Please use this identifier to cite or link to this item:
Title: Specification mining: Methodologies, theories and applications
Authors: DAVID LO
Keywords: Software Engineering, Data Mining, Software Maintenance, Program Comprehension, Software Reliability, Pattern Mining
Issue Date: 9-Oct-2008
Citation: DAVID LO (2008-10-09). Specification mining: Methodologies, theories and applications. ScholarBank@NUS Repository.
Abstract: In this dissertation, we describe theories, methodologies and applications of mining expressive software specifications from program execution traces. By observing program execution traces, specifications in the formats of automata, frequent behavioral patterns, temporal rules expressed in Linear Temporal Logic (LTL) and Live Sequence Chart (LSC) can be mined. Our goal is to improve automation, accuracy and efficiency of mining processes. We build the work from the ground up by first describing evaluation measures, followed by properties and theorems, methodologies and finally applications of mined specifications. Mined specifications are useful to aid program understanding, reduce the cost of software maintenance and provide the set of formal specifications for program verification tools. This work builds on the synergy of concepts and techniques from several domains of computer science including software engineering, programming languages, data mining, and machine learning.
Appears in Collections:Ph.D Theses (Open)

Show full item record
Files in This Item:
File Description SizeFormatAccess SettingsVersion 
LoD.pdf1.37 MBAdobe PDF



Page view(s)

checked on Nov 25, 2018


checked on Nov 25, 2018

Google ScholarTM


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.