Static program analysis
Static program analysis is the analysis of computer software that is performed without actually executing programs (analysis performed on executing programs is known as dynamic analysis). In most cases the analysis is performed on some version of the source code, and in the other cases, some form of the object code. The term is usually applied to the analysis performed by an automated tool, with human analysis being called program understanding, program comprehension or code review.
The sophistication of the analysis performed by tools varies from those that only consider the behavior of individual statements and declarations, to those that include the complete source code of a program in their analysis. The uses of the information obtained from the analysis vary from highlighting possible coding errors (e.g., the lint tool) to formal methods that mathematically prove properties about a given program (e.g., its behavior matches that of its specification).
Software metrics and reverse engineering can be described as forms of static analysis. Deriving software metrics and static analysis are increasingly deployed together, especially in creation of embedded systems, by defining so-called software quality objectives.
A growing commercial use of static analysis is in the verification of properties of software used in safety-critical computer systems and locating potentially vulnerable code. For example the following industries have identified the use of static code analysis as a means of improving the quality of increasingly sophisticated and complex software:
- Medical software: The U.S. Food and Drug Administration (FDA) has identified the use of static analysis for medical devices.
- Nuclear software: In the UK the Health and Safety Executive recommends the use of static analysis on Reactor Protection Systems.
- Aviation software (in combination with dynamic analysis)
A study in 2012 by VDC Research reports that 28.7% of the embedded software engineers surveyed currently use static analysis tools and 39.7% expect to use them within 2 years.
In application security industry the name Static Application Security Testing (SAST) is also used.
The OMG (Object Management Group) recently published a study regarding the types of software analysis required for software quality measurement and assessment. This document on "How to Deliver Resilient, Secure, Efficient, and Easily Changed IT Systems in Line with CISQ Recommendations" describes three levels of software analysis.
Unit Level - Analysis that takes place within a specific program or subroutine, without connecting to the context of that program.
Technology Level - Analysis that takes into account interactions between unit programs to get a more holistic and semantic view of the overall program in order to find issues and avoid obvious false positives.
System Level - Analysis that takes into account the interactions between unit programs, but without being limited to one specific technology or programming language.
Mission/Business Level - Analysis that takes into account the business/mission layer terms, rules and processes that are implemented within the software system for its operation as part of enterprise or program/mission layer activities. These elements are implemented without being limited to one specific technology or programming language and in many cases are distributed across multiple languages but are statically extracted and analyzed for system understanding for mission assurance.
Formal methods is the term applied to the analysis of software (and computer hardware) whose results are obtained purely through the use of rigorous mathematical methods. The mathematical techniques used include denotational semantics, axiomatic semantics, operational semantics, and abstract interpretation.
By a straightforward reduction to the halting problem, it is possible to prove that (for any Turing complete language), finding all possible run-time errors in an arbitrary program (or more generally any kind of violation of a specification on the final result of a program) is undecidable: there is no mechanical method that can always answer truthfully whether an arbitrary program may or may not exhibit runtime errors. This result dates from the works of Church, Gödel and Turing in the 1930s (see: Halting problem and Rice's theorem). As with many undecidable questions, one can still attempt to give useful approximate solutions.
Some of the implementation techniques of formal static analysis include:
- Model checking, considers systems that have finite state or may be reduced to finite state by abstraction;
- Data-flow analysis, a lattice-based technique for gathering information about the possible set of values;
- Abstract interpretation, to model the effect that every statement has on the state of an abstract machine (i.e., it 'executes' the software based on the mathematical properties of each statement and declaration). This abstract machine over-approximates the behaviours of the system: the abstract system is thus made simpler to analyze, at the expense of incompleteness (not every property true of the original system is true of the abstract system). If properly done, though, abstract interpretation is sound (every property true of the abstract system can be mapped to a true property of the original system). The Frama-c value analysis plugin and Polyspace heavily rely on abstract interpretation.
- Use of assertions in program code as first suggested by Hoare logic. There is tool support for some programming languages (e.g., the SPARK programming language (a subset of Ada) and the Java Modeling Language — JML — using ESC/Java and ESC/Java2, Frama-c WP (weakest precondition) plugin for the C language extended with ACSL (ANSI/ISO C Specification Language) ).
- Symbolic execution, as used to derive mathematical expressions representing the value of mutated variables at particular points in the code.
- KPI driven code analysis, a method of analyzing software source code and source-code-related IT systems to gain insight into business-critical aspects of the development of a software system, such as team-performance, time-to-market, risk-management, failure-prediction, and others.
- Wichmann, B. A.; Canning, A. A.; Clutterbuck, D. L.; Winsbarrow, L. A.; Ward, N. J.; Marsh, D. W. R. (Mar 1995). "Industrial Perspective on Static Analysis.". Software Engineering Journal: 69–75. Archived from the original on 2011-09-27.
- "Software Quality Objectives for Source Code" (PDF). Proceedings: Embedded Real Time Software and Systems 2010 Conference, ERTS2010.org, Toulouse, France: Patrick Briand, Martin Brochet, Thierry Cambois, Emmanuel Coutenceau, Olivier Guetta, Daniel Mainberte, Frederic Mondot, Patrick Munier, Loic Noury, Philippe Spozio, Frederic Retailleau.
- Improving Software Security with Precise Static and Runtime Analysis (PDF), Benjamin Livshits, section 7.3 "Static Techniques for Security". Stanford doctoral thesis, 2006.
- FDA (2010-09-08). "Infusion Pump Software Safety Research at FDA". Food and Drug Administration. Retrieved 2010-09-09.
- Computer based safety systems - technical guidance for assessing software aspects of digital computer based protection systems, http://www.hse.gov.uk/nuclear/operational/tech_asst_guides/tast046.pdf
- Position Paper CAST-9. Considerations for Evaluating Safety Engineering Approaches to Software Assurance // FAA, Certification Authorities Software Team (CAST), January, 2002: "Verification. A combination of both static and dynamic analyses should be specified by the applicant/developer and applied to the software."
- VDC Research (2012-02-01). "Automated Defect Prevention for Embedded Software Quality". VDC Research. Retrieved 2012-04-10.
- Jones, Paul (2010-02-09). "A Formal Methods-based verification approach to medical device software analysis". Embedded Systems Design. Retrieved 2010-09-09.
- Syllabus and readings for Alex Aiken’s Stanford CS295 course.
- Nathaniel Ayewah, David Hovemeyer, J. David Morgenthaler, John Penix, William Pugh, "Using Static Analysis to Find Bugs," IEEE Software, vol. 25, no. 5, pp. 22–29, Sep./Oct. 2008, doi:10.1109/MS.2008.130
- Brian Chess, Jacob West (Fortify Software) (2007). Secure Programming with Static Analysis. Addison-Wesley. ISBN 978-0-321-42477-8.
- Flemming Nielson, Hanne R. Nielson, Chris Hankin (1999, corrected 2004). Principles of Program Analysis. Springer. ISBN 978-3-540-65410-0.
- "Abstract interpretation and static analysis," International Winter School on Semantics and Applications 2003, by David A. Schmidt
- Code Quality Improvement - Coding standards conformance checking (DDJ)
- Competition on Software Verification (SV-COMP)
- Episode 59: Static Code Analysis Interview (Podcast) at Software Engineering Radio
- Implementing Automated Governance for Coding Standards Explains why and how to integrate static code analysis into the build process
- Integrate static analysis into a software development process
- .NET Static Analysis (InfoQ)
- Static Code Analysis - Polyspace
- The SAMATE Project, a resource for Automated Static Analysis tools