Patent Description:
A critical aspect of computer software development is quality assurance. For a given software project different types of testing may be appropriate, and different tools are available to assist in the testing process.

Code coverage (or test coverage) tools are one type of tool available to assist with software testing. Generally speaking, a code coverage tool is used to determine what parts of source code are covered by a given test suite and what (if any) parts of source code are not.

Complex software products can involve hundreds of thousands (or even millions) of lines of code spread across tens or hundreds of thousands of source code files. For such software products, the result set of a code coverage analysis can be large and require significant storage resources to store for review by relevant stakeholders.

This storage issue is further exacerbated in cases where code coverage analysis is repetitively performed as a source code base changes over time - e.g. each time revised source code is committed to the base in order to fix an issue or provide a new feature. In cases such as this each code coverage analysis performed generates a new set of code coverage results that need to be stored.

The approaches described in this section are approaches that are known to the inventors and could be pursued. They are not necessarily approaches that have been pursued. Therefore, unless otherwise indicated, it should not be assumed that any of the approaches described in this section qualify as prior art merely by virtue of their inclusion in this section, or that those approaches are known to a person of ordinary skill in the art.

Document <CIT> discloses a system for generating delta code coverage information by processing code coverage information corresponding to software program code files, comprising a source control module storing multiple software program code files to be processed.

Document <CIT> discloses a method for detecting that new source code associated with a defect identifier has been checked in to a source code repository, including transmitting a notification indicating a test case deficiency for a code branch.

Document <CIT> discloses a method for providing automatic test generation for model-based code coverage, involving obtaining a representation of a system and obtaining a set of test obligations associated with a coverage criterion for testing the representation.

The document <NPL> discloses the basics of the git distributed version control system.

The appended claims may serve as a summary of the invention.

In other instances, well-known structures and devices are shown in block diagram form in order to avoid unnecessary obscuring.

As described above, code coverage tools are one type of tool available to assist with software testing. Generally speaking, a code coverage tool operates to measure or determine 'parts' of a source code base that are covered by a particular test suite (i.e. one or more tests that are performed on a software program). As used herein, a source code base is a set of one or more source code files (each source code file comprising one or more lines of source code) that are compiled together to provide a software product. A source code base may have different versions, reflecting changes made to the source code base over time. A test suite is a set of one or more tests that are run against the source code product to test its operation.

Different code coverage tools may analyze and report on different source code 'parts'. For example, source code 'parts' could be source code functions or subroutines, source code statements, source code branches, source code conditions, or source code lines. Accordingly, coverage information refers to information that indicates source code parts (whether lines, functions, routines, or other parts) that were covered by a test suite. Similarly, partial coverage information refers to information that indicates source code parts that were partially covered by a test suite.

Code coverage results from a given code coverage analysis can be relatively large. This is undesirable from a storage perspective, and can become a particular issue for software products with large code bases which are changed and analyzed frequently.

Consider, for example, a software product with a large source code base that is in ongoing development (e.g. for feature addition and/or bug-fixing). The code base may, for example, comprise hundreds (if not thousands) of source code files which collectively contain hundreds of thousands (if not millions) of lines of code. The code base and/or test suite for the product may be updated multiple times a day, and with each update a code coverage analysis performed to determine whether the existing test suite used to test the software product is still useful or needs to be changed. If every code coverage analysis generates a result set of, for example, <NUM>-10mb of raw data, and over the course of a day around <NUM> analyses are run, the disk space required to store the coverage results quickly becomes very large.

The inventors have identified that for some projects code coverage results from successive code coverage analyses include a large amount of data duplication. For such projects, therefore, the inventors have identified that it may be possible to reduce the storage required to store code coverage results if the data can be de-duplicated. The inventors have further identified efficient de-duplication and storage of code coverage results can be performed by leveraging functionality provided by version control systems.

The embodiments described herein provide a direct improvement to computer systems and computer technology. By reducing the quantity of digital data stored for code coverage results, the amount of memory, network bandwidth, processing time, and power usage may be reduced. Further, the embodiments described herein offer an improvement in the overall efficiency of a computing system, resulting in a faster, more responsive computer system. Additionally, the embodiments described herein describe a technical solution to a technical problem that is rooted in computer systems and the use of networked computers. Further still, by using the embodiments described herein, the reduction in memory used results in a minimal, if any, impact to the usability of the code coverage results. These advantages and others described throughout this specification are clear improvements over existing systems that are unable to provide these improvements or advantages.

The embodiments described herein are implemented using one or more computer systems. An example computer processing system will be described with reference to <FIG>, followed by an overview of the high-level functional systems involved in the disclosed embodiments. Example processes for generating code coverage test results, processing those results and storing them, and then retrieving stored code coverage results will then be described to illustrate particular embodiments and various features thereof.

Embodiments and features described herein are implemented by one or more special-purpose computing devices. The special-purpose computing devices may be hard-wired to perform the techniques described, or may include digital electronic devices such as one or more application-specific integrated circuits (ASICs) or field programmable gate arrays (FPGAs) that are persistently programmed to perform the techniques, or may include one or more general purpose hardware processors programmed to perform the techniques pursuant to program instructions in firmware, memory, other storage, or a combination. The special-purpose computing devices may be desktop computer systems, portable computer systems, handheld devices, networking devices, server systems, or any other device/system that incorporates hard-wired and/or program logic to implement the techniques.

For example, each of the client system <NUM>, test system <NUM>, and version control system <NUM> described below may be a separate computer system <NUM>.

Hardware processor <NUM> may be, for example, a general purpose microprocessor (e.g. a CPU) or a special purpose processor (e.g. a graphical processing unit or GPU).

Main memory <NUM> also may be used for storing temporary variables or other intermediate information during execution of instructions by the processor <NUM>.

A storage device <NUM>, such as a magnetic disk, solid state disk, or optical disk, is provided and coupled to bus <NUM> for storing information and instructions.

Computer system <NUM> may be coupled, via bus <NUM>, to one more output devices such as a display <NUM> for displaying information to a computer user. Display <NUM> may, for example, be a cathode ray tube (CRT), a liquid crystal display (LCD), a light emitting diode (LED display), or a touch screen display. An input device <NUM>, including alphanumeric and other keys, may be coupled to bus <NUM> for communicating information and command selections to processor <NUM>. Additional and/or alternative input devices are possible, for example touch screen displays.

In certain embodiments, the techniques herein are performed by computer system <NUM> in response to processor <NUM> executing one or more sequences of one or more instructions contained in main memory <NUM>.

For example, communication interface <NUM> may be an integrated services digital network (ISDN) card, cable modem, satellite modem, or a modem to provide a data communication connection to a corresponding type of communications or telephone line.

A computer system as described herein may be configured in a plurality of useful arrangements. In one approach, a data processing method comprises using a computer system, obtaining from one or more non-transitory computer-readable data storage media a copy of one or more sequences of instructions that are stored on the media and which when executed by the computer system processor cause the computer system to perform (either alone or in combination with one or more additional computer systems), the techniques that are described herein.

A computer system may take a variety of forms. For example, a client computer <NUM> may be a desktop computer, a laptop computer, a notebook computer, a tablet computer, a smart phone, or other computer.

<FIG> is a diagram <NUM> illustrating various functional systems involved in embodiments described herein. At a high level, the systems comprise a client system <NUM>, a test system <NUM>, and a version control system <NUM>.

Client system <NUM> runs a client application <NUM> via which a user can interact with the test system <NUM> and version control system <NUM> to initiate code coverage analyses and access/retrieve code coverage results. Client system <NUM> will typically be a user computing device such as a desktop computer, a mobile phone, a tablet or the like.

Test system <NUM> provides server-side support for the client test application <NUM> and also performs code coverage analyses. To this end the test system <NUM> comprises a test module <NUM> for running a code coverage tool. As one example, the code coverage tool may be Cobertura, however alternative code coverage tools may be used (e.g. Clover, Emma, Istanbul, BlanketJs). Test system <NUM> also comprises a code coverage result processing module <NUM> for processing the code coverage results generated by the testing module <NUM>. Test system <NUM> may be a stand-alone computer system or a distributed system with multiple instances concurrently running on one or more physical computer systems (e.g. servers).

Version control system <NUM> comprises a version control application <NUM> and maintains a version control system data store <NUM> on which data repositories are stored. In certain embodiments, the repositories comprise one or more source code repositories <NUM> and one or more code coverage result repositories <NUM>. The embodiments herein will be described using Git as the version control application <NUM>, however alternative version control systems may be used (e.g. CVS, SVN, Mercurial, Perforce). As with the test system <NUM>, the version control system <NUM> may be a distributed system with multiple instances concurrently running on one or more physical computer systems (e.g. servers). In this case, data store <NUM> will generally be a dedicated database system running on its own computer processing system and accessible to all version control application instances. Version control system <NUM> may be provisioned in a public or private cloud or hosted as a 'normal' server system, and will typically be set up so as to enable concurrent access by multiple users (e.g. by via multiple client systems <NUM> and, in certain embodiments, the test system <NUM>).

In the illustrated example, client system <NUM>, test system <NUM>, and version control system <NUM> communicate with one another via a communications network <NUM>. This may be a public network (e.g. the Internet <NUM> shown in <FIG>) or a local area network (e.g. network <NUM> of <FIG>). In alternative embodiments, two or more of the client system <NUM>, test system <NUM>, and version control system <NUM> may communicate directly with one another rather than over a network.

As will be appreciated, <FIG> illustrates functional systems used in the present embodiments. These functional systems could be implemented using various hardware configurations and architectures. For example, while the client system <NUM> and test system <NUM> have been described as separate systems these may, the functions performed by the test system <NUM> may, in fact, be provided by the client system <NUM> (i.e. by installing appropriate software on the client system <NUM>).

This section describes various processes involved in generating and handling code coverage test results. The generation of raw code coverage test results will be described briefly with reference to <FIG>, the processing and storage of code coverage results will be described with reference to <FIG>, and the retrieval of code coverage results will be described with reference to <FIG>.

Turning to <FIG>, an example process <NUM> for performing a code coverage analysis (and generating test results) will be described.

At <NUM>, the test system <NUM> determines parameters for the code coverage analysis to be performed. The parameters define at least the source code base, a particular version of that source code base, and a particular test suite that the code coverage analysis is to be performed on. The parameters may be determined based on user input (received via a client system <NUM>) or may be default values. For example, source code bases may be associated default test suites. In this case, when a particular source code base is selected the default test suite for that source code base is automatically selected by default.

In the present embodiment, the source code base is maintained by a version control system <NUM> in a source code repository <NUM> and the specific version/revision of a source code base is identified by a commit identifier (or commit hash).

At <NUM>, the test system <NUM> retrieves the source code file(s) in respect of the particular source code base version identified at <NUM> (e.g. from the version control system <NUM>) and prepares those file(s).

At <NUM>, the test system <NUM> performs the code coverage analysis using a code coverage tool (e.g. Cobertura or an alternative code coverage tool). This generates raw code coverage analysis results.

At <NUM>, the test system <NUM> generates code coverage data for downstream use. The code coverage data comprises the raw code coverage analysis results as generated by the code coverage tool as well as code base identification information allowing the source code base (and particular version thereof) on which the analysis was performed to be identified. Once again, the code base identification information may be the relevant commit identifier. In some embodiments, for example where default test suites are used, there is no need to identify the particular test suite against which the code coverage analysis was performed. In embodiments where it is possible to use multiple test suites to test a given code base an additional parameter will be passed which can be used to associate the test suite with the results (e.g. by inclusion of the value in the resulting file name to make it uniquely identifiable).

In certain embodiments, generating the code coverage data for downstream use involves processing the raw code coverage data to generate a wireformat (or reduced version) of that data for efficient transmission. Generally speaking, this involves processing the raw code coverage analysis results to discard data that is not of interest for downstream processing/storage and retain data that is. For example, where the code coverage tool outputs. xml data the data can be parsed by identifying tags of interest in the. xml and extracting the information associated with those tags for inclusion in the wireformat.

By way of specific example, Table A below shows an extract of. xml output generated by the Cobertura code coverage tool:
<IMG>.

Presuming that the data of interest is which lines of which files were covered by the test suite, an example wireformat corresponding to this extract is shown in Table B:.

As can be see, the wireformat has been generated by identifying xml tags indicating the line numbers of particular source code files covered by the test suite and including that information in the wireformat. The remaining output from the code coverage tool is (for immediate purposes) disregarded, thereby reducing resources required to transmit and store this data. In alternative implementations additional (or different) data may be extracted from the raw code coverage results as desired. For example, the code coverage tool may report on partial coverage information (e.g. source code lines that are partially covered by the test suite) and this may be included in the wireformat. By way of further example, the code coverage tool may report on other aspects such as method complexity, hit count, and / other aspects which if desired can also be included in the wireformat.

At <NUM>, the test system <NUM> shares the code coverage data generated at <NUM>. The code coverage data may be shared in various ways, for example by communicating it to a client device <NUM>, sending the data to other users, devices or services, or publishing the data for other devices/users/servers to access, posting it to a version control system.

Once the results have been shared at <NUM> the code coverage analysis is complete.

The person skilled in the art will recognize that there are many code coverage tools and many systems/methods available for performing a code coverage analysis. While a high level example has been described with reference to <FIG> many alternatives are possible. Relevant factors in this regard are that a code coverage analysis is performed on an identifiable source code base and the results of that analysis are made available for downstream use.

Once code coverage analysis is complete, the code coverage test results are processed.

In the present embodiment the results are processed by the code coverage result processing module <NUM> running on the test system <NUM>. Processing of the code coverage results (i.e. performing the processing described in relation to <FIG> below) could, however, be performed by alternative systems. For example, the code coverage results could be passed back to a client system <NUM> and processed by an appropriate application/module running on the client system <NUM>.

At <NUM>, code coverage data is accessed or received. In the present embodiment, the code coverage data comprises the wireformat data as described above and at least a code base identifier (identifying the source code base and version which the code coverage tool analyzed). In alternative embodiments, the raw code coverage results (generated by the code coverage tool) could be accessed/received (rather than a wire/other format) and processed directly. The code coverage data may be accessed in various ways. For example, the data may be received from a test module such as <NUM> (e.g. as the result of an output step such as <NUM> described above). Alternatively, the data may be communicated by a user via their client device <NUM> (who has previously run a code coverage analysis process and received the relevant data). Further alternatively, the data may be retrieved from a location at which the code coverage data has been made available.

At <NUM>, the code base identifier received/accessed at <NUM> is used to identify (or create) a code coverage repository that is associated with that code base. The code coverage repository is a version control system repository in which code coverage results are stored (e.g. repository <NUM> of version control system <NUM>). If no associated code coverage repository exists it is created using appropriate commands/tools provided by the version control system. A clone (e.g. a shallow clone) of the code coverage repository is then performed. Cloning the repository causes a local workspace or working directory to be created.

In some embodiments, a dedicated code coverage repository is created to correspond with each separate source code repository on which code coverage analysis is performed. For example, if a source code repository (e.g. source code repository <NUM>) is being used to store the code base for a particular software product (product <NUM>), code coverage results for code coverage analysis of that code base may be stored in a corresponding code coverage repository (e.g. code coverage repository <NUM>). If a separate source code repository (e.g. source code repository <NUM>) is being used to store the code base for a different software product (product <NUM>), code coverage results for code coverage analysis of that code base may be stored in a separate code coverage repository (e.g. code coverage repository <NUM>).

In other embodiments, a single version control system repository is used to store all code coverage results.

Once the code coverage data has been accessed/received, it is processed to generate a new storage version thereof. Generally speaking, the storage version of the code coverage results is a relatively light-weight (i.e. low size) version of the results which maintains selected information in respect of the code coverage analysis only. The code coverage information selected for inclusion in the storage version, and the particular format used to store that information, will differ depending on implementation and the particular code coverage tool used. Typically, though, the selected information will include coverage information: i.e. information indicating the specific parts of the source code base that were covered by the test suite. As noted above, 'parts' in this respect are whatever atomic elements of the source code that are tracked by the code coverage tool - e.g. source code lines, source code functions, or other source code elements. If the code coverage tool reports on partial coverage of source code parts, partial coverage information may also be selected for inclusion in the storage version - i.e. information indicating which parts of the source code base were partially covered by the test suite. As will be appreciated, different embodiments could record different or additional information regarding the code coverage (for example, method complexity values, hit counts etc.).

Example processing steps for generating a storage version of the code coverage results are described with respect to steps <NUM> - <NUM>. In this example, the storage version of the code coverage results is a set of one or more code coverage result files. Each code coverage result file in the set corresponds to a source code file from the code base that was analyzed and contains selected analysis information from the code coverage results relating to that source code file.

At <NUM>, the wireformat data accessed/received at <NUM> is processed to identify the next unprocessed source code file that was covered by the code coverage analysis.

At <NUM>, a code coverage result file corresponding to the source code file identified at <NUM> is generated.

The code coverage result file is associated with its corresponding source code file. This association may be achieved in various ways, and may be done at the time it is generated or in a later process. For example, association of a code coverage result file with its corresponding source code file may be achieved using the name of the file, data written to the file, or file metadata. In the present embodiment, a code coverage result file is associated with its corresponding source code file using the code coverage file name. Specifically, the name of the code coverage result file includes the path and name of the corresponding source code file - e.g. "<source code path>/<source code file name>".

At <NUM>, the code coverage result file generated at <NUM> is populated with selected code coverage information pertaining to its corresponding source code file. The selected code coverage information is extracted or otherwise derived from the code coverage result data accessed at <NUM>. As noted above, the selected code coverage information may differ depending on the code coverage tool and implementation. In the example below, the selected code coverage information comprises coverage information and partial coverage information (with the parts in question being line numbers) - i.e. the selected code coverage information comprises line numbers indicating lines in source code files that were covered by the test suite and line numbers indicating lines in source code files that were partially covered by the test suite. If not already done, the populated code coverage result file can be written/saved to the working directory/workspace created as a result of cloning the code coverage repository at <NUM>.

By way of specific example, the data of the code coverage result file may be an array including one or more integers and an optional separator character - e.g. a '|' (pipe) or any other appropriate character). In this case, integers appearing before the separator indicate line numbers of the corresponding source code file that were covered by the test suite and integers appearing after the separator character indicate line numbers of the corresponding source code file that were partially covered by the test suite. To illustrate this format, and using a '|' (pipe) as the separation character: "[<NUM>,<NUM>]" would indicate that lines <NUM> and <NUM> were covered; "[<NUM>,<NUM>,<NUM>,<NUM> | <NUM>]" would indicate that lines <NUM>, <NUM>, <NUM>, and <NUM> were covered and line <NUM> was partially covered; "[ | <NUM>,<NUM>]" would indicate that lines <NUM> and <NUM> were partially covered; [] would indicate no lines were covered and no lines were partially covered.

Once the selected code coverage information is written to the code coverage result file, the process continues to <NUM> where a determination is made as to whether the code coverage analysis covered any further source code files for which corresponding code coverage result files have not been generated. If so the process returns to <NUM> to select the next unprocessed source code file.

If, at <NUM>, all source code files have been processed (and, accordingly, the set of code coverage result files is complete) the process continues to <NUM>.

Once the storage version of the code coverage results has been generated it is saved to the version control system repository (e.g. code coverage repository <NUM>). Example processing to achieve this is described with respect to steps <NUM> and <NUM>.

At <NUM>, a commit is crafted to save the storage version of the code coverage results back to the code coverage repository. Continuing the above example, the commit is crafted in respect of the code coverage result files that have been saved to the working directory/workspace created at <NUM>. The commit is crafted in a way that associates it with the relevant source code base that the coverage results relate to. Where Git is used as the version control system, this association may be achieved using a tag that somehow allows for identification of the source code base. By way of specific example, a tag along the following lines may be used 'cov-SourceCodeIdentifier'. In this example, the prefix 'cov' is used to identify that the commit relates to code coverage results, and the 'SourceCodeIdentifier' element of the tag allows the related source code base to be identified. The 'SourceCodeIdentifier' element may be the commit id of the source code base which the code coverage results correspond to. In other embodiments the commit may be associated with its corresponding source code base commit using other data or other mechanisms. If the data used for the association is not data inherent in the associated source code commit, however, an additional data structure may be required in order to record the associations between source code bases (and particular revisions thereof) and their corresponding code coverage results.

At <NUM>, the storage version of the code coverage results is pushed (or published) to the code coverage repository. Where this is the first time that code coverage results in respect of the source code base are being stored in the code coverage repository, the entire set of code coverage result files are copied to the repository. For subsequent commits of code coverage results relating to the same source code base (e.g. the results of code coverage analysis from downstream versions of the source code base), however, storage efficiencies will typically be gained due to likely duplication in the code coverage results and the operation of the version control system.

To illustrate this, consider the source code repository commits depicted in Table B below:.

Table B illustrates a source code repository (repository <NUM>) with three commits. In the first commit (commit A, commit id SC1-A) two files exist and, as both are new, both are saved to the repository (SCFile_1 and SCFile_2). In the second commit (commit B, commit id SC1-B), the content of SCFile_1 is unmodified but the content of SCFile_2 has been changed. For commit B, therefore, the version control system: creates a link to SCFile_1 as stored in Commit A (rather than storing a further copy of the file); stores the modified version of SCFile_2. In the third commit (commit C, commit id SC1-C), SCFile_1 remains the same (i.e. unchanged since commit A), SCFile_2 remains the same (i.e. unchanged since commit B), and SCFile_3 is newly added. For commit C, therefore, the version control system: creates a link to SCFile_1 per Commit A; creates a link to SCFile_2 per Commit B; stores a copy of SCFile_3.

If code coverage analysis was performed to determine the coverage of a particular test suite over each of the three source code base versions (i.e. the versions of Commit A, Commit B, and Commit C), the corresponding code coverage repository could look something like that illustrated in Table C:.

The code coverage repository example illustrated in Table C shows three commits corresponding to the results of three code coverage analyses (performed, respectively, on the code bases of commit id SC1-A, commit id SC1-B, and commit id SC1-C). As can be seen, each code coverage repository commit is tagged with an identifier allowing the corresponding version of the source code base to be identified (while human readable commit identifiers have been used for the purposes of illustration in tables B and C commit identifiers are typically an alphanumeric hash value). Further, each code coverage result file is named in a way that allows the corresponding source code file to be identified: e.g. code coverage result file "/. /SCRepo1/SCFile_1" includes both the path and file name of its corresponding source code file "SCFile_1".

Commit <NUM> in the code coverage repo is the first commit, and therefore both code coverage result files (/. /SCRepo1/SCFile_1 and /. /SCRepo1/SCFile_2) are stored in the repository.

For commit <NUM> in the code coverage repo, the code coverage result file corresponding to source code file <NUM> (i.e. '/. /SCRepo1/SCFile_1') is the same as in commit <NUM>. Accordingly, the version control system generates a link to this file per the commit rather than storing another copy of it. The code coverage result file corresponding to source code file <NUM> (i.e. file name '/. /SCRepo1/SCFile_2') has changed since commit <NUM>, however, so the new version of '/. /SCRepo1/SCFile_2' is stored in the repository.

For commit <NUM> in the code coverage repo, '/. /SCRepo1/SCFile_1 ' is again unchanged, and accordingly a link is created (rather than storing another copy of the file). Similarly, '/. /SCRepo1/SCFile_2' is unchanged and a link is created for this file also. /SCRepo1/SCFile_3' is new and is therefore saved to the repository.

As can be seen from this simple example, instead of storing three identical copies of the code coverage result file '/. /SCRepo1/SCFile_1', a single copy only of that file is stored, and two links (requiring less memory) are generated. Where there are many commits and the source code base includes thousands (or tens of thousands of files) the storage savings can be considerable.

Turning to <FIG>, an example process <NUM> for retrieving code coverage results stored in a code coverage result repository will be described. Process <NUM> will be described as being performed by a client system <NUM> with a user using a client application (such as a web browser or other client application <NUM>) to retrieve and view the test results. The operations could, however, be performed by a different system configured to receive and respond to retrieval requests.

At <NUM>, a request is made to retrieve code coverage results. The request includes a source code base identifier which identifies the particular source code base of interest - i.e. the source code base for which code coverage analysis results are desired. In certain embodiments the source code base identifier is the commit ID of the source code base.

At <NUM>, the relevant code coverage results are identified (using the code base identifier received in the request) and extracted from the code coverage repository <NUM>. Continuing the above example, this can be done by interacting with the version control system <NUM> to access/view the relevant code coverage results.

At <NUM>, and if desired, any processing of the checked-out storage version of the code coverage results is performed. This may, for example, be processing to generate visualizations of the code coverage results to allow users to easily interpret the results (e.g. to see which lines of which source code files in the source code base were covered, which were partially covered, and which were not covered).

At <NUM>, the requested code coverage results are returned (e.g. to the client system <NUM> or other device/service that requested them). The results returned may be in a 'raw' format (i.e. the storage version of the results as stored in the code coverage repository <NUM>) or a processed form (e.g. following any desired processing at <NUM>).

In the foregoing specification, embodiments of the invention have been described with reference to numerous specific details that may vary from implementation to implementation. Thus, the sole and exclusive indicator of what is the invention, and is intended by the applicants to be the invention, is the set of claims that issue from this application, in the specific form in which such claims issue, including any subsequent correction. Any definitions expressly set forth herein for terms contained in such claims shall govern the meaning of such terms as used in the claims. Hence, no limitation, element, property, feature, advantage or attribute that is not expressly recited in a claim should limit the scope of such claim in any way. The specification and drawings are, accordingly, to be regarded in an illustrative rather than a restrictive sense.

A number of flowcharts have been provided in order to illustrate processing or functional steps. Although these flowcharts define steps in particular orders to explain various features in some cases the steps may be able to be performed in a different order. Furthermore, in some cases one or more steps may be combined into a single step, a single step may be divided into multiple separate steps, and/or the function(s) achieved by one or more of the described/illustrated steps may be achieved by one or more alternative steps.

As used herein the terms "include" and "comprise" (and variations of those terms, such as "including", "includes", "comprising", "comprises", "comprised" and the like) are intended to be inclusive and are not intended to exclude further features, components, integers or steps.

Claim 1:
A computer implemented method comprising:
receiving code coverage analysis data performed with respect to a particular version of a source code base and a particular test suite, the code coverage analysis data indicating portions of the source code base covered by the particular test suite;
obtaining, from a code coverage result repository (<NUM>), a previous code coverage analysis data produced using a previous version of a source code base and a test suite;
processing the code coverage analysis data to generate a storage version, the storage version including an array of data elements including an identifier of each of a set of atomic elements of a source code base and a respective selected analysis information regarding a respective atomic element of the set of atomic elements;
analyzing the storage version of the code coverage analysis data with respect to the previous code coverage analysis data to identify:
a first storage version that includes code coverage analysis data for a first source code file; and
a second storage version that includes code coverage analysis data for a second source code file;
comparing the storage version of the code coverage analysis data to determine that the first storage version is unmodified and the second storage version has changed; and
committing a new storage version of the code coverage analysis data in the code coverage result repository (<NUM>) maintained by a particular version control system (<NUM>), wherein the new storage version of the code coverage analysis data committed to the code coverage result repository (<NUM>) is associated with the particular version of the particular source code base, the new storage version comprising:
a modified version of the second storage version comprising changes that resulted from changes to the second source code file; and
a link to the first storage version stored on the previous code coverage analysis data.