Code Error Research Articles

Constant Values Distribution Investigation in the C Programs Source Code

Currently, software engineering plays a key role in software development, one of the criteria for the development of which is the investigation of its factology and various scientific and practical patterns. An important aspect of this area is the logic of program execution, operating with internal data, and, in particular, constant values, the identification of patterns in which actualizes this research. The main applications of this pattern include obtaining fundamental knowledge about algorithms, creating new and expanding existing metrics for evaluating and comparing program code, developing methods for its optimization, using it in genetic programming, etc.The purpose of this article is to obtain the frequency distribution of constant values in the source code of programs in the C programming language.The essence of the presented approach is to create a method for statistical analysis of the text of the source codes of programs contained in the ExeBench dataset (which consists of a huge amount of source code of functions in the C programming language, their assembler code for various processor architectures, compilation errors and other information).The proposed method is based on the use of algorithms for lexical and syntactic analysis of source code functions, semantic definition of constant types, and conversion of the recording of programming language symbols into the corresponding numeric or string values.The method has an implementation in the form of a software tool in the Python programming language, given in the form of an intuitive pseudocode. Experiments using this prototype allowed us to obtain the desired distribution of constant values for the source code of programs in the C programming language. Analysis of the obtained results allowed us to make a number of important theoretical and practical conclusions regarding the most frequently used constants, the correspondence of the obtained distribution to the Zipf law and its proximity to the exponential function, the anomalous appearance of a number of constants in the Top 50, etc.The scientific novelty of the proposed approach lies in the fact that the distribution of constant values for the source code of programs in the C programming language is obtained for the first time.The theoretical significance consists in obtaining new fundamental knowledge regarding the features and patterns of source code constructions, which can be extended to other programming languages.The practical significance consists in applying the distribution to a wide range of tasks, including the author's genetic reverse engineering, which in itself is a qualitatively new direction.

Creating the Slider Tester Repair Recommendation System to Enhance the Repair Step by Using Machine Learning

This project aims to develop a recommendation system to mitigate looping issues in HDD slider testing using the Amber testing machine (Machine A). Components simulating the HDD often fail and require repair before re-testing. However, post-repair, there is a 34% probability that the component (referred to as Product A) will experience looping, characterized by repeated failures with error code A. This recurring issue significantly hampers testing efficiency by reducing the number of successful slider tests. To address this challenge, we propose a dual-approach recommendation system that provides technicians with actionable insights to minimize the occurrence of looping. For previously analyzed components, a collaborative filtering technique utilizing implicit ratings is employed to generate recommendations. For new components, for which prior data are unavailable, a cosine similarity approach is applied to suggest optimal actions. An automatic training system is implemented to retrain the model as new data become available, ensuring that the recommendation system remains robust and effective over time. The proposed system is expected to offer precise guidance to technicians, thereby improving the overall efficiency of the testing process by reducing the frequency of looping issues. This work represents a significant advancement in enhancing operational reliability and productivity in HDD slider testing.

Full-duplex dynamic TDMA scheme and clock synchronization and compensation method for the multi-user UWOC system.

In this Letter, we propose a full-duplex dynamic time division multiple access (FDD-TDMA) scheme for multi-user underwater wireless optical communication (UWOC). It supports full-duplex communication through wavelength division duplex (WDD) and enhances the system throughput using dynamic time resource allocation. Additionally, a clock synchronization and compensation method is proposed for precise clock synchronization without time-keeping. With the proposed FDD-TDMA scheme and the clock synchronization and compensation method, we establish a two-user UWOC system based on on-off keying (OOK) modulation. Experiments are conducted in a 10 m water pool environment. The experimental results show that the designed system can achieve a data rate of 25 Mbps without error codes and 40 Mbps with a bit error rate (BER) below the forward error correction (FEC) limit. The FDD-TDMA scheme notably improves the system throughput when communication demands among users are variable compared to the conventional time division multiple access (TDMA). Moreover, a reduction in phase deviations from microseconds to ten nanoseconds is achieved by the clock synchronization and compensation method.

Performance analysis of multiuser mmWave DCT-spread CP-Less OFDM communication system

In this paper, we propose a framework for multiuser mmWave DCT-Spread CP-less OFDM communication system and analyze it comprehensively. Due to excessive cyclic prefix (CP) usage in conventional multicarrier systems, spectral efficiency reduces and increases transmission latency. Our proposed system enhances spectral efficiency and reduces transmission latency. We introduce an image encryption algorithm based on DNA encoding combined with a chaotic map is introduced to enhance physical layer security (PLS). The impact of block diagonalization (BD) channel precoding for multiuser interference (MUI) reduction and designed subcarrier mapping with time-domain Tukey windowing for out-of-band (OOB) power emission reduction are investigated. In addition, the paper studies the applicability of discrete cosine transforms (DCT)-Spreading for peak-to-average power ratio (PAPR) reduction. Simulation results demonstrate that Turbo and Repeat and Accumulate (RA) channel coding and minimum mean square error (MMSE) and Cholesky decomposition (CD)-based zero-forcing (ZF) signal detection schemes improve bit error rate (BER) performance of the proposed system for different users.

Machine learning for efficient generation of universal photonic quantum computing resources

We present numerical results from simulations using deep reinforcement learning to control a measurement-based quantum processor—a time-multiplexed optical circuit sampled by photon-number-resolving detection—and find it generates squeezed cat states quasi-deterministically, with an average success rate of 98%, far outperforming all other proposals. Since squeezed cat states are deterministic precursors to the Gottesman–Kitaev–Preskill (GKP) bosonic error code, this is a key result for enabling fault tolerant photonic quantum computing. Informed by these simulations, we also discovered a one-step quantum circuit of constant parameters that can generate GKP states with high probability, though not deterministically.

Hyperkalemia Incidence in Patients With Non-Dialysis Chronic Kidney Disease: A Large Retrospective Cohort Study From United States Clinical Care

Estimates of the incidence of hyperkalemia in patients with chronic kidney disease (CKD) vary widely. Our objective was to estimate hyperkalemia incidence in patients with CKD from routine clinical care, including by level of kidney damage or function and among important patient subgroups. Retrospective cohort study. 1,771,900 patients with stage 1-4 CKD identified from the US Optum De-Identified electronic health records database. Impaired kidney damage or function level at baseline based on urinary albumin-creatinine ratio (UACR) and estimated glomerular filtration rate (eGFR), respectively, and selected patient subgroups. Hyperkalemia: 2 elevated serum potassium values (≥5.5mmol/L) from the inpatient setting (2-24 hours apart) or outpatient setting (maximum 7 days apart), or 1 elevated serum potassium value plus pharmacotherapy initiation or hyperkalemia diagnosis (maximum 3 days apart). Incidence rates of hyperkalemia were calculated. Estimates were stratified by UACR and eGFR level at baseline and patient subgroups. Over a mean follow-up of 3.9 years, the incidence of hyperkalemia was 3.37 events/100 person-years (95% confidence intervals, 3.36-3.38). Higher incidence rates were observed with increased UACR and lower eGFR. Highest rates were observed with UACR≥3,500 (up to 19.1/100 person-years) irrespective of decreased eGFR level. High rates also occurred in patients with type 2 diabetes mellitus (T2DM, 5.43/100 person-years), heart failure (8.7/100 person-years), and those prescribed steroidal mineralocorticoid receptor antagonists (sMRAs, 7.7/100 person-years). Potential misclassification of variables from possible medical coding errors; potential data incompleteness issues if patients received care at institutions not included in Optum. Hyperkalemia is a frequent occurrence in CKD, particularly in patients with T2DM, heart failure, or prescribed sMRAs, indicating the need for regular serum potassium and UACR monitoring in this patient population to help mitigate risk.

Evolution of word production errors after typicality-based semantic naming treatment in individuals with aphasia

ABSTRACT Background The Complexity Account for Treatment Efficacy (CATE) has been applied to semantic typicality in aphasia naming therapy, i.e. training atypical items of a category would improve naming of typical untrained-related items. However, most aphasia treatment studies have implemented a binary scoring system to measure response accuracy, which may not thoroughly reveal linguistic mechanisms underlying aphasia recovery. Aims The current study investigated the evolution of error patterns following typicality-based Semantic Features Analysis (SFA) treatment in individuals with post-stroke aphasia. Methods & Procedures Thirty individuals with chronic aphasia participated in a typicality-based SFA treatment, and ten individuals with chronic aphasia served as controls. The treatment participants and controls completed a naming screener before and after either a treatment period or a no-treatment period, respectively. Responses were coded using an error coding scale and analyzed with mixed-effects models. Outcomes & Results Treatment participants demonstrated significant treatment and generalization effects, as captured by significant improvements on the error coding system for both trained and untrained items. However, the group-level analysis did not reveal significant generalization from training atypical items to untrained typical items. Subgroup analyses based on participants’ performance in treatment showed significant gains in naming untrained typical items from training atypical items in responders, but improved naming of untrained atypical items from training typical items in nonresponders. Conclusions These findings suggest different linguistic mechanisms underlying aphasia recovery and highlight the importance of investigating treatment and generalization effects using a fine-grained error coding system as a complement to a binary scoring system.

Mitigating Temporal Fragility in the XY Surface Code

An important outstanding challenge that must be overcome in order to fully utilize the XY surface code for correcting biased Pauli noise is the phenomenon of fragile temporal boundaries that arises during the standard logical state-preparation and measurement protocols. To address this challenge we propose a new logical state-preparation protocol based on locally entangling qubits into small Greenberger-Horne-Zeilinger-like states prior to making the stabilizer measurements that place them in the XY-code state. We prove that in this new procedure O(n) high-rate errors along a single lattice boundary can cause a logical failure, leading to an almost quadratic reduction in the number of fault configurations compared to the standard state-preparation approach. Moreover, the code becomes equivalent to a repetition code for high-rate errors, guaranteeing a 50% code-capacity threshold during state preparation for infinitely biased noise. With a simple matching decoder we confirm that our preparation protocol outperforms the standard protocol in terms of both threshold and logical error rate in the fault-tolerant regime where measurements are unreliable and at experimentally realistic biases. We also discuss how our state-preparation protocol can be inverted for similar fragile-boundary-mitigated logical-state measurement. Published by the American Physical Society 2024

Coherent errors in stabilizer codes caused by quasistatic phase damping

Coherent errors in stabilizer codes caused by quasistatic phase damping

Spatio-temporal adaptive algorithm using Hamming code based on 3D-MIMO wireless channel model

Space-time coding is an effective method for constructing communication systems while saving bandwidth, taking into account the shortage of frequency resources and power in fading channels, which is implemented based on the advantages of using adaptive antenna arrays. Currently, WiMAX radio access technology has become widespread; its use is justified in conditions of direct visibility between the base and mobile stations, but in a city with dense buildings and in the presence of organized interference, its use leads to an increase in the likelihood of bit errors. At the same time, the combination of OFDM (orthogonal frequency division multiplexing) and MIMO (spatial coding) technologies based on adaptive antenna arrays significantly reduces the probability of bit errors, and therefore increases the throughput of the communication system. The use of adaptive space-time devices at the outputs of antenna arrays makes it possible to select a signal path with maximum power and with a minimum error in receiving OFDM pilot subcarriers, even in the absence of direct visibility between the base and mobile stations and in conditions of active interference. In addition, the use of a 3D model of the communication channel will allow us to evaluate the effectiveness of the communication system model in real operating conditions. The goal of the work is to solve the problem of additionally increasing noise immunity in communication systems in conditions of numerous reflections caused by dense buildings in urban environments, using a combination of Hamming code, OFDM and an algorithm for adaptive spatio-temporal signal processing in receivers such as SISO (Singl Input – Singl Output), and MIMO (Multiply Input – Multiply Output), built on adaptive antenna arrays. The work calculated the weight coefficients of the adaptation algorithm using the theory of eigenvalues and eigenvectors of the spatial correlation matrix of signals at the outputs of the adaptive antenna arrays. Modeling of algorithms and a 3D model of the communication channel in Matlab using the Hamming code was carried out, as a result, an increase in the efficiency of error correction for the Hamming code was demonstrated, as well as a significant reduction in the probability of code errors and an increase in the performance of the communication system when using an adaptive algorithm. At the same time, the article uses the term “multipath” channel in contrast to the generally accepted, but incorrect “multibeam” channel, since multibeam can be a characteristic of an antenna system. The presented results confirm that when processing signals in a receiving system in a multipath channel with dense urban development, the use of adaptive spatiotemporal algorithms provides increased noise immunity and radio communication capacity, especially for image transmission when using unmanned aerial vehicles.

Design of Warehouse Information System for KCM Division Using Javascript

Increasingly advanced technological developments force business people to be adaptive, especially when there is an increase in production. The KCM division, one of the PT XYZ business units operating in the media sector, experienced increased production. This causes the production equipment to be borrowed irregularly, and information on the warehouse of production equipment is also difficult to find. The Warehouse Information System is the solution to this problem. This research aims to create a warehousing information system that records all information on borrowing production equipment, fulfills warehousing information needs, and solves several existing warehousing problems. This research method is an experimental one-shot case study designed with the Framework for the Applications of System Thinking (FAST) and using simple, easily accessible, and free tools, namely Google Spreadsheet and Javascript coding. The results of this research are that the KCM division's warehousing information system that has been created has been tested to be 100% capable of meeting information needs for borrowing production equipment and resolving existing warehousing problems based on system tests that have been carried out. It is recommended that this system be further developed in future research to overcome minor errors in coding.

Attitudes and Perceptions of Teachers and Chinese Students Towards Corrective Feedback in L2 Writing

Corrective feedback is a concept of second language acquisition (SLA). Previous studies have investigated the definitions, categories, and effectiveness of corrective feedback from myriad perspectives, often choosing English as a second language to conduct research on ESL students. Writing is a challenge for most L2 learners, and written feedback is part of overall corrective feedback. Much research has emphasized the effectiveness of corrective feedback, but how different types of corrective feedback influence L2 learners differently remains unknown. Few studies have combined students’ with teachers’ perceptions of written corrective feedback. Most only emphasized students’ preferences and few studies concentrated on Chinese students. As such, this paper aims to investigate the attitudes and perceptions of teachers and Chinese students towards written corrective feedback in L2 writing, which is beneficial to determine whether teachers can have awareness of students’ perceptions and satisfy their needs according to individual situations, helping them facilitate the accuracy of L2 writing. The results reveal that differences exist between Chinese students’ and teachers’ preferences for written corrective feedback in L2 writing. Both groups think written corrective feedback is effective to enhance L2 writing, and most Chinese students and teachers affirm that different strategies of written corrective feedback should be given according to different error types. Finally, in teachers’ opinions, the most appropriate written corrective feedback for Chinese students is direct corrective feedback and metalinguistic feedback (e.g. using error codes and metalinguistic codes), while Chinese students believe that the most appropriate written corrective feedback is direct and indirect corrective feedback.

Deterministic generation of highly squeezed GKP states in ultracold atoms

We demonstrate a method for encoding Gottesman–Kitaev–Preskill (GKP) error-correcting qubits with single ultracold atoms trapped in individual sites of a deep optical lattice. Using quantum optimal control protocols, we demonstrate the generation of GKP qubit states with 10 dB squeezing, which is the current minimum allowable squeezing level for use in surface code error correction. States are encoded in the vibrational levels of the individual lattice sites and generated via phase modulation of the lattice potential. Finally, we provide a feasible experimental protocol for the realization of these states. Our protocol opens up possibilities for generating large arrays of atomic GKP states for continuous-variable quantum information.

An EEG-Based Neuroplastic Approach to Predictive Coding in People With Schizophrenia or Traumatic Brain Injury.

Despite different etiologies, people with schizophrenia (SCZ) or with traumatic brain injury (TBI) both show aberrant neuroplasticity. One neuroplastic mechanism that may be affected is prediction error coding. We used a roving mismatch negativity (rMMN) paradigm which uses different lengths of standard tone trains and is optimized to assess predictive coding. Twenty-five SCZ, 22 TBI (mild to moderate), and 25 healthy controls were assessed. We used a frequency-deviant rMMN in which the number of standards preceding the deviant was either 2, 6, or 36. We evaluated repetition positivity to the standard tone immediately preceding a deviant tone (repetition positivity [RP], to assess formation of the memory trace), deviant negativity to the deviant stimulus (deviant negativity [DN], which reflects signaling of a prediction error), and the difference wave between the 2 (the MMN). We found that SCZ showed reduced DN and MMN compared with healthy controls and with people with mild to moderate TBI. We did not detect impairments in any index (RP, DN, or MMN) in people with TBI compared to controls. Our findings suggest that prediction error coding assessed with rMMN is aberrant in SCZ but intact in TBI, though there is a suggestion that severity of head injury results in poorer prediction error coding.

Construction of Qــ Ary(n,Μ,d )ــ Codes in PG (2,9)

This study's main objective is to offer the connection between the projective plane of order nine & the field of coding theory. An incidence matrix has been developed using the parameters n (code length), d (code min. distance), and e (code error correcting). The greatest value of size code M across a limited field of the ninth order has also been determined. There are a few theorems and examples provided.

A family of permutationally invariant quantum codes

We construct a new family of permutationally invariant codes that correct t Pauli errors for any t≥1. We also show that codes in the new family correct quantum deletion errors as well as spontaneous decay errors. Our construction contains some of the previously known permutationally invariant quantum codes as particular cases, which also admit transversal gates. In many cases, the codes in the new family are shorter than the best previously known explicit permutationally invariant codes for Pauli errors and deletions. Furthermore, our new code family includes a new ((4,2,2)) optimal single-deletion-correcting code. As a separate result, we generalize the conditions for permutationally invariant codes to correct t Pauli errors from the previously known results for t=1 to any number of errors. For small t, these conditions can be used to construct new examples of codes by computer.

Enhancing Security in Industrial Application Development: Case Study on Self-Generating Artificial Intelligence Tools

The emergence of security vulnerabilities and risks in software development assisted by self-generated tools, particularly with regard to the generation of code that lacks due consideration of security measures, could have significant consequences for industry and its organizations. This manuscript aims to demonstrate how such self-generative vulnerabilities manifest in software programming, through a case study. To this end, this work undertakes a methodology that illustrates a practical example of vulnerability existing in the code generated using an AI model such as ChatGPT, showcasing the creation of a web application database, SQL queries, and PHP server-side. At the same time, the experimentation details a step-by-step SQL injection attack process, highlighting the hacker’s actions to exploit the vulnerability in the website’s database structure, through iterative testing and executing SQL commands to gain access to sensitive data. Recommendations on effective prevention strategies include training programs, error analysis, responsible attitude, integration of tools and audits in software development, and collaboration with third parties. As a result, this manuscript discusses compliance with regulatory frameworks such as GDPR and HIPAA, along with the adoption of standards such as ISO/IEC 27002 or ISA/IEC 62443, for industrial applications. Such measures lead to the conclusion that incorporating secure coding standards and guideline—from organizations such as OWASP and CERT training programs—further strengthens defenses against vulnerabilities introduced by AI-generated code and novice programming errors, ultimately improving overall security and regulatory compliance.

Autoparametric Resonance Extending the Bit-Flip Time of a Cat Qubit up to 0.3 s

Cat qubits, for which logical |0⟩ and |1⟩ are coherent states |±α⟩ of a harmonic mode, offer a promising route towards quantum error correction. Using dissipation to our advantage so that photon pairs of the harmonic mode are exchanged with single photons of its environment, it is possible to stabilize the logical states and exponentially increase the bit-flip time of the cat qubit with the photon number |α|2. A large two-photon dissipation rate κ2 ensures fast qubit manipulation and short error-correction cycles, which are instrumental to correct the remaining phase-flip errors in a repetition code of cat qubits. Here, we introduce and operate an autoparametric superconducting circuit that couples a mode containing the cat qubit to a lossy mode whose frequency is set at twice that of the cat mode. This passive coupling does not require a parametric pump, and it reaches a rate κ2/2π≈2 MHz. With such a strong two-photon dissipation, bit-flip errors of the autoparametric cat qubit are prevented for a characteristic time up to 0.3 s with only a mild impact on phase-flip errors. In addition, we illustrate how the phase of a quantum superposition between |α⟩ and |−α⟩ can be arbitrarily changed by driving the harmonic mode while keeping the engineered dissipation active. Published by the American Physical Society 2024

Leveraging ChatGPT to Enhance Debugging: Evaluating AI-Driven Solutions in Software Development

Debugging is a crucial component of software development, focusing on identifying and correcting problems, commonly known as bugs, in code. Recent advances in artificial intelligence (AI) have introduced new opportunities for automating this process using language models such as ChatGPT. This article explores the use of ChatGPT in addressing programming challenges, assessing its ability to detect, anticipate, and rectify errors in code. The research examines ChatGPT’s debugging capabilities by evaluating its natural language processing, knowledge representation, and pattern recognition skills. The text compares ChatGPT’s performance with conventional debugging tools through real-world examples and case studies. The findings suggest that ChatGPT can effectively assist in debugging by automatically identifying and correcting errors, predicting issues early in the development phase, and clarifying the underlying causes of bugs. However, the system’s effectiveness depends on the quality of its training data and architecture. While ChatGPT has the potential to be a valuable tool in the debugging process, it is essential to combine it with traditional debugging methods to ensure accuracy and reliability. Further research is needed to enhance ChatGPT’s capabilities and evaluate its effectiveness in real-world scenarios.

Can GPU performance increase faster than the code error rate?

Graphics processing units (GPUs) are the reference architecture to accelerate high-performance computing applications and the training/interference of convolutional neural networks. For both these domains, performance and reliability are two of the main constraints. It is believed that the only way to increase reliability is to sacrifice performance, e.g., using redundancies. We show in this paper that this is not always the case. As a very promising result, we found that most GPUs performance improvements also bring the benefit of increasing the number of executions correctly completed before experiencing a silent data corruption (SDC). We consider four different common GPUs’ performance optimizations: architectural solutions, software implementations, compiler optimizations, and threads degree of parallelism. We compare different implementations of a variety of parallel codes and, through beam experiments and applications profiling, we show that the performance improvement typically (but not necessarily) increases the GPU SDC rate. Nevertheless, for the vast majority of the configurations the performance gain is much higher than the SDC rate increase, allowing to process a higher amount of correct data. As we show, the programmer choices can increase up to 25×\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$25\ imes {}$$\\end{document} the number of correctly completed executions without redesigning the algorithm nor including specific hardening solutions.