Two or more parties entering into a contract for service or goods may make use of an escrow of the funds for payment to enable trust in the contract. In such an event the documents or financial instruments, the object(s) in escrow, are held in trust by a trusted third party (escrow provider) until the specified conditions are fulfilled. In the scenario of software escrow, the object of escrow is typically the source code, and the specified release conditions usually address potential scenarios wherein the software provider becomes unable to continue providing services (such as due to bankruptcy or a change in services provided, etc.) The subject of software escrow is not well documented in the academic body of work, with the largest information sources, active commentary and supporting papers provided by commercial software escrow providers, both in South Africa and abroad. This work maps the software escrow topic onto the King III compliance framework in South Africa. This is of value since any users of bespoke developed applications may require extended professional assistance to align with the King III guidelines. The supporting risk assessment model developed in this work will serve as a tool to evaluate and motivate for software escrow agreements. It will also provide an overview of the various escrow agreement types and will transfer the focus to the value proposition that they each hold. Initial research has indicated that current awareness of software escrow in industry is still very low. This was evidenced by the significant number of approached specialists that declined to participate in the survey due to their own admitted inexperience in applying the discipline of software escrow within their companies. Moreover, the participants that contributed to the research indicated that they only required software escrow for medium to highly critical applications. This proved the value of assessing the various risk factors that bespoke software development introduces, as well as the risk mitigation options available, through tools such as escrow, to reduce the actual and residual risk to a manageable level.

A dissertation submitted to the Faculty of Science, University of the Witwatersrand, Johannesburg in fulfillment of the requirements for the degree of Master of Science. May 2017 / Plagiarism is a serious problem in academia. It is prevalent in the computing discipline where students are expected to submit source code assignments as part of their assessment; hence, there is every likelihood of copying. Ideally, students can collaborate with each other to perform a programming task, but it is expected that each student submit his/her own solution for the programming task. More so, one might conclude that the interaction would make them learn programming. Unfortunately, that may not always be the case. In undergraduate courses, especially in the computer sciences, if a given class is large, it would be unfeasible for an instructor to manually check each and every assignment for probable plagiarism. Even if the class size were smaller, it is still impractical to inspect every assignment for likely plagiarism because some potentially plagiarised content could still be missed by humans. Therefore, automatically checking the source code programs for likely plagiarism is essential. There have been many proposed methods that attempt to detect source code plagiarism in undergraduate source code assignments but, an ideal system should be able to differentiate actual cases of plagiarism from coincidental similarities that usually occur in source code plagiarism. Some of the existing source code plagiarism detection systems are either not scalable, or performed better when programs are modified with a number of insertions and deletions to obfuscate plagiarism. To address this issue, a graph-based model which considers structural similarities of programs is introduced to address cases of plagiarism in programming assignments. This research study proposes an approach to measuring cases of similarities in programming assignments using an existing plagiarism detection system to find similarities in programs, and a graph-based model to annotate the programs. We describe experiments with data sets of undergraduate Java programs to inspect the programs for plagiarism and evaluate the graph-model with good precision. An evaluation of the graph-based model reveals a high rate of plagiarism in the programs and resilience to many obfuscation techniques, while false detection (coincident similarity) rarely occurred. If this detection method is adopted into use, it will aid an instructor to carry out the detection process conscientiously. / MT 2017

Thesis (Ph.D.)--University of Delaware, 2008. / Principal faculty advisors: Lori L. Pollock and Lisa Marvel, Dept. of Computer & Information Sciences. Includes bibliographical references.

Thesis (Masters) -- California Institute of Technology, 2010. / Title from home page (viewed 04/19/10). Advisor names found in the thesis' metadata record in the digital repository. Includes bibliographical references.

Thesis (Ph.D.)--University of Delaware, 2006. / Principal faculty advisor: Javier Garcia-Frias, Dept. of Electrical and Computer Engineering. Includes bibliographical references.

Thesis (Ph.D.)--University of Delaware, 2006. / Principal faculty advisor: Javier Garcia-Frias, Dept. of Electrical and Computer Engineering. Includes bibliographical references.

Thesis (Ph. D.)--Lehigh University, 2004. / Includes vita. Includes bibliographical references (leaves 235-240).

Thesis (Ph.D.)--Drexel University, 2008. / Includes abstract and vita. Includes bibliographical references (leaves 115-117).

Thesis (M.E.E.)--University of Delaware, 2008. / Principal faculty advisor: Javier Garcia-Frias, Dept. of Electrical and Computer Engineering. Includes bibliographical references.

Thesis (M.Sc.). / Written for the School of Computer Science. Title from title page of PDF (viewed 2009/06/18). Includes bibliographical references.