相关论文: Software Code Quality Measurement: Implications fr…

The use of learning-based techniques to achieve automated software vulnerability detection has been of longstanding interest within the software security domain. These data-driven solutions are enabled by large software vulnerability…

Any traditional engineering field has metrics to rigorously assess the quality of their products. Engineers know that the output must satisfy the requirements, must comply with the production and market rules, and must be competitive.…

Amidst the ever-expanding digital sphere, the evolution of the Internet has not only fostered an atmosphere of information transparency and sharing but has also sparked a revolution in software development practices. The distributed nature…

Software quality models provide either abstract quality characteristics or concrete quality measurements; there is no seamless integration of these two aspects. Reasons for this include the complexity of quality and the various quality…

Code-mixing is a frequent communication style among multilingual speakers where they mix words and phrases from two different languages in the same utterance of text or speech. Identifying and filtering code-mixed text is a challenging task…

Software review text fragments have considerably valuable information about users experience. It includes a huge set of properties including the software quality. Opinion mining or sentiment analysis is concerned with analyzing textual user…

Maintainability is a key quality attribute of successful software systems. However, its management in practice is still problematic. Currently, there is no comprehensive basis for assessing and improving the maintainability of software…

Due to their pivotal role in software engineering, considerable effort is spent on the quality assurance of software requirements specifications. As they are mainly described in natural language, relatively few means of automated quality…

Software is a unique entity that has laid a strong impact on all other fields either related or not related to software. These include medical, scientific, business, educational, defence, transport, telecommunication to name a few.…

Context: Scientific software plays an important role in critical decision making, for example making weather predictions based on climate models, and computation of evidence for research publications. Recently, scientists have had to…

Machine learning has been proven to be effective in various application areas, such as object and speech recognition on mobile systems. Since a critical key to machine learning success is the availability of large training data, many…

Recent research provides evidence that effective communication in collaborative software development has significant impact on the software development lifecycle. Although related qualitative and quantitative studies point out textual…

Code smells are symptoms of poor design quality. Since code review is a process that also aims at improving code quality, we investigate whether and how code review influences the severity of code smells. In this study, we analyze more than…

With even the most trivial of applications now being written on top of millions of lines code of libraries, API's, and programming languages, much of the complexity that used to exist when designing software has been abstracted away to…

Code complexity metrics such as cyclomatic complexity have long been used to assess software quality and maintainability. With the rapid advancement of large language models (LLMs) on coding tasks, an important yet underexplored question…

Software project failure and cancellation rates increase day by day due to technical failures, quality failures, lack of end client acceptance etc. and also the lack of proper management. There are a number of reasons affected by the…

Motivation: The question of what combination of attributes drives the adoption of a particular software technology is critical to developers. It determines both those technologies that receive wide support from the community and those which…

We apply machine learning to version control data to measure the quantity of effort required to produce source code changes. We construct a model of a `standard coder' trained from examples of code changes produced by actual software…

Infrastructure-as-code (IaC) is a practice to implement continuous deployment by allowing management and provisioning of infrastructure through the definition of machine-readable files and automation around them, rather than physical…

Software development is a collaborative process that involves various interactions among individuals and teams. TODO comments in source code play a critical role in managing and coordinating diverse tasks during this process. However, this…