9 results about "Software bug" patented technology

A computer-implemented method for runtime detection of a software error in a predetermined software element is disclosed. The method comprises the following steps: a) Creating at least one replica software element of the predetermined software element, in particular during a creation phase, such that a test set of executable software elements is created based on the predetermined software element, wherein one or more delay elements (716) are embedded in the at least one replica software element; b) Deployment of at least two executable software elements of the test set on at least one computing platform, in particular during a test phase; c) Comparing the processing results of the at least two executable software elements used on the computing platform in order to detect the software error.

An automated functional fault localization method for software product lines integrates techniques such as Spectrum-Based Fault Localization (SBFL), machine learning algorithms, data mining, and information theory. By utilizing code blocks as the detection granularity, it performs probability allocation from three perspectives: prediction, actual execution, and correlation. The suspiciousness values of code blocks are then computed using uncertainty reasoning algorithms, enabling the rapid identification of suspicious statements. Building on this, a more precise assessment of these statements is achieved by evaluating at three levels of granularity: global, local, and code block. This ultimately results in more efficient and accurate fault localization. The code blocks directly correspond to internal feature interactions, significantly enhancing the efficiency of searching for these interactions. For program statements with a higher likelihood of causing software errors, this method allows for quick identification and localization without manual intervention, thereby facilitating the maintenance of software product line systems.

Methods, systems, and apparatus for automatic detection of software bugs are disclosed. An example apparatus includes a comparator to compare reference code to input code to detect a source code error in the input code; a graph generator to generate a graphical representation of the reference code or the input code, the graphical representation to identify non-overlapping code regions; and a root cause determiner to determine a root cause of the source code error in the input code, the root cause based on the non-overlapping code regions.

This application discloses a server link fault location system, method, electronic device, and storage medium, relating to the field of server link testing technology. It collects physical layer and protocol layer data from data acquisition points using a data acquisition component, and controls a testing component to perform server link testing. The testing component includes a control module and an analysis module. The control module sends test commands to the server link. When a server link fault is detected, the analysis module obtains physical layer and protocol layer data from each data acquisition point from the acquisition component. Based on the acquired data, it determines the fault location and / or fault type of the server link, achieving automated link quality assessment and determining the fault location and fault type. This solves the problem that related technologies struggle to accurately locate fault locations and distinguish between hardware link faults and software errors through single stress tests, requiring manual fault location and resulting in low troubleshooting efficiency. Therefore, it achieves the technical effect of improving troubleshooting efficiency.

An automated program repair tool utilizes a neural transformer model with attention to predict the contents of a bug repair in the context of source code having a bug of an identified bug type. The neural transformer model is trained on a large unsupervised corpus of source code using a span-masking denoising optimization objective, and fine-tuned on a large supervised dataset of triplets containing a bug-type annotation, software bug, and repair. The bug-type annotation is derived from an interprocedural static code analyzer. A bug type edit centroid is computed for each bug type and used in the inference decoding phase to generate the bug repair.

Methods, systems, and computer-readable storage media for debugging errors occurring in software and can include actions of receiving a current bug ticket (CBT) including bug data descriptive of a bug occurring within a software system, prompting a LLM using a first prompt to return a first embedding representative of at least a portion of the CBT, determining a set of candidate historical bug tickets (HBTs) using the first embedding and a set of HBT embeddings, prompting the LLM using a second prompt to return a set of similar HBTs, the second prompt generated using the set of candidate HBTs, and updating the CBT to identify one or more HBTs in the set of similar HBTs.

The invention discloses an exception monitoring method and device, a storage medium and electronic equipment, and relates to the technical field of chips, and the method comprises the steps: responding to a condition that a target chip is in a running state, and monitoring the target chip through an exception monitoring program; when it is monitored that the target chip has the abnormal operation event, obtaining monitoring information of the abnormal monitoring program on the abnormal operation event and operation environment parameters corresponding to the abnormal operation event; determining an abnormal event type of the abnormal operation event based on the monitoring information; and generating abnormal information corresponding to the abnormal operation event according to the abnormal event type and the operation environment parameters, wherein the abnormal information is used for performing abnormal recovery on the abnormal operation event. According to the method, the abnormal event type of the abnormal operation event is determined based on the monitoring information, so that the exception is accurately distinguished; the exception information used for exception recovery is generated according to the exception event type and the operation environment parameters, so that the exception operation event is effectively recovered, and the processing efficiency of software errors is improved.

Managing source code change set commits to decrease time to identify software bugs in versions of a software project is provided. An initial order of relevant commits corresponding to the software project is determined in a priority queue based on a weight of each respective commit of the relevant commits. The initial order of the relevant commits is adjusted in the priority queue based on a build distance between the relevant commits of affected source files. A particular commit having a highest priority ranking is selected in the priority queue for build and test. The build and the test of the particular commit having the highest priority ranking in the priority queue is executed.

Embodiments of the present disclosure include techniques for decentralizing feature toggles. In certain embodiments, feature toggles are generated for features across a plurality of software systems. The feature toggles include annotations specifying dependencies across the plurality of software systems. The annotated feature toggles are stored in a central repository accessible by the plurality of software systems. When a feature toggle is enabled, feature toggles across the systems may be retrieved from the repository and analyzed by an LLM to determine which feature toggles may need to be updated to prevent a software error.