Closed Source Software Projects Research Articles

Classifying code comments in Java software systems

Code comments are a key software component containing information about the underlying implementation. Several studies have shown that code comments enhance the readability of the code. Nevertheless, not all the comments have the same goal and target audience. In this paper, we investigate how 14 diverse Java open and closed source software projects use code comments, with the aim of understanding their purpose. Through our analysis, we produce a taxonomy of source code comments; subsequently, we investigate how often each category occur by manually classifying more than 40,000 lines of code comments from the aforementioned projects. In addition, we investigate how to automatically classify code comments at line level into our taxonomy using machine learning; initial results are promising and suggest that an accurate classification is within reach, even when training the machine learner on projects different than the target one. Data and Materials [https://doi.org/10.5281/zenodo.2628361].

Rate-Based Queueing Simulation Model of Open Source Software Debugging Activities

Open source software (OSS) approach has become increasingly prevalent for software development. As the widespread utilization of OSS, the reliability of OSS products becomes an important issue. By simulating the testing and debugging processes of software life cycle, the rate-based queueing simulation model has shown its feasibility for closed source software (CSS) reliability assessment. However, the debugging activities of OSS projects are different in many ways from those of CSS projects and thus the simulation approach needs to be calibrated for OSS projects. In this paper, we first characterize the debugging activities of OSS projects. Based on this, we propose a new rate-based queueing simulation framework for OSS reliability assessment including the model and the procedures. Then a decision model is developed to determine the optimal version-updating time with respect to two objectives: minimizing the time for version update, and maximizing OSS reliability. To illustrate the proposed framework, three real datasets from Apache and GNOME projects are used. The empirical results indicate that our framework is able to effectively approximate the real scenarios. Moreover, the influences of the core contributor staffing levels are analyzed and the optimal version-updating times are obtained.

Software project management: Theory of constraints, risk management, and performance evaluation

Constraints and risks are two critical factors that affect software project performance; more attention needs to be paid to constraints and risks in order to improve performance. In this paper, investigation will take place to determine the relation between those three factors. An enhanced model has been proposed to describe how these factors affect each other. As an application, the performance is examined for both open and closed source software projects in terms of some constraints and risk factors. Moreover, solutions for controlling both constraints and risks are provided. For constraints, project activities scheduling is enhanced using a genetic algorithm. For risks, RISKIT is briefly explained as a risk management methodology.

An empirical study of open-source and closed-source software products

We describe an empirical study of open-source and closed-source software projects. The motivation for this research is to quantitatively investigate common perceptions about open-source projects, and to validate these perceptions through an empirical study. We investigate the hypothesis that open-source software grows more quickly, but does not find evidence to support this. The project growth is similar for all the projects in the analysis, indicating that other factors may limit growth. The hypothesis that creativity is more prevalent in open-source software is also examined, and evidence to support this hypothesis is found using the metric of functions added over time. The concept of open-source projects succeeding because of their simplicity is not supported by the analysis, nor is the hypothesis of open-source projects being more modular. However, the belief that defects are found and fixed more rapidly in open-source projects is supported by an analysis of the functions modified. We find support for two of the five common beliefs and conclude that, when implementing or switching to the open-source development model, practitioners should ensure that an appropriate metrics collection strategy is in place to verify the perceived benefits.