The present application is directed towards systems and methods for cluster-based code analysis and transformation. Cluster-based analysis may group code objects based on their similarity across functional areas, such as where a code object is cloned in multiple areas (e.g. sort functions that are duplicated across areas, or reports or tables that are identical). In some implementations, objects may be grouped into clusters by type, or based on reading from or writing to a common table. In some implementations, clustering at different layers may be possible.

A method, computer system, and computer program product for estimation of post-inlining transformation benefits are provided. The embodiment may include performing abstract interpretation on a program to find potential post-inlining transformations. The embodiment may also include encoding potential post-inlining transformations into a profitability metric by associating constraints under which a profit is determined to be realized. The embodiment may further include scaling the profitability metric using the relative execution frequency of the program point to which the transformation applies to favor applying transformations in the most frequently executed code paths. The embodiment may also include generating method summaries to store the potential post-inlining transformations in the method summaries. The embodiment may further include creating a method summary map to match each method with each method summary.

A system for compiling programs for execution thereof using a hierarchical processing system having two or more levels of memory hierarchy can perform memory-level-specific optimizations, without exceeding a specified maximum compilation time. To this end, the compiler system employs a polyhedral model and limits the dimensions of a polyhedral program representation that is processed by the compiler at each level using a focalization operator that temporarily reduces one or more dimensions of the polyhedral representation. Semantic correctness is provided via a defocalization operator that can restore all polyhedral dimensions that had been temporarily removed.

The present application is directed towards systems and methods for cluster-based code analysis and transformation. Cluster-based analysis may group code objects based on their similarity across functional areas, such as where a code object is cloned in multiple areas (e.g. sort functions that are duplicated across areas, or reports or tables that are identical). In some implementations, objects may be grouped into clusters by type, or based on reading from or writing to a common table. In some implementations, clustering at different layers may be possible.

Disclosed aspects relate to operation efficiency management in a shared pool of configurable computing resources. A first set of processing operations of a first application may be detected. A second set of processing operations of a second application may be detected. The first set of processing operations of the first application may be compared with the second set of processing operations of the second application. A substantial match of the first and second processing operations of the first and second applications may be determined. A single set of processing operations for both the first and second applications may be established.

Systems and methods for configuring a reduced instruction set computer processor architecture to execute fully homomorphic encryption (FHE) logic gates as a streaming topology. The method includes parsing sequential FHE logic gate code, transforming the FHE logic gate code into a set of code modules that each have in input and an output that is a function of the input and which do not pass control to other functions, creating a node wrapper around each code module, configuring at least one of the primary processing cores to implement the logic element equivalents of each element in a manner which operates in a streaming mode wherein data streams out of corresponding arithmetic logic units into the main memory and other ones of the plurality arithmetic logic units.

The present application is directed towards systems and methods for providing a heat map interface for analyzing and reporting transformation capabilities of a source installation to a target installation of an application. Characteristics of the source installation are displayed in an easy, intuitive interface, providing improved efficiency in analysis and planning. Furthermore, the interface is interactive, allowing an administrator or user to select and apply transformation dispositions to code objects grouped into regions and sub-regions, providing versatility and accuracy of configuration.

The present application is directed towards systems and methods for providing a heat map interface for analyzing and reporting transformation capabilities of a source installation to a target installation of an application. Characteristics of the source installation are displayed in an easy, intuitive interface, providing improved efficiency in analysis and planning. Furthermore, the interface is interactive, allowing an administrator or user to select and apply transformation dispositions to code objects grouped into regions and sub-regions, providing versatility and accuracy of configuration.

A screen transition aggregation device includes a calculation unit configured to calculate a degree of similarity between a transition destination screen and a transition source screen in order from an end screen in a screen transition diagram; and a generation unit configured to classify the transition destination screen and the transition source screen into groups based on a comparison between the degree of similarity and a threshold value, and to generate information indicating a transition relationship between the groups. Thus, the ease of grasping the specifications of an application that provides a function by screen transition is improved.

The present application is directed towards systems and methods for cluster-based code analysis and transformation. Cluster-based analysis may group code objects based on their similarity across functional areas, such as where a code object is cloned in multiple areas (e.g. sort functions that are duplicated across areas, or reports or tables that are identical). In some implementations, objects may be grouped into clusters by type, or based on reading from or writing to a common table. In some implementations, clustering at different layers may be possible.