Grant: Collaborative Research and Development Grants
Ryerson University
$52,000.00
Test case prioritization
FY 2017-18
Summary
This proposal is a collaborative effort between IBM CAS Canada and the Data Science Laboratory at Ryerson University to build a software tool-aided test case prioritization model. Software analytics guide practitioners in decision making throughout the software development process. In this context, prediction models can help managers efficiently organize their resources and identify problems by analyzing patterns on existing project data in an intelligent and meaningful manner. It is necessary to have all-in-one tools that manage data collection, analysis, and calibration as well as communicate with existing systems in software organizations to provide valuable information. Over the years we have developed such a tool, called Dione. Dione is a software delivery intelligence and predictive analytics tool for a software delivery platform. It has an intelligent decision optimization engine (mining, filtering, prediction). It integrates data extraction, reporting, and prediction modules for a complete decision support cycle and offers a minimum configuration solution in a platform agnostic manner. In this project we aim to deploy Dione to IBM Rational Team Concert (RTC) to address practical challenges regarding Test Case prioritization. Test case prioritization techniques schedule test cases for execution in an order that attempts to increase their effectiveness in meeting some performance goal. Various goals are possible; one involves rate of fault detection - a measure of how quickly faults are detected within the testing process. An improved rate of fault detection during testing can provide faster feedback on the system under test, and let software engineers begin correcting faults earlier than might otherwise be possible. In the case of successful application of the proposed solution, it will not only impact the product quality of RTC but also be a best practice for the users of it. In other words, this will trigger cascaded benefits for a particular software industry in Canada.
Program
Collaborative Research and Development Grants
Recipient
Location
Ontario, Canada
Recipient Type
Academia
Type
Grant
Source
NSERC's Awards Data
As published
Application id
499518-2016
Name nom
Bener, Ayse
Department département
Mechanical and Industrial Engineering
Organization id
43
Institution établissement
Ryerson University
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2017
Competition year année de concours
2016
Award amount
52000
Program id
CRDPJ
Program name en
Collaborative Research and Development Grants
Program name fr
Subventions de recherche et développement coopérative
Group en
Research partnerships programs
Group fr
Programmes de partenariat
Committee code
96
Committee name en
RPP Internal Decision Cttee
Committee name fr
Cté de décision interne - PPR
Area of application code
802
Area of application group en
Information and communication services
Area of application group fr
Services d'information et de télécommunications
Area of application en
Information systems and technology
Area of application fr
Systèmes d'information et technologie de l'information
Research subject code
2700
Research subject group en
Information technology
Research subject group fr
Technologie de l'information
Research subject en
Information technology
Research subject fr
Technologie de l'information
Partie
2
Nb partie
3
Application title
Test case prioritization
Keyword
NSERC
Application summary
This proposal is a collaborative effort between IBM CAS Canada and the Data Science Laboratory at Ryerson University to build a software tool-aided test case prioritization model. Software analytics guide practitioners in decision making throughout the software development process. In this context, prediction models can help managers efficiently organize their resources and identify problems by analyzing patterns on existing project data in an intelligent and meaningful manner. It is necessary to have all-in-one tools that manage data collection, analysis, and calibration as well as communicate with existing systems in software organizations to provide valuable information. Over the years we have developed such a tool, called Dione. Dione is a software delivery intelligence and predictive analytics tool for a software delivery platform. It has an intelligent decision optimization engine (mining, filtering, prediction). It integrates data extraction, reporting, and prediction modules for a complete decision support cycle and offers a minimum configuration solution in a platform agnostic manner. In this project we aim to deploy Dione to IBM Rational Team Concert (RTC) to address practical challenges regarding Test Case prioritization. Test case prioritization techniques schedule test cases for execution in an order that attempts to increase their effectiveness in meeting some performance goal. Various goals are possible; one involves rate of fault detection - a measure of how quickly faults are detected within the testing process. An improved rate of fault detection during testing can provide faster feedback on the system under test, and let software engineers begin correcting faults earlier than might otherwise be possible. In the case of successful application of the proposed solution, it will not only impact the product quality of RTC but also be a best practice for the users of it. In other words, this will trigger cascaded benefits for a particular software industry in Canada.
