Techniques for off-device anti-malware protection for mobile devices are disclosed. In some embodiments, off-device anti-malware protection for mobile devices includes receiving a software inventory for a mobile device, in which the software inventory identifies a plurality of applications installed on the mobile device; and determining whether one or more of the plurality of applications identified in the software inventory are associated with malware based on a policy. In some embodiments, the off-device anti-malware protection for mobile devices further includes enforcing the policy on the mobile device. In some embodiments, the off-device anti-malware protection for mobile devices is provided as a cloud service.

Off-device anti-malware protection for mobile devices

Quantifying the risks of applications (“apps”) for mobile devices is disclosed. In some embodiments, quantifying the risks of apps for mobile devices includes receiving an application for a mobile device; performing an automated analysis of the application based on a risk profile; and generating a risk score based on the automated analysis of the application based on the risk profile.

Quantifying the risks of applications for mobile devices

Techniques for in-line filtering of insecure or unwanted mobile components or communications (e.g., insecure or unwanted behaviors associated with applications for mobile devices (“apps”), updates for apps, communications to/from apps, operating system components/updates for mobile devices, etc.) for mobile devices are disclosed. In some embodiments, in-line filtering of apps for mobile devices includes intercepting a request for downloading an application to a mobile device; and modifying a response to the request for downloading the application to the mobile device. In some embodiments, the response includes a notification that the application cannot be downloaded due to an application risk policy violation.

In-line filtering of insecure or unwanted mobile device software components or communications

A system and method for improved testing of a software build is provided. The system and method automatically track differences between software builds by scanning the binaries of a software product to automatically discover its classes. The system and method then build a detailed dictionary that captures static and dynamic information of that build, including class dependencies. A comparison may be made with another build, so that the present invention may automatically execute selective tests on any types, and their dependencies, that have had a structural or behavioral modification since the last build. Testers may load a set of constructors for any specific types to further increase coverage of types (or classes) tested. The present invention may also provide detailed reports that may be used to drive future testing work and target specific areas of the code for additional testing. The system and method may further provide code generation from intermediate code to specified targets to aid in reproducing and fixing bugs.

Method and system for automatically testing a software build

Methods and systems for facilitating incremental software development are disclosed. For example, a method can include receiving a plurality of binary software libraries sufficient for building a software project. A request from a user to modify source code for at least one of the plurality of binary libraries is received. In response to receiving the request, the source code for the at least one of the plurality of binary libraries is retrieved. The source code for the at least one of the plurality of binary libraries is presented to the user. Modified source code for the at least one of the plurality of binary libraries is received. The modified source code is compiled to produce compiled modified code. A revised version of the software project is built using the compiled modified code and the plurality of binary libraries.

Systems and methods for incremental software development

A method for determining changed code in a second program binary relative to a first or baseline program binary, where the second program is a different version of the first program, includes translating, responsive to symbol tables and/or control flow representations, machine addresses of both program binaries to symbols. The first and second program binaries are disassembled using the translated symbols. Differences between the two resulting disassemblies are determined, and a list of the differences is created. Differences between the program binaries can be determined by textually comparing the disassemblies, or alternatively, by determining the differences between the control flow representations of the programs. The list of differences can be presented to a user, or alternatively, can be passed to another process for further processing, such as test coverage analysis, code change analysis, or failure analysis, among other analyses.

Method for determining the degree to which changed code has been exercised

A method for determining changed code in a second program binary relative to a first or baseline program binary, where the second program is a different version of the first program, includes translating, responsive to symbol tables and/or control flow representations, machine addresses of both program binaries to symbols. The first and second program binaries are disassembled using the translated symbols. Differences between the two resulting disassemblies are determined, and a list of the differences is created. Differences between the program binaries can be determined by textually comparing the disassemblies, or alternatively, by determining the differences between the control flow representations of the programs. The list of differences can be presented to a user, or alternatively, can be passed to another process for further processing, such as test coverage analysis, code change analysis, or failure analysis, among other analyses. Analyzing changed code coverage includes marking code in the second program which is changed or different from the first program. The second program is then executed in a test environment, and code which is executed is marked as having been executed. Next, the second program is executed in a non-test environment, such as a production environment, and code which is executed in this second environment is marked accordingly. Finally, from the variously, marked code, a list of changed code which have not executed in the test environment but have executed in the non-test environment is provided.

Method for determining the degree to which code has been changed

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Method for determining the degree to which changed code has been exercised

Method for determining the degree to which code has been changed