Using Learning Styles of Software Professionals to Improve their Inspection Team Performance

  title={Using Learning Styles of Software Professionals to Improve their Inspection Team Performance},
  author={Anurag Goswami and Gursimran Singh Walia and Abhinav Singh},
Validating Requirements Reviews by Introducing Fault-Type Level Granularity: A Machine Learning Approach
This work aims at automation of fault-consolidation step by using supervised machine learning algorithms that can effectively isolate faults from non-faults during the fault consolidation step of requirements inspections. Expand
Application of back-translation: a transfer learning approach to identify ambiguous software requirements
By augmenting requirements using BT, ULMFiT got a higher accuracy than SVM, Logistic Regression, and Multinomial Naive Bayes classifier, and provides some promising insights on how transfer learning and text augmentation can be applied to small data sets in requirements engineering. Expand
Automating Key Phrase Extraction from Fault Logs to Support Post-Inspection Repair of Software Requirements
This research paper aims at developing an automated approach to identify fault prone requirements in a software requirement specification (SRS) document to mitigate the fault propagation to laterExpand
iSENSE: Completion-Aware Crowdtesting Management
The results show that ISENSE can provide managers with greater awareness of testing progress to achieve cost-effectiveness gains of crowdtesting, and a median of 100% bugs can be detected with 30% saved cost based on the automated close prediction. Expand
Using Learning Styles to Improve Software Requirements Quality: An Empirical Investigation
Using nanofiltration membranes for the recovery of phosphorous with a second type of technology for the Recovery of nitrogen is suggest to be a viable process. Expand
Using Eye Tracking to Investigate Reading Patterns and Learning Styles of Software Requirement Inspectors to Enhance Inspection Team Outcome
Analysis of reading trends of effective and efficient inspectors using eye movement and LS data of individual inspectors and virtual inspection teams shows inspectors who detect more faults during inspection, focus significantly more at the fault region to find and report faults as opposed to comprehending requirements information. Expand
Using Learning Styles to Staff and Improve Software Inspection Team Performance
The results showed that the inspection teams formed with inspectors of diverse LSs outperformed teams with similar LSs of inspectors, and can help software managers better staff inspectors, enabling cost savings, and improving quality. Expand