Peñuela Vega, Camilo Orlando · Americanae (AECID Library) · 2015
Abstract. The research work presents a student profiling model, and the results after applying it to the "Computer Programming" course, which is developed partially virtual through the Virtual Intelligent Learning Platform, this is an E-Learning system that allows the students to consult the course material and to take the tests. The model identifies the profiles based on socio-economic data (age and gender), and students' behavior when using the Platform (Number of accesses to documents, exercises or videos, percentage of accesses performed in class, average session length and average absence time). The profiles found are analyzed in order to define if they are connected to the academic performance. Data of around 1000 students (those enrolled in 2014) and 20500 sessions, were used. The profiles were found through the k-Means clustering algorithm. Per each profile, the common sequences of navigation were identified. A warnings system is proposed, it uses a lazy classifier to assign a profile to the current student, and based on this profile, give timely feedback by showing alerts. A recommender system is proposed, it shows suggestions of resources that should be accessed, in order to improve the academic performance.
Cited by 0
Navarro-Cota, Christian, Molina, Ana I., Redondo, Miguel A. et al. · Figshare · 2025
The demand for programmers has grown exponentially in recent years, making programming an indispensable skill. However, the complex nature of programming poses various challenges for novice programmers, leading to high dropout rates in programming courses. The recognition of individual differences, encompassing distinct neurocognitive profiles, is acknowledged to influence the accuracy of predicting programming skill outcomes. As a result, an increasing awareness exists regarding the substantial contribution of human factors, including personality or cognitive ability, to programming performance. This study conducts a Systematic Literature Review (SLR) to explore recent research on individual differentiation or programmer profiling in programming tasks. The primary goal is to examine pertinent research exploring personal characteristics’ influence on programming in various contexts. As a result of this review, a taxonomy has been introduced to enhance the comprehension of programmers’ multifaceted individual differences, categorising influential factors into nine distinct dimensions. Furthermore, it has been found that individual differences influence performance in programming tasks, as well as in the learning of this discipline. In conclusion, this SLR emphasises human factors’ critical role in programming and proposes a taxonomy that is a valuable framework for researchers, educators, and practitioners to enhance their understanding of human factors’ influence on programming performance.
Cited by 0Open access
Navarro-Cota, Christian, Molina, Ana I., Redondo, Miguel A. et al. · Figshare · 2025
The demand for programmers has grown exponentially in recent years, making programming an indispensable skill. However, the complex nature of programming poses various challenges for novice programmers, leading to high dropout rates in programming courses. The recognition of individual differences, encompassing distinct neurocognitive profiles, is acknowledged to influence the accuracy of predicting programming skill outcomes. As a result, an increasing awareness exists regarding the substantial contribution of human factors, including personality or cognitive ability, to programming performance. This study conducts a Systematic Literature Review (SLR) to explore recent research on individual differentiation or programmer profiling in programming tasks. The primary goal is to examine pertinent research exploring personal characteristics’ influence on programming in various contexts. As a result of this review, a taxonomy has been introduced to enhance the comprehension of programmers’ multifaceted individual differences, categorising influential factors into nine distinct dimensions. Furthermore, it has been found that individual differences influence performance in programming tasks, as well as in the learning of this discipline. In conclusion, this SLR emphasises human factors’ critical role in programming and proposes a taxonomy that is a valuable framework for researchers, educators, and practitioners to enhance their understanding of human factors’ influence on programming performance.
Cited by 0Open access
Michael J. Corley · 2007
Abstract : Embedded Statistical Profiling is an initiative to support both offensive and defensive computer network applications. The basis for the effort comprises the development of an environment framework known as Simplified Protocol Capture (SIMPCAP). The environment comprises a collection of tools manifested from SIMPCAP including a SQLite based packet querying engine, virtual file abstraction for seamless multi-file processing, and a complete packet capture / decoding Application Programming Interface (API). Together, these tools automatically integrate with existing LIBPCAP based tools, resulting in a highly tunable and robust environment for 1st level and 2nd level forensic analysts working in network centric operations.
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2008
Abstract- Practicing computer engineers must be able to build efficient, reliable systems. Today’s engineering student learns functionality-focused programming. Design issues that affect system performance, reliability, cost, robustness, and security are rarely covered. This paper presents a design environment where students program systems that are functionally correct and have necessary performance and efficiency. These projects are evaluated for accuracy, performance, and resource efficiency relative to a given specification. This approach is supported by a new educational tool MiSaSiM: a resource-aware execution simulator that enhances system understanding with reversible trace navigation, performance and cost analysis, and instruction profiling. MiSaSiM provides problem domain scaffolding and visualizations to facilitate learning within a semester course. As part of Georgia Tech’s commitment to globalization of engineering education, MiSaSiM was developed as a distributed educational laboratory tool. It is an integral part of a computing systems course offered concurrently at several distance-learning locations. In addition to describing a systems-oriented approach to programming using MiSaSiM, this paper includes examples of MiSaSiM projects, assessment techniques, student performance, and lessons learned over three years of experience with local and distance learning students.
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Андрей Зубрилин, Andrey Zubrilin, Анастасия Карандаева et al. · Profession-oriented School · 2017
The article shows how to involve the Centers of Youth Innovation Creativity in order to involve schoolchildren in studying robotics and demonstrating the importance of the computer science course taught at school. The variants of tasks on learning algorithmic constructions through programming of robots are given.
Cited by 3
Martin Henz And, Martin Henz, Michael Mehl · 2007
Executing computer programs means interpreting the instructions coded in a programming language. Most implementations of high-level languages, such as DFKI Oz, use an intermediate step of compilation: The source code is compiled to a machine code which is then interpreted by the hardware or a more abstract machine. We show the advantages and problems that occur when one tries to directly interprete Oz source code. We present an implementation of a meta-circular Oz interpreter, i.e. an interpreter for Oz written in Oz and demonstrate its application to source-level profiling, execution visualization and language design. Keywords--- Oz, interpreter, programming environments, profiling 1. Introduction Interpreters are computer programs that execute a suitable representation of a source program. Examples of interpreters are (1) every computer itself since it executes source programs in form of binary code, and (2) a BASIC interpreter that executes a given BASIC program line-by-line. Meta...
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Watson Manduna · 2018 International Conference on Multidisciplinary Research · 2024
Numerous literature sources in computer programming education (CPE) have emphasized that learning programming is difficult. Several reasons are provided, which include subject complexity, student culture, technology integration, and institutional infrastructure. Several tools are proposed to remedy this situation, but the problem seems to persist. A critical systemic approach (CSA) is suggested in this study to alleviate these problems. Literature on the usage of a CSA in computing training environments is scarce. Utilization of the CSA permitted the researcher to apply a critical multi-methodology, where several interpretative data collection (diaries and online semi-structured interviews) and analysis (cross-case and collaborative) methods were employed. A purposive sampling technique was employed to select the study participants, namely five computing teacher trainees and two experts in critical systems thinking, human-computer interaction, computer science programming, and curriculum development. The computing teacher trainees collaborated with the initial data. At the same time, the experts contributed to the theory in the form of validation and provision of new insights that the teacher trainees overlooked. Some of the study results indicate that a more comprehensive stakeholder social contract is needed to remedy these problems. It was also observed that student profiling plays a significant role in computing learning and, if considered, would empower the computer instructor to accommodate student uniqueness. On the other hand, learner autonomy was considered critical as it empowers students to take ownership, take risks, continue learning, and critique learning.
Cited by 0Open access
Manuel Selva, Lionel Morel, Kévin Marquet · HAL (Le Centre pour la Communication Scientifique Directe) · 2016
The memory subsystem of modern multicore architectures is becoming more and more complex with the increasing number of cores integrated in a single computer. This complexity leads to profiling needs to let software developers understand how programs use the memory subsystem. Modern processors come with hardware profiling features to help building tools for these profiling needs. Regarding memory profiling, many processors provide means to monitor memory traffic and to sample read and write memory accesses. Unfortunately, these hardware profiling mechanisms are often very complex to use and are specific to each micro-architecture. In this report, we present numap, a library dedicated to the profiling of the memory subsytem of modern multicore architectures. numap is portable across many micro-architectures and comes with a clean application programming interface allowing to easily build profiling tools on top of it.
Cited by 1Open access
Jeremy Singer, Chris Kirkham · Science of Computer Programming · 2007
Cited by 11
C. Guerra-García, R. Juárez-Ramírez, S. Jiménez et al. · Programming and Computer Software · 2025
Organizations that aim to achieve their strategic objectives and rely on data to support operational and decision-making processes must possess a clear understanding of the extent to which their data fulfills established quality criteria. These criteria are typically enunciated through specific data quality dimensions. In academic and professional contexts, data quality assessment frameworks often necessitate the implementation of mechanisms for the systematic monitoring and control of data quality levels. The introduction of a methodology that integrates a qualitative assessment of data quality dimensions–supplemented by data profiling techniques to quantify selected dimensions–can significantly enhance the effectiveness and reliability of data utilization. The principal contribution of this proposal is the development of a comprehensive methodology for evaluating data quality through the combined use of survey-based diagnostic tools and data profiling techniques. Furthermore, the paper presents the outcomes of a case study, which serves to validate the proposed methodology within a real organizational setting.
Cited by 0
Milan Jovic, Matthias Hauswirth · Science of Computer Programming · 2010
Cited by 10
Plаmеnkа Borovskа, Emilyan Asenov, Vеskа Gаnchеvа · 2011
This paper suggest a model of parallel computation based on Bacteria Foraging metaheuristics for Job Shop Scheduling optimization problem. The parallel model is verified experimentally by Hybrid (MPI + OpenMP) programming implementations, run on heterogeneous computer cluster. The experimental study comprises parallel performance evaluation, parallel algorithm scalability analysis, profiling and evaluation of solution quality.
Cited by 2
Rajagopal Devarajan, Padmanabhan Rao, J Best et al. · The International Arab Journal of Information Technology · 2020
Unauthorized access in a personal computer or single system of a network for tracking the system access or theft the information is called attack/ hacking. An Intrusion detection System defined as an effective security technology, it detect, prevent and possibly react to computer related malicious activities. For protecting computer systems and networks from abuse used mechanism named Intrusion detection system. The aim of the study is to know the possibilities of Intrusion detection and highly efficient and effective prevent technique. Using this model identified the efficient algorithm for intrusion detection Behaviour Profiling Algorithm and to perform dynamic analysis using Statistical Approach model using log file which provides vital information about systems and the activities on them. The proposed algorithm implemented model it produced above 90%, 96% and 98% in the wired, wireless and cloud network respectively. This study concluded that, the efficient algorithm to detect the intrusion is behaviour profiling algorithm, while join with the statistical approach model, it produces efficient result. In further research, possibility to identify which programming technique used to store the activity log into the database. Next identify which algorithm is opt to implement the intrusion detection and prevention system by using big data even the network is wired, wireless or cloud network
Cited by 13Open access
Konstantin Läufer(** (eds, Konstantin Läufer, Gerald Baumgartner et al. · 1998
, Paper Using Static Single Assignment Form to Improve Flow-Insensitive Pointer Analysis Rebecca Hasti and Susan Horwitz (Computer Sciences Dept., University of Wisconsin - Madison) Abstract, Paper Edge Profiling vs. Path Profiling: The Showdown Thomas Ball, Peter Mataga (Bell Laboratories, Lucent Technologies), and Mooly Sagiv (TelAviv University) Abstract, Paper 3:30-4:00 Break 4:00-5:30 Technical Session II Action Transformation: An Application of Sort Inference Kent Lee (Dept. of Computer Science, Luther College) Abstract, Slides, Slide supplement: test0.action, Slide supplement: test0.sorts, Paper Integration of Software Development Documents with the Software Concordance Ethan Munson (Dept. of Electrical Engineering and Computer Science, University of Wisconsin - Milwaukee) Abstract, Paper Issues in the Design of SWAR Programming Models Randall J. Fisher and Hank Dietz (Dept. of Electrical and Computer Engineering, Purdue University) Abstract 5:30-6:00 MSPLS Spring '9...
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Alok Mysore · eScholarship (California Digital Library) · 2018
Programming tutorials often created with the goal of helping people perform complex software-based tasks in domains such as programming, data science, system administration, and computational research. However, it is tedious to create detailed step-by-step tutorials for tasks that span multiple interrelated Graphical User Interface (GUI) and command-line applications. Once these tutorials are created, it is also hard for tutorial creators to get fine-grained feedback about how learners are actually stepping through their tutorials and which parts lead to the most struggle.We address these challenges by creating two prototypes:- Torta: an end-to-end system that automatically generates step-by-step GUI and command-line app tutorials by demonstration, provides an editor to trim, organize, and add validation criteria to these tutorials, and provides a web-based viewer that can validate step-level progress and automatically run certain steps.- Porta: a system that automatically tracks how users navigate through a tutorial webpage and what actions they take on their computer. Porta tracks running shell commands, invoking compilers, and logging into remote servers and surfaces this trace data in the form of profiling visualizations. The visualization augments the tutorial with heatmaps of activity hotspots and markers that expand to show event details, error messages, and embedded screencast videos of user actions.The core technical insight that underpins both these systems is that Operating-system-wide activity tracing makes it possible to easily generate new tutorials and profile existing tutorials.An exploratory study on 10 computer science teaching assistants (TAs) and 6 students found that they all preferred the experience and results of using Torta to record and consume tutorials respectively.A user study of 3 tutorial creators and 12 students who followed their tutorials found that Porta enabled both the tutorial creators and the students to provide more specific, targeted, and actionable feedback about how to improve these tutorials.These systems together open up possibilities of easing the use of creating quality step-by-step tutorials and user testing existing instructional material in a more systemic and scalable manner.
Cited by 0Open access
Jin Shi, Shoubo Cao, Aleksei Grigorev et al. · Cancer Management and Research · 2018
We established an individualized CTA profiling in resected stage III NSCLC based on 10 CTA expression. With the help of computer programming language, the goal of the maximum CTA expression coverage was reached by using the least CTA combination based on sex, smoking history, and histology. These results were significant for the further study of CTA-specific T-cell immunotherapy.
Cited by 9Open access
Aibek Sarimbekov, Andreas Sewe, Walter Binder et al. · Science of Computer Programming · 2012
Cited by 26
Georgios Tournavitis, Björn Franke · 2010
In recent years multi-core computer systems have left the realm of high-performance computing and virtually all of today's desktop computers and embedded computing systems are equipped with several processing cores. Still, no single parallel programming model has found widespread support and parallel programming remains an art for the majority of application programmers. In addition, there exists a plethora of sequential legacy applications for which automatic parallelization is the only hope to benefit from the increased processing power of modern multi-core systems. In the past automatic parallelization largely focused on data parallelism. In this paper we present a novel approach to extracting and exploiting pipeline parallelism from sequential applications. We use profiling to overcome the limitations of static data and control flow analysis enabling more aggressive parallelization. Our approach is orthogonal to existing automatic parallelization approaches and additional data parallelism may be exploited in the individual pipeline stages. The key contribution of this paper is a whole-program representation that supports profiling, parallelism extraction and exploitation. We demonstrate how this enhances conventional pipeline parallelization by incorporating support for multi-level loops and pipeline stage replication in a uniform and automatic way. We have evaluated our methodology on a set of multimedia and stream processing benchmarks and demonstrate speedups of up to 4.7 on a eight-core Intel Xeon machine.
Cited by 46
Anthony M. Sloane, Matthew Roberts · Science of Computer Programming · 2014
Cited by 2