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A study concerning the bug tracking applications
... Bugzilla, one of the bugtracking system, is for tracking bug in mozilla's products. It had 14 attributes: summary, status, severity, resolution, assigned_to, product, component, priority, cclist_accesible, version, op_sys, reporter_accessible, qa_contact [1]. From those attributes, severity was considered important for bug report [1] because the completion of fixing bug was based on the type of bug severity. ...
... It had 14 attributes: summary, status, severity, resolution, assigned_to, product, component, priority, cclist_accesible, version, op_sys, reporter_accessible, qa_contact [1]. From those attributes, severity was considered important for bug report [1] because the completion of fixing bug was based on the type of bug severity. Moreover, user interpretation of the type of bug severity was must be precise. ...
Determination of bug severity level is needed in fixing a bug. Actually, in a bug-tracking system, there are around 14 attributes used for defining a bug. But, all this time we do not know which attributes are highly influential for this. In this research, a new model of severity type classification using the Infogain method for Bugzilla is proposed. As for the classification process, we use the Support Vector Machine, because this method is suitable for handling massive data records. In this research, 8 bug attributes and 17.746 records of bug reports are involved. From the result of the experiment, we recommend five attributes that can be used effectively in classifying the severity types with a minimal value of info gain 0,33 which is component, qa_contact, summary, cc_list, and product. The combination of those 5 attributes resulting in 99,83% accuracy of severity types classification.
... Each of such bugs should be monitored, evaluated, and prioritized for debugging. Many bug tracking systems exist nowadays (e.g., Bugzilla, Jira, Mantis etc.) [25] to track the bugs reported by the customers. The main benefit of a bug-tracking system is to provide a clear centralized overview of the development and its state. ...
Today’s mobile gadgets are seamlessly incorporating innovative features demanded by the users. Most often, the applications contain bugs or functionality issues reported by the customers. The developers are responsible for reproducing such reported bugs, which are written in natural languages. Reproducing bugs from bug reports make the bug resolution inefficient. Nowadays, various methods are adopted to reproduce crash reports for android applications. But bug reproduction for non-android applications is still a challenging task. This paper proposes a novel approach that is capable of doing bug reproduction from bug reports to help the developers to solve the functionality issues of non-android applications in an automated manner. This approach uses a UI tester called the GUI engine, which is an excel sheet. The use cases which are to be tested can be filled in the GUI engine. All the use cases are to be filled based on a particular syntax. For that purpose, the developer can make use of a set of yaml files containing all the GUI information for all the screens of the application under test. The use cases are executed in the GUI engine and conclusions are made based on the test result. The GUI engine displays two colors green and red showing the working and failing of GUI components of the application under test. So that the developer can easily identify the failing components and take actions accordingly. The test has been done with more than 1000 test cases for one region and the result shows that almost all GUI components work for this method except for animation. It has tested for software developed for US, Europe, and German regions. Also, the proposed method is found to be much faster and efficient than the existing as well as manual testing methods.
... Each of such bugs should be monitored, evaluated, and prioritized for debugging. Many bug tracking systems exist nowadays (e.g., Bugzilla, Jira, Mantis etc.) [25] to track the bugs reported by the customers. The main benefit of a bug-tracking system is to provide a clear centralized overview of the development and its state. ...
PT. XYZ is one of the companies which engages in fast moving consumer goods (FMCG) sector and has soft drinks as its main product. In supporting the product distribution to its customers, PT XYZ has several administrative offices and distribution centers (DC) which spread across each region. The DC has main function as the warehouse which has storage activity before the products are distributed. One of the DC is located in Bandung, West Java. DC Bandung itself received product shipments from three factories, such as Cibitung, Cakung and Tambun. Related to the product shipment, DC Bandung has not determined the replenishment policy, and this condition results over stock at some periods, due to the unscheduled delivery time and undetermined product quantity. This condition gives a big impact to the total inventory cost that has to be borne by DC Bandung. This research was conducted to give the proposal of product replenishment policy with mixed-integer programming method, as one of the linear programming types, which aimed to minimize over stock and total holding cost in DC Bandung. Mathematical model is also involved in this research as an approximation to the real replenishment system in the DC. The results of application of the proposed method are in the form of analytical solution, such as order quantity, and reorder point of each product that will give an impact to the total unit inventory and the total holding cost in the DC. The results calculation of replenishment policy provide savings on total inventory costs as much as IDR 23,800,981.20
... Page 4992 the incoming technical queries (6,9,20). Similarly in software development area it helps in tracking the bugs. ...
Bug tracking tools help stake holders involved in software projects to detect bugs, resolve them and then ensure to have contingency and preventive measures so that detected bugs are not repeated in the future projects. The present generation of software developed, are enormous and extensive in size inorder to meet customer requirements and hence presence of bugs is impossible to avoid. Hence it is very important to know the functionalities and features of different bug trackers namely the open source ones so that compatible and relevant tools can be chosen efficiently for bug tracking purposes. The paper provides description of ten popular bug tracking tools and the major features of these tools are discussed in details yet concise manner. A comparative matrix is presented which helps to compare the tools, analyse them and find a tool which supports majority of the functionalities expected from an ideal bug tracking tool. © 2016, International Journal of Pharmacy and Technology. All rights reserved.
... An extensive overview and comparison of bug reporting systems or issue tracking systems may be found on Internet, or in relevant literature [12], [13] etc. Deeper analysis and bug classification is reported by Zaman et al. [14], or Lal and Sureka [13], etc. However, there is no study that covers cloud aspects of the bug reporting solutions. ...
Software issues contain units of work to fix, improve or create new threads during the development and facilitate communication among the team members. Assigning an issue to the most relevant team member and determining a category of an issue is a tedious and challenging task. Wrong classifications cause delays and rework in the project and trouble among the team members. This thesis proposes a set of carefully curated linguistic features for shallow machine learning methods and compares the performance of shallow and ensemble methods with deep language models. Unlike the state-of-the-art, we assign issues to four roles (designer, developer, tester, and leader) rather than to specific individuals or teams to contribute to the generality of our solution. We also consider the level of experience of the developers to reflect the industrial practices in our solution formulation. We employ a classification approach to categorize issues into distinct classes, namely bug, new feature, improvement, and other. Additionally, we endeavor to further classify bugs based on the specific type of modification required. We collect and annotate five industrial data sets from one of the top three global television producers to evaluate our proposal and compare it with deep language models. Our data sets contain 5324 issues in total. We show that an ensemble classifier of shallow techniques achieves 0.92 for issue assignment and 0.90 for issue classification in accuracy which is statistically comparable to the state-of-the-art deep language models. The contributions include the public sharing of five annotated industrial issue data sets, the development of a clear and comprehensive feature set, the introduction of a novel label set and the validation of the efficacy of an ensemble classifier of shallow machine learning techniques.
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