Justification and Considerations in Profiling Automated Testing in Software Maintenance Organizations for E Type Systems

Document Type

Thesis Proposal


Dr. Paul Jorgensen, jorgensp@gvsu.edu

Embargo Period



Premise: Automated software testing is not a silver bullet to software engineering. [FEW99 p288, DUSTIN99 p32]. However, automated testing can provide significant gains in labor savings to an organization [DUSTIN99]. Given that 70 percent of most developers are assigned to work in maintenance roles [MCNU02 p.317], it would appear that the maintenance environment with limited or no automated testing would be an area to derive the greatest benefit. Robert Poston warns, though, that in a maintenance environment tools should be introduced only as changes are required [1996 p.210]. This paper does not disagree with Poston's contention. However, in the case of E-type systems, which continually experience change [LEHMAN00], it does advocate that maintenance organizations should evaluate its posture for automated testing, particularly where complex interoperability of systems exists. In addition to discussing the justification, it proposes the use of a visual modeling tool that represents a high level profile of an organization's need and its ability to support automated testing.

Scope: The scope of this paper is to discuss guidelines on establishing an organization's automated testing profile and how the profile supports a decision on whether to implement automated testing tools. Often, individual developers will generate applications to drive their specific development units, which are referred to as harnesses [POST96], but to be effective, automated testing must rise above this level and be viewed as a strategic asset [FEWS99]. In support of that, this paper's goal is to establish a strategic view, particularly in organizations with multiple systems that interact, which "are the bane of testers." [JORG02] While it takes into consideration the technical aspects of testing, its focus is on the economic value produced by automated test tools to address what Boehm describes as the lack of "adequate frameworks for modeling, measuring and analyzing the connections between technical properties, decisions and value creation." [BOEHM00 p. 2] Further, it will present an evaluation and prediction model based on concepts in the management information sciences. The scope of this paper does not include a discussion on design issues of automated test tools.

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