programs as represented by 18 test cases. Algorithm performance was measured in terms of processing time, memory usage, and external memory fragmentation. Algorithms maintaining separate free space lists for each size of memory block used tended to perform quite well compared with other algorithms. Simple algorithms operating on memory ordered lists (without any free list) performed surprisingly well. Algorithms employing power-of-two block sizes had favorable processing requirements hut generally unfavorable memory usage. Algorithms employing LIFO, FIFO, or memory ordered free lists generally performed poorly compared with others. [ABSTRACT FROM AUTHOR]

in many scientific tad technical endeavors, a three-dimensional solid must be reconstructed from serial sections, either to aid in the comprehension of the subjects structure or to facilitate its automatic manipulation and analysis. This paper presents a general solution to the problem of constructing a surface over a set of cross-sectional contours. This surface, to be composed of triangular tiles, is constructed by separately determining an optimal surface between each pair of consecutive contours. Determining such a surface is reduced to the problem of finding certain minimum cost cycles in a directed toroidal graph. A new fast algorithm for finding such cycles is utilized. Also developed is a closed-form expression, in terms of the number of contour points, for an upper hound on the number of operations Squired to execute the algorithm. An illustrated example which involves the construction of a minimum area surface describing a human head is included. [ABSTRACT FROM AUTHOR]

The Alphard "form" provides the programmer with a great deal of control over the implementation of abstract data types. In this paper the abstraction techniques are extended from simple data representation and function definition to the iteration statement, the most important point of Interaction between data and the control structure of the language Itself. A means of specializing Alphard's loops to operate on abstract entities without explicit dependence on the representation of those entities is introduced. Specification and verification techniques that allow the properties of the generators for such iterations to be expressed in the form of proof rules are developed. Results are obtained that for common special cases of these loops are essentially identical to the corresponding constructs in other languages. A means of showing that a generator will terminate is also provided. [ABSTRACT FROM AUTHOR]

CLU is a new programming language designed to support the use of abstractions in program construction. Work hi programming methodology has led to the realization that three kinds of abstractions-procedural, control, and especially data abstractions- are useful in the programming process. Of these, only the procedural abstraction is supported well by conventional languages, through the procedure or subroutine. CLU provides, in addition to procedures, novel linguistic mechanisms that support the use of data and control abstractions. This paper provides an Introduction to the abstraction mechanisms in CLU. By means of programming examples, the utility of the three kinds of abstractions in program construction is illustrated, and it is shown how CLU programs may be written to use and implement abstractions. The CLU library, which permits incremental program development with complete type checking performed at compile time, is also discussed. [ABSTRACT FROM AUTHOR]

Improvements to the exhaustive search method of best-match file searching have previously been achieved by doing a preprocessing step involving the calculation of distances from a reference point. This paper discusses the proper choice of reference points and extends the previous algorithm to use more than one reference point. It is shown that reference points should be located outside of data clusters. The results of computer simulations are presented which show that large improvements can be achieved by the proper choice and location of multiple reference points. [ABSTRACT FROM AUTHOR]

The global data relationships in a program can be exposed and codified by the static analysis methods described in this paper. A procedure is given which determines all the definitions which can possibly "reach" each node of the control flow graph of the program and all the definitions that are "live" on each edge of the graph. The procedure uses an "Interval" ordered edge listing data structure and handles reducible and irreducible graphs indistinguishably. [ABSTRACT FROM AUTHOR]

Consider a multipriority batch computer system which users from several different classes may join, with toll, service, and waiting charges. Such a system is formulated here as a semi- Markov decision process, In which the aim of arriving users Is to minimize their expected loss. The optimal joining policy of arriving users who may join the system at some of its queues is a control limit policy, with a single control number for any possible queue and the user's class; a newly arriving user will join a queue that is not filled up to the control number corresponding to this queue and the user's class. In this paper control numbers, as well as lower and upper bounds for the control numbers and the capacities of the system's queues, are derived. [ABSTRACT FROM AUTHOR]

Data set allocation in today's multilevel storage systems is usually based on qualitative, ad hoc decisions. While it would be desirable to obtain an optimal solution to this allocation problem, it is clear that the number of parameters involved makes it intractable to straight-forward solution. In such a situation, we must find a set of assumptions which simplify the problem greatly, but which still provide a basis for considering all significant cost elements. This paper presents such a first, quantitative allocation step. It considers many of the significant detailed costs of system utilization, data storage, data staging, and data migration. Although many avenues of further improvement are available, the present algorithm seems to be usefully accurate. As such, it can aid in quantifying the problems of data set allocation, storage system configuration, and new device designs. [ABSTRACT FROM AUTHOR]

GLYPNER is one of the earliest existing languages designed for programming the Illiac IV computer. The syntax of the language is based on ALGOL 60, but has been extended to allow the programmer explicitly to specify the parallelism of his algorithm in terms of 64-word vectors. This paper describes the characteristics, goals, and philosophy of the language, and discusses some of the problems associated with parallel computer architectures. [ABSTRACT FROM AUTHOR]

The paper describes an efficient method for reduction of the binary matrices which arise in some school time-tabling problems. It is a development of that described by John Lions. It has been generalized and adapted to fit into the complete timetabling process; to use a more compact data representation and more efficient processing techniques; to take fuller advantage of possible available previous knowledge about the matrix. And it is designed as a structured program, which can readily be coded by the reader in the high level or low level programming language of his choice. Practical tests of the method have shown it to be a good basis for a realistic timetabling algorithm. [ABSTRACT FROM AUTHOR]

This paper suggests a bidirectional relationship between state-space and problem- reduction representations. It resents a formalism based on multiple-input and multiple-output operators which provides a basis for viewing the two types of representations in this manner. A representation of the language recognition problem which is based on the Cocke parsing algorithm Is used as an illustration. A method for representing problems in first-order logic in such a way that the inference system employed by a resolution-based theorem prover determines whether the set of clauses is interpreted in the state-space mode or in the problem-reduction mode is presented. The analogous concepts in problem-reduction and theorem proving, and the terminology used to refer to them, are noted. The relationship between problem-reduction, input resolution, and linear resolution is is discussed. [ABSTRACT FROM AUTHOR]

The article offers highlights from the research paper "Data-Driven Algorithm Design" written by Gupta and Roughgarden.

This paper presents a generalization of an old programming technique; using it, one may add and subtract numbers represented in any radix, including a mixed radix, and stored one digit per byte in bytes of sufficient size. Radix conversion is unnecessary, no looping is required, and numbers may even be stored in a display (I/O) format. Applications to Cobol, MIX, and hexadecimal sums are discussed. [ABSTRACT FROM AUTHOR]

The problem classically titled "The Examination Schedule Problem" takes various forms in the literature. Most of these formulations can be presented in the terminology of classical Network Theory. One such formulation is: Given a nondirected network, partition its nodes into a minimal number of subsets such that no two members of the same subset are connected by an An obvious lower limit to this number is the size of the largest strongly connected subgraph. Kirchgassner proved that an upper limit is this size plus one. One logical extension of the previous work is the introduction of variable length examinations where W(I) is the number of periods for exam I. The object of this paper is to generalize the definition of largest strongly connected subgraph to include the weighting of nodes, to present an approximate algorithm which usually finds the largest strongly connected subgraph, and to discuss the application of this algorithm to the solution of school scheduling and exam scheduling problems. [ABSTRACT FROM AUTHOR]

The article presents an introduction to a paper regarding a deterministic parallel algorithm for bipartite matching.