This dataset is the result of test case and developer metrics extraction from Honfi's experiment in https://zenodo.org/record/2596044#.Xnm4sS2B1QJ

The detail of test case extraction is attached.

It contained 20 metrics from the generated test case and six metrics from the profile of developers. 26 metrics act as independent variable. There are two dependent variables : ABU (Actual Binary Understandability) and TAU (Timed Actual Understandability).

  • Other
  • Last Updated On: 
    Tue, 03/24/2020 - 03:56

    The dataset is system activities captured by Procmon on Windows, including running malware WannaPeace.

  • Standards Research Data
  • Last Updated On: 
    Tue, 03/17/2020 - 02:52

    CUPSNBOTTLES is an object data set, recorded by a mobile service robot. There are 10 object classes, each with a varying number of samples. Additionally, there is a clutter class, containing samples where the object detector failed.

  • Computer Vision
  • Last Updated On: 
    Fri, 02/28/2020 - 11:47


    This dataset was created for research on blockchain anomaly and fraud detection. And donated to IEEE data port online community. 





  • Artificial Intelligence
  • Last Updated On: 
    Sun, 11/24/2019 - 08:27

    We provide a large benchmark dataset consisting of about: 3.5 million keystroke events; 57.1 million data-points for accelerometer and gyroscope each; and 1.7 million data-points for swipes. Data was collected between April 2017 and June 2017 after the required IRB approval. Data from 117 participants, in a session lasting between 2 to 2.5 hours each, performing multiple activities such as: typing (free and fixed text), gait (walking, upstairs and downstairs) and swiping activities while using desktop, phone and tablet is shared. 


  • Artificial Intelligence
  • Last Updated On: 
    Thu, 03/05/2020 - 00:59

    Dockerfile plays an important role in the Docker-based containerization process, but many Dockerfile codes are infected with smells in practice. This dataset contains a collection of 6,334 projects to help developers gain some insights into the occurrence of Dockerfile smells. Those projects belong to 10 popular programming languages, i.e., Shell, Makefile, Ruby, PHP, Python, Java, HTML, CSS, JavaScript, and Go. 

  • Standards Research Data
  • Last Updated On: 
    Sat, 11/16/2019 - 11:43

    This work focuses on using the full potential of PV inverters in order to improve the efficiency of low voltage networks. More specifically, the  independent per-phase control capability of PV three-phase four-wire inverters, which are able to inject different active and reactive powers in each phase, in order to reduce the system phase unbalance is considered.  This new operational procedure is analyzed by raising an optimization problem which uses a very accurate modelling of European low voltage networks.

  • Power and Energy
  • Last Updated On: 
    Thu, 11/14/2019 - 12:26

    ASNM datasets include records consisting of many features, that express various properties and characteristics of TCP communications. These features are called Advanced Security Network Metrics (ASNM) and were designed with the intention to discern legitimate and malicious connections (especially intrusions).

  • Machine Learning
  • Last Updated On: 
    Sun, 11/03/2019 - 01:04

    This study was conducted in Mayaguez – Puerto Rico, and an area of around 18 Km2 was covered, which were determined using the following classification of places:

    ·         Main Avenues: Wide public ways that has hospitals, vegetation, buildings, on either side

    ·         Open Places: Mall parking lots and public plazas

    ·         Streets & Roads: Dense residential and commercial areas on both sides

         Vendor             Equipment                  Description      

    KEYSIGHT®      N9343C                    Handheld Spectrum Analyzer

  • IoT
  • Last Updated On: 
    Sun, 10/27/2019 - 21:54

    7200 .csv files, each containing a 10 kHz recording of a 1 ms lasting 100 hz sound, recorded centimeterwise in a 20 cm x 60 cm locating range on a table. 3600 files (3 at each of the 1200 different positions) are without an obstacle between the loudspeaker and the microphone, 3600 RIR recordings are affected by the changes of the object (a book). The OOLA is initially trained offline in batch mode by the first instance of the RIR recordings without the book. Then it learns online in an incremental mode how the RIR changes by the book.

  • Artificial Intelligence
  • Last Updated On: 
    Mon, 11/04/2019 - 07:37