skip to main content
10.1145/2491411.2494574acmconferencesArticle/Chapter ViewAbstractPublication PagesfseConference Proceedingsconference-collections
research-article

The economics of static analysis tools

Published:18 August 2013Publication History

ABSTRACT

Static analysis tools have experienced a dichotomy over the span of the last decade. They have proven themselves to be useful in many domains, but at the same time have not (in general) experienced any notable concrete integration into a development environment. This is partly due to the inherent complexity of the tools themselves, as well as due to other intangible factors. Such factors usually tend to include questions about the return on investment of the tool and the value the tool provides in a development environment. In this paper, we present an empirical model for evaluating static analysis tools from the perspective of the economic value they provide. We further apply this model to a case study of the Static Driver Verier (SDV) tool that ships with the Windows Driver Kit and show the usefulness of the model and the tool.

References

  1. T. Ball, B. Cook, V. Levin, and S. K. Rajamani. Slam and static driver verifier: Technology transfer of formal methods inside microsoft. In Integrated formal methods, pages 1–20. Springer, 2004.Google ScholarGoogle Scholar
  2. P. J. Guo, T. Zimmermann, N. Nagappan, and B. Murphy. Characterizing and predicting which bugs get fixed: An empirical study of microsoft windows. In Software Engineering, 2010 ACM/IEEE 32nd International Conference on, volume 1, pages 495–504. IEEE, 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. P. J. Guo, T. Zimmermann, N. Nagappan, and B. Murphy. Not my bug! and other reasons for software bug report reassignments. In Proceedings of the ACM 2011 conference on Computer supported cooperative work, pages 395–404. ACM, 2011. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. G. J. Holzmann. Economics of software verification. In Proceedings of the 2001 ACM SIGPLAN-SIGSOFT workshop on Program analysis for software tools and engineering, pages 80–89. ACM, 2001. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. S. T. Knox. Modeling the cost of software quality. Digital Technical Journal, 5:9–9, 1993. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. M. Lata and R. Kumar. An approach to optimize the cost of software quality assurance analysis. International Journal of Computer Applications, 5(8), 2010.Google ScholarGoogle ScholarCross RefCross Ref
  7. MSDN. Code analysis for drivers. http://msdn.microsoft.com/en-us/library/ windows/hardware/hh454182(v=vs.85).aspx, 2012.Google ScholarGoogle Scholar
  8. MSDN. Driver verifier. http://msdn.microsoft.com/en-us/library/ windows/hardware/ff545448(v=vs.85).aspx, 2012.Google ScholarGoogle Scholar
  9. S. Sinofsky. Building robust USB 3.0 support. http://blogs.msdn.com/b/b8/archive/2011/08/22/ building-robust-usb-3-0-support.aspx, 2011.Google ScholarGoogle Scholar
  10. S. Wagner and T. Seifert. Software quality economics for defect-detection techniques using failure prediction. In ACM SIGSOFT Software Engineering Notes, volume 30, pages 1–6. ACM, 2005. Google ScholarGoogle ScholarDigital LibraryDigital Library

Index Terms

  1. The economics of static analysis tools

              Recommendations

              Comments

              Login options

              Check if you have access through your login credentials or your institution to get full access on this article.

              Sign in
              • Published in

                cover image ACM Conferences
                ESEC/FSE 2013: Proceedings of the 2013 9th Joint Meeting on Foundations of Software Engineering
                August 2013
                738 pages
                ISBN:9781450322379
                DOI:10.1145/2491411

                Copyright © 2013 ACM

                Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

                Publisher

                Association for Computing Machinery

                New York, NY, United States

                Publication History

                • Published: 18 August 2013

                Permissions

                Request permissions about this article.

                Request Permissions

                Check for updates

                Qualifiers

                • research-article

                Acceptance Rates

                Overall Acceptance Rate112of543submissions,21%

              PDF Format

              View or Download as a PDF file.

              PDF

              eReader

              View online with eReader.

              eReader