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- Fault Localization (2)
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Articles 1 - 9 of 9
Full-Text Articles in Physical Sciences and Mathematics
Personalizing Software Development Practice Using Mastery-Based Coaching, Chris Boesch, Sandra Boesch
Personalizing Software Development Practice Using Mastery-Based Coaching, Chris Boesch, Sandra Boesch
Chris BOESCH
The authors previously developed a system to facilitate the self-directed learning and practicing of software languages in Singapore. One of the goals of this self-directed learning was to enable the development of student mentors who would then be able to assist other students during classroom sessions. Building on this work, the authors extended the platform to support personalized coaching with the goals of further enabling and preparing students to mentor their peers. This paper covers the challenges, insights, and features that were developed in order to develop and deploy this mastery-based coaching feature.
Will Fault Localization Work For These Failures? An Automated Approach To Predict Effectiveness Of Fault Localization Tools, Tien-Duy B. Le, David Lo
Will Fault Localization Work For These Failures? An Automated Approach To Predict Effectiveness Of Fault Localization Tools, Tien-Duy B. Le, David Lo
David LO
Debugging is a crucial yet expensive activity to improve the reliability of software systems. To reduce debugging cost, various fault localization tools have been proposed. A spectrum-based fault localization tool often outputs an ordered list of program elements sorted based on their likelihood to be the root cause of a set of failures (i.e., their suspiciousness scores). Despite the many studies on fault localization, unfortunately, however, for many bugs, the root causes are often low in the ordered list. This potentially causes developers to distrust fault localization tools. Recently, Parnin and Orso highlight in their user study that many debuggers …
Drone: Predicting Priority Of Reported Bugs By Multi-Factor Analysis, Yuan Tian, David Lo, Chengnian Sun
Drone: Predicting Priority Of Reported Bugs By Multi-Factor Analysis, Yuan Tian, David Lo, Chengnian Sun
David LO
Bugs are prevalent. To improve software quality, developers often allow users to report bugs that they found using a bug tracking system such as Bugzilla. Users would specify among other things, a description of the bug, the component that is affected by the bug, and the severity of the bug. Based on this information, bug triagers would then assign a priority level to the reported bug. As resources are limited, bug reports would be investigated based on their priority levels. This priority assignment process however is a manual one. Could we do better? In this paper, we propose an automated …
Multi-Abstraction Concern Localization, Tien-Duy B. Duy, Shaowei Wang, David Lo
Multi-Abstraction Concern Localization, Tien-Duy B. Duy, Shaowei Wang, David Lo
David LO
Concern localization refers to the process of locating code units that match a particular textual description. It takes as input textual documents such as bug reports and feature requests and outputs a list of candidate code units that need to be changed to address the bug reports or feature requests. Many information retrieval (IR) based concern localization techniques have been proposed in the literature. These techniques typically represent code units and textual descriptions as a bag of tokens at one level of abstraction, e.g., each token is a word, or each token is a topic. In this work, we propose …
Theory And Practice, Do They Match? A Case With Spectrum-Based Fault Localization, Tien-Duy B. Le, Ferdian Thung, David Lo
Theory And Practice, Do They Match? A Case With Spectrum-Based Fault Localization, Tien-Duy B. Le, Ferdian Thung, David Lo
David LO
Spectrum-based fault localization refers to the process of identifying program units that are buggy from two sets of execution traces: normal traces and faulty traces. These approaches use statistical formulas to measure the suspiciousness of program units based on the execution traces. There have been many spectrum-based fault localization approaches proposing various formulas in the literature. Two of the best performing and well-known ones are Tarantula and Ochiai. Recently, Xie et al. find that theoretically, under certain assumptions, two families of spectrum-based fault localization formulas outperform all other formulas including those of Tarantula and Ochiai. In this work, we empirically …
A Treeboost Model For Software Effort Estimation Based On Use Case Points, Luiz Capretz, Ali Nassif
A Treeboost Model For Software Effort Estimation Based On Use Case Points, Luiz Capretz, Ali Nassif
Luiz Fernando Capretz
Software effort prediction is an important task in the software development life cycle. Many models including regression models, machine learning models, algorithmic models, expert judgment and estimation by analogy have been widely used to estimate software effort and cost. In this work, a Treeboost (Stochastic Gradient Boosting) model is put forward to predict software effort based on the Use Case Point method. The inputs of the model include software size in use case points, productivity and complexity. A multiple linear regression model was created and the Treeboost model was evaluated against the multiple linear regression model, as well as the …
Managing The Business Of Software Product Line: An Empirical Investigation Of Key Business Factors, Faheem Ahmed, Luiz Capretz
Managing The Business Of Software Product Line: An Empirical Investigation Of Key Business Factors, Faheem Ahmed, Luiz Capretz
Luiz Fernando Capretz
Business has been highlighted as a one of the critical dimensions of software product line engineering. This paper’s main contribution is to increase the understanding of the influence of key business factors by showing empirically that they play an imperative role in managing a successful software product line. A quantitative survey of software organizations currently involved in the business of developing software product lines over a wide range of operations, including consumer electronics, telecommunications, avionics, and information technology, was designed to test the conceptual model and hypotheses of the study. This is the first study to demonstrate the relationships between …
Eef-Cas: An Effort Estimation Framework With Customizable Attribute Selection, Katarina Grolinger, Besa Muslimi, Miriam Capretz, Mark Benko
Eef-Cas: An Effort Estimation Framework With Customizable Attribute Selection, Katarina Grolinger, Besa Muslimi, Miriam Capretz, Mark Benko
Katarina Grolinger
Existing estimation frameworks generally provide one-size-fits-all solutions that fail to produce accurate estimates in most environments. Research has shown that the accomplishment of accurate effort estimates is a long-term process that, above all, requires the extensive collection of effort estimation data by each organization. Collected data is generally characterized by a set of attributes that are believed to affect the development effort. The attributes that most affect development effort vary widely depending on the type of product being developed and the environment in which it is being developed. Thus, any new estimation framework must offer the flexibility of customizable attribute …
Knowledge As A Service Framework For Disaster Data Management, Katarina Grolinger, Emna Mezghani, Miriam Capretz, Ernesto Exposito
Knowledge As A Service Framework For Disaster Data Management, Katarina Grolinger, Emna Mezghani, Miriam Capretz, Ernesto Exposito
Katarina Grolinger
Each year, a number of natural disasters strike across the globe, killing hundreds and causing billions of dollars in property and infrastructure damage. Minimizing the impact of disasters is imperative in today’s society. As the capabilities of software and hardware evolve, so does the role of information and communication technology in disaster mitigation, preparation, response, and recovery. A large quantity of disaster-related data is available, including response plans, records of previous incidents, simulation data, social media data, and Web sites. However, current data management solutions offer few or no integration capabilities. Moreover, recent advances in cloud computing, big data, and …