Downloads & Free Reading Options - Results

In my talk I will report on the work in progress. The initial idea of the project was to test available compilers of C-like languages. Our plan is the following: Choose a reasonable subset of the language to be tested. Formalize the semantics of the sub-language in AsmL. Produce tons of different programs. Using the AsmL Test tool, build test sequences for all these programs to check the correctness of the executable binary produced by the compiler. We started with a very simple fragment of the language (if, while, break, goto, simple function call). The next reasonable step is to add exceptions handling, arithmetical expressions, classes. (Joint work with Andrey Novikov.) ©2004 Microsoft Corporation. All rights reserved.

In my talk I will report on the work in progress. The initial idea of the project was to test available compilers of C-like languages. Our plan is the following: Choose a reasonable subset of the language to be tested. Formalize the semantics of the sub-language in AsmL. Produce tons of different programs. Using the AsmL Test tool, build test sequences for all these programs to check the correctness of the executable binary produced by the compiler. We started with a very simple fragment of the language (if, while, break, goto, simple function call). The next reasonable step is to add exceptions handling, arithmetical expressions, classes. (Joint work with Andrey Novikov.) ©2004 Microsoft Corporation. All rights reserved.

Java programming language 30 mm key fob + add python key fob

Java programming language 30 mm key fob + add python key fob

The issue of model validation is critical in the formulation and interpretation of mathematical programming models, yet this problem is largely ignored by contemporary modeling languages and the systems they support. This research advanced modeling languages for mathematical programming by providing a formalism and defining a language for specifying a dimensional complement, called typing, to the algebraic representation of models. Typing is a formal specification used to determine automatically whether the algebraic model is well-formed in the sense that its objective junction and constraints are composed of homogeneous components and that operations junction and constraints are composed of homogeneous components and that operations performed using indices are meaningful. A provision is made for the definition of dimensional axioms that can be applied automatically to resolve dimensional differences. The addiction of formal typing to mathematical programming models also yields a powerful abstraction mechanism for integrated modeling.

"NPS-52-81-009."

"NPS-52-81-009."

Frances S. Grodzinsky

Frances S. Grodzinsky

Frances S. Grodzinsky

Frances S. Grodzinsky

Throughout the 1990s, Richard Reid of Michigan State University maintained a list showing the first programming language used in introductory programming courses taken by computer science and information systems majors; it was updated for several years afterwards by Frances Van Scoy of West Virginia University. However, it has been 5 years since the last Reid List was released. An updated list was compiled revealing the most popular programming languages. The resultant correspondence with faculty members at many of the 410 Reid List colleges and universities indicates several trends, some of which are contradictory, as well as the reasons for the language choices of the participating schools. We present several conclusions from our findings.

This paper elaborates on the concepts of a new programming language “Dart”, which has been developed by Google and considered for future use. Here, we compare it to the most famous, real time, and updated language “Java”. This is to define similarities and differences between the two important languages, explain programs’ behavior, with a focus on investigating alternative implementation strategies and problem definitions. We used programming languages’ concepts and terminologies to compare between the main characteristics of the two languages, Dart & Java.

This paper elaborates on the concepts of a new programming language “Dart”, which has been developed by Google and considered for future use. Here, we compare it to the most famous, real time, and updated language “Java”. This is to define similarities and differences between the two important languages, explain programs’ behavior, with a focus on investigating alternative implementation strategies and problem definitions. We used programming languages’ concepts and terminologies to compare between the main characteristics of the two languages, Dart & Java.

This paper elaborates on the concepts of a new programming language “Dart”, which has been developed by Google and considered for future use. Here, we compare it to the most famous, real time, and updated language “Java”. This is to define similarities and differences between the two important languages, explain programs’ behavior, with a focus on investigating alternative implementation strategies and problem definitions. We used programming languages’ concepts and terminologies to compare between the main characteristics of the two languages, Dart & Java.

This paper elaborates on the concepts of a new programming language “Dart”, which has been developed by Google and considered for future use. Here, we compare it to the most famous, real time, and updated language “Java”. This is to define similarities and differences between the two important languages, explain programs’ behavior, with a focus on investigating alternative implementation strategies and problem definitions. We used programming languages’ concepts and terminologies to compare between the main characteristics of the two languages, Dart & Java.

ACM Transactions on Programming Languages and Systems 1994: Volume 16 , Issue Index. Digitized from IA1534625-06 . Previous issue: sim_acm-transactions-on-programming-languages-and-systems_1993-10_15_5 . Next issue: sim_acm-transactions-on-programming-languages-and-systems_1994-01_16_1 .

Programming multiprocessor architectures is a critical research issue. An overview is given of the various approaches to programming these architectures that are currently being explored. It is argued that two of these approaches, interactive programming environments and functional parallel languages, are particularly attractive since they remove much of the burden of exploiting parallel architectures from the user. Also described is recent work by the author in the design of parallel languages. Research on languages for both shared and nonshared memory multiprocessors is described, as well as the relations of this work to other current language research projects.

C and C++ programming languages have certain characteristics that can act like a double-edged sword. Having direct access to memory allows programmers to implement linked-lists and do pointer arithmetic operations but at the same time it also allows buffer overflows. Or, having vast amount of undefined behaviors allows the compilers to optimize the code to the full extent, but it also causes major vulnerabilities such as double free (i.e. trying to release part of memory that was already released). Code sanitizers, first introduced with the Address Sanitizer by Google in 2012, offer a flexible code weakness mitigation run-time mechanism. In this thesis, the major code sanitizers were tested on popular open-source software with regard to their effectivenesses on finding bugs that have the potential of compromising security. It is also discussed if they can be employed in production (release mode), and if they can be an alternative to porting code into "secure" languages. It is found out that code sanitizers in certain cases can be used in production in order to reduce the attack surface. Furthermore, it is found out that if disk size is not scarce, Undefined Behavior Sanitizer can be utilized in production without noticeable impact on the performance or memory usage even though the increase of program size it induces has the potential of spoiling spatial locality for the CPU cache mechanisms. It should be also noted that during experimentation, Undefined Behavior Sanitizer was able to find numerous undefined behaviors in an open-source Minecraft clone game named Minetest. One notable undefined behavior found was thought to cause behavioral divergence between Intel and ARM architectures due to casting negative floating-point number into unsigned integer. The patches containing the fixes which were merged into the upstream repositories are included in this thesis. The research conducted while writing this thesis suggests that code sanitizers do not necessarily need to be limited being used in debugging sessions, as they are shown to be effective in eliminating the top Common Weakness Enumeration (CWE™) entries while having a modest overhead. The tests done on popular projects and real-world scenarios hint that code sanitizers deserve more attention from software developers.

Video content can be found here: https://www.youtube.com/channel/UC0BAd8tPlDqFvDYBemHcQPQ/

Video content can be found here: https://www.youtube.com/channel/UC0BAd8tPlDqFvDYBemHcQPQ/

Video content can be found here: https://www.youtube.com/channel/UC0BAd8tPlDqFvDYBemHcQPQ/

xx, 844 p. : 24 cm

In order to promote public education and public safety, equal justice for all, a better informed citizenry, the rule of law, world trade and world peace, this legal document is hereby made available on a noncommercial basis, as it is the right of all humans to know and speak the laws that govern them. (For more information: 12 Tables of Code ) Name of Standards Organization: Bureau of Indian Standards (BIS) Division Name: Electronics and Information Technology Section Name: Software and System Engineering (LITD 14) Designator of Legally Binding Document: IS 10681 Title of Legally Binding Document: Programming languages - COBOL Number of Amendments: Equivalence: ISO 1989 Superceding: Superceded by: LEGALLY BINDING DOCUMENT Step Out From the Old to the New --Jawaharlal Nehru Invent a new India using knowledge. --Satyanarayan Gangaram Pitroda

pages cm

pages cm

pages cm

THE FIRST TASK OF THE HOL Working Group was to formulate a set of requirements consistent with the levies of the Military Departments. This effort proceeded as follows: While there is no intent to replace the already standard COBOL and FORTRAN in their field of application, initially there was no reason to unnecessarily restrict the requirements to only those areas such as real-time applications or weapons systems where the major problems are, although this area must receive emphasis. Therefore, requirements were solicited from as broad a base as possible, to be prioritized later as required. Further, inquiries were not restricted to those programs presently using high order languages, rather, a major thrust of the effort is to provide HOL's to meet the requirements of those who are now constrained to use an assembly language for lack of a suitable HOL. The results of four months of such input were put together in a more concrete form, one which could then pretend to represent a fairly complete set of requirements, although still a tentative set. This document was called the 'woodenman,' and it too was distributed widely. It provided a more rigorous framework for specific comment. On the basis of all inputs and the official responses from each of the Military Departments, a more complete set of requirements has evolved and is presented here as a 'tinman.' This document represents a set of requirements for high order computer programming language consistent with the input from the Military Services.

The terms value-oriented and object-oriented are used to describe both programming languages and programming styles. This paper will describe the differences between values and objects and to show that their proper discrimination can be a valuable aid to conquering program complexity. The first section will show that values amount to timeless abstractions for which the concepts of updating, sharing and instantiation have no meaning. The second section will show that objects exist in time and, hence, can be created, destroyed, copied, shared and updated. The third section shows that proper discrimination of these concepts in programming languages will clarify problems such as the role of state in functional programming. The paper concludes by demonstrating the use of the value/object distinction as a tool for program organization. (Author)

The terms value-oriented and object-oriented are used to describe both programming languages and programming styles. This paper will describe the differences between values and objects and to show that their proper discrimination can be a valuable aid to conquering program complexity. The first section will show that values amount to timeless abstractions for which the concepts of updating, sharing and instantiation have no meaning. The second section will show that objects exist in time and, hence, can be created, destroyed, copied, shared and updated. The third section shows that proper discrimination of these concepts in programming languages will clarify problems such as the role of state in functional programming. The paper concludes by demonstrating the use of the value/object distinction as a tool for program organization. (Author)

The two-volume open access book set LNCS 14576 + 14577 constitutes the proceedings of the 33rd European Symposium on Programming, ESOP 2024, which was held during April 6-11, 2024, in Luxemburg, as part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2024. The 25 full papers and 1 fresh perspective paper presented in these proceedings were carefully reviewed and selected from 72 submissions. The papers were organized in topical sections as follows: Part I: Effects and modal types; bidirectional typing and session types; dependent types; Part II: Quantum programming and domain-specific languages; verification; program analysis; abstract interpretation.

The two-volume open access book set LNCS 14576 + 14577 constitutes the proceedings of the 33rd European Symposium on Programming, ESOP 2024, which was held during April 6-11, 2024, in Luxemburg, as part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2024. The 25 full papers and 1 fresh perspective paper presented in these proceedings were carefully reviewed and selected from 72 submissions. The papers were organized in topical sections as follows: Part I: Effects and modal types; bidirectional typing and session types; dependent types; Part II: Quantum programming and domain-specific languages; verification; program analysis; abstract interpretation.

Video content can be found here: https://www.youtube.com/channel/UC0BAd8tPlDqFvDYBemHcQPQ/

Video content can be found here: https://www.youtube.com/channel/UC0BAd8tPlDqFvDYBemHcQPQ/

Video content can be found here: https://www.youtube.com/channel/UC0BAd8tPlDqFvDYBemHcQPQ/

Video content can be found here: https://www.youtube.com/channel/UC0BAd8tPlDqFvDYBemHcQPQ/

The von Neumann bottleneck imposes severe limitations on programming languages. This thesis points out that although the hardware limitations imposed by this bottleneck are being overcome, its constraints will remain in programs as long as there are assignments statements in their code. We assert that functional programming languages allow us to harness the processing power of computers with hundreds or even thousands of processors, and which allow us to solve problems which are time/cost prohibitive on a uniprocessor. We discuss a mechanical method for transforming imperative programs into functional programs. We feel that the mechanical transformation process is very inexpensive, and that it might be the best way to make imperative library programs into functional ones which are well suited to concurrent processing. Originator supplied key words include: Parallel processing, Functional, Concurrent processing, and Multiprocessor.

With an ever increasing demand for new program applications and the failure of older generations of languages, such as COBOL, PL/I, PASCAL, etc., to keep up with this increased demand, there exists a need for new techniques and approaches to programming. Greater programmer/user productivity and enhanced user friendliness, to allow more end users to develop applications on their own, are goals sought by industry in order to reduce skyrocketing backlogs of applications. This paper describes a new generation of programming languages, used in the development of business and scientific applications, that addresses and achieves these goals. The basic characteristics of Fourth Generation Languages is reviewed and the design and implementation of a Fourth Generation Language is proposed. Although Fourth Generation Languages do increase user productivity and are easier to learn and use than previous generations of languages, much research remains to be done before general end user computing becomes the norm rather than the exception. (Author)

artificial intelligence; computer architecture; computer software selection and evaluation; distributed computer systems; formal logic; formal model; java; model checking; processors; program compilers; program verification; programming language; semantics; separation logic; software engineering specifications; theorem proving; type; systems verification

artificial intelligence; computer architecture; computer software selection and evaluation; distributed computer systems; formal logic; formal model; java; model checking; processors; program compilers; program verification; programming language; semantics; separation logic; software engineering specifications; theorem proving; type; systems verification

Panel: ? Aimee Knight ? Joe Eames ? AJ ONeal Special Guests: Jeremy Fairbank In this episode, the JavaScript Jabber panel talks to Jeremy Fairbank about his talk Practical Functional Programming . Jeremy is a remote software developer and consultant for Test Double . They talk about what Test Double is and what they do there and the 6 things he touched on in his talk, such as hard to follow code, function composition, and mutable vs immutable data. They also touch on the theory of unit testing, if functional programming is the solution, and more! In particular, we dive pretty deep on: ? Jeremy intro ? Works for Test Double ? What he means by “remote” ? What is Test Double? ? They believe software is broken and they are there to fix it ? His talk - Practical Functional Programming ? The 6 things he talked about in his talk ? Practical aspects that any software engineer is going to deal with ? Purity and the side effects of programming in general ? Hard to follow code ? Imperative VS declarative code ? Code breaking unexpectedly ? Mutable data VS immutable data ? The idea of too much code ? Combining multiple functions together to make more complex functions ? Function composition ? Elm , Elixir , and F# ? Pipe operator ? Scary to refactor code ? Static types ? The idea of null ? The theory of unit testing ? Is functional programming the solution? ? His approach from the talk ? And much, much more! Links: ? Test Double ? His talk - Practical Functional Programming ? Elm ? Elixir ? F# ? @elpapapollo ? jeremyfairbank.com ? Jeremy’s GitHub ? Jeremy’s YouTube Sponsors ? Kendo UI ? Sentry ? Digital Ocean Picks: Aimee ? American Dollar ? Force with lease AJ ? Superfight Joe ? The 2018 Web Developer Roadmap by Brandon Morelli ? Svelte Jeremy ? Programming Elm ? The Secrets of Consulting by Gerald M. Weinberg ? Connect.Tech

Panel: ? Aimee Knight ? Joe Eames ? AJ ONeal Special Guests: Jeremy Fairbank In this episode, the JavaScript Jabber panel talks to Jeremy Fairbank about his talk Practical Functional Programming . Jeremy is a remote software developer and consultant for Test Double . They talk about what Test Double is and what they do there and the 6 things he touched on in his talk, such as hard to follow code, function composition, and mutable vs immutable data. They also touch on the theory of unit testing, if functional programming is the solution, and more! In particular, we dive pretty deep on: ? Jeremy intro ? Works for Test Double ? What he means by “remote” ? What is Test Double? ? They believe software is broken and they are there to fix it ? His talk - Practical Functional Programming ? The 6 things he talked about in his talk ? Practical aspects that any software engineer is going to deal with ? Purity and the side effects of programming in general ? Hard to follow code ? Imperative VS declarative code ? Code breaking unexpectedly ? Mutable data VS immutable data ? The idea of too much code ? Combining multiple functions together to make more complex functions ? Function composition ? Elm , Elixir , and F# ? Pipe operator ? Scary to refactor code ? Static types ? The idea of null ? The theory of unit testing ? Is functional programming the solution? ? His approach from the talk ? And much, much more! Links: ? Test Double ? His talk - Practical Functional Programming ? Elm ? Elixir ? F# ? @elpapapollo ? jeremyfairbank.com ? Jeremy’s GitHub ? Jeremy’s YouTube Sponsors ? Kendo UI ? Sentry ? Digital Ocean Picks: Aimee ? American Dollar ? Force with lease AJ ? Superfight Joe ? The 2018 Web Developer Roadmap by Brandon Morelli ? Svelte Jeremy ? Programming Elm ? The Secrets of Consulting by Gerald M. Weinberg ? Connect.Tech

Panel: ? Aimee Knight ? Joe Eames ? AJ ONeal Special Guests: Jeremy Fairbank In this episode, the JavaScript Jabber panel talks to Jeremy Fairbank about his talk Practical Functional Programming . Jeremy is a remote software developer and consultant for Test Double . They talk about what Test Double is and what they do there and the 6 things he touched on in his talk, such as hard to follow code, function composition, and mutable vs immutable data. They also touch on the theory of unit testing, if functional programming is the solution, and more! In particular, we dive pretty deep on: ? Jeremy intro ? Works for Test Double ? What he means by “remote” ? What is Test Double? ? They believe software is broken and they are there to fix it ? His talk - Practical Functional Programming ? The 6 things he talked about in his talk ? Practical aspects that any software engineer is going to deal with ? Purity and the side effects of programming in general ? Hard to follow code ? Imperative VS declarative code ? Code breaking unexpectedly ? Mutable data VS immutable data ? The idea of too much code ? Combining multiple functions together to make more complex functions ? Function composition ? Elm , Elixir , and F# ? Pipe operator ? Scary to refactor code ? Static types ? The idea of null ? The theory of unit testing ? Is functional programming the solution? ? His approach from the talk ? And much, much more! Links: ? Test Double ? His talk - Practical Functional Programming ? Elm ? Elixir ? F# ? @elpapapollo ? jeremyfairbank.com ? Jeremy’s GitHub ? Jeremy’s YouTube Sponsors ? Kendo UI ? Sentry ? Digital Ocean Picks: Aimee ? American Dollar ? Force with lease AJ ? Superfight Joe ? The 2018 Web Developer Roadmap by Brandon Morelli ? Svelte Jeremy ? Programming Elm ? The Secrets of Consulting by Gerald M. Weinberg ? Connect.Tech

Panel: ? Aimee Knight ? Joe Eames ? AJ ONeal Special Guests: Jeremy Fairbank In this episode, the JavaScript Jabber panel talks to Jeremy Fairbank about his talk Practical Functional Programming . Jeremy is a remote software developer and consultant for Test Double . They talk about what Test Double is and what they do there and the 6 things he touched on in his talk, such as hard to follow code, function composition, and mutable vs immutable data. They also touch on the theory of unit testing, if functional programming is the solution, and more! In particular, we dive pretty deep on: ? Jeremy intro ? Works for Test Double ? What he means by “remote” ? What is Test Double? ? They believe software is broken and they are there to fix it ? His talk - Practical Functional Programming ? The 6 things he talked about in his talk ? Practical aspects that any software engineer is going to deal with ? Purity and the side effects of programming in general ? Hard to follow code ? Imperative VS declarative code ? Code breaking unexpectedly ? Mutable data VS immutable data ? The idea of too much code ? Combining multiple functions together to make more complex functions ? Function composition ? Elm , Elixir , and F# ? Pipe operator ? Scary to refactor code ? Static types ? The idea of null ? The theory of unit testing ? Is functional programming the solution? ? His approach from the talk ? And much, much more! Links: ? Test Double ? His talk - Practical Functional Programming ? Elm ? Elixir ? F# ? @elpapapollo ? jeremyfairbank.com ? Jeremy’s GitHub ? Jeremy’s YouTube Sponsors ? Kendo UI ? Sentry ? Digital Ocean Picks: Aimee ? American Dollar ? Force with lease AJ ? Superfight Joe ? The 2018 Web Developer Roadmap by Brandon Morelli ? Svelte Jeremy ? Programming Elm ? The Secrets of Consulting by Gerald M. Weinberg ? Connect.Tech

Panel: ? Aimee Knight ? Joe Eames ? AJ ONeal Special Guests: Jeremy Fairbank In this episode, the JavaScript Jabber panel talks to Jeremy Fairbank about his talk Practical Functional Programming . Jeremy is a remote software developer and consultant for Test Double . They talk about what Test Double is and what they do there and the 6 things he touched on in his talk, such as hard to follow code, function composition, and mutable vs immutable data. They also touch on the theory of unit testing, if functional programming is the solution, and more! In particular, we dive pretty deep on: ? Jeremy intro ? Works for Test Double ? What he means by “remote” ? What is Test Double? ? They believe software is broken and they are there to fix it ? His talk - Practical Functional Programming ? The 6 things he talked about in his talk ? Practical aspects that any software engineer is going to deal with ? Purity and the side effects of programming in general ? Hard to follow code ? Imperative VS declarative code ? Code breaking unexpectedly ? Mutable data VS immutable data ? The idea of too much code ? Combining multiple functions together to make more complex functions ? Function composition ? Elm , Elixir , and F# ? Pipe operator ? Scary to refactor code ? Static types ? The idea of null ? The theory of unit testing ? Is functional programming the solution? ? His approach from the talk ? And much, much more! Links: ? Test Double ? His talk - Practical Functional Programming ? Elm ? Elixir ? F# ? @elpapapollo ? jeremyfairbank.com ? Jeremy’s GitHub ? Jeremy’s YouTube Sponsors ? Kendo UI ? Sentry ? Digital Ocean Picks: Aimee ? American Dollar ? Force with lease AJ ? Superfight Joe ? The 2018 Web Developer Roadmap by Brandon Morelli ? Svelte Jeremy ? Programming Elm ? The Secrets of Consulting by Gerald M. Weinberg ? Connect.Tech

This work introduces a runtime model for managing communication with support for latency-hiding. The model enables non-computer science researchers to exploit communication latency-hiding techniques seamlessly. For compiled languages, it is often possible to create efficient schedules for communication, but this is not the case for interpreted languages. By maintaining data dependencies between scheduled operations, it is possible to aggressively initiate communication and lazily evaluate tasks to allow maximal time for the communication to finish before entering a wait state. We implement a heuristic of this model in DistNumPy, an auto-parallelizing version of numerical Python that allows sequential NumPy programs to run on distributed memory architectures. Furthermore, we present performance comparisons for eight benchmarks with and without automatic latency-hiding. The results shows that our model reduces the time spent on waiting for communication as much as 27 times, from a maximum of 54% to only 2% of the total execution time, in a stencil application.

This work introduces a runtime model for managing communication with support for latency-hiding. The model enables non-computer science researchers to exploit communication latency-hiding techniques seamlessly. For compiled languages, it is often possible to create efficient schedules for communication, but this is not the case for interpreted languages. By maintaining data dependencies between scheduled operations, it is possible to aggressively initiate communication and lazily evaluate tasks to allow maximal time for the communication to finish before entering a wait state. We implement a heuristic of this model in DistNumPy, an auto-parallelizing version of numerical Python that allows sequential NumPy programs to run on distributed memory architectures. Furthermore, we present performance comparisons for eight benchmarks with and without automatic latency-hiding. The results shows that our model reduces the time spent on waiting for communication as much as 27 times, from a maximum of 54% to only 2% of the total execution time, in a stencil application.

With the advent of numerous languages it is difficult to realize the edge of one language in a particular scope over another one. We are making an effort, realizing these few issues and comparing some main stream languages like Java, Scala, C++, Haskell, VB .NET, AspectJ, Perl, Ruby, PHP and Scheme keeping in mind some core issues in program development.

With the advent of numerous languages it is difficult to realize the edge of one language in a particular scope over another one. We are making an effort, realizing these few issues and comparing some main stream languages like Java, Scala, C++, Haskell, VB .NET, AspectJ, Perl, Ruby, PHP and Scheme keeping in mind some core issues in program development.

With the advent of numerous languages it is difficult to realize the edge of one language in a particular scope over another one. We are making an effort, realizing these few issues and comparing some main stream languages like Java, Scala, C++, Haskell, VB .NET, AspectJ, Perl, Ruby, PHP and Scheme keeping in mind some core issues in program development.