Summary To improve the ability of compilers to determine alias relations in a program, the C standard restricts the types of expressions that may access objects in memory. In practice, however, many existing C programs do not conform to these restrictions, making type‐based alias analysis unsound for those programs. As a result, type‐based alias analysis is frequently disabled. Existing approaches for verifying type safety exist within larger frameworks designed to verify overall memory safety, requiring both static analysis and runtime checks. This paper describes the motivation for analyzing the safety of type‐based alias analysis independently; presents SafeType, a purely static approach to detection of violations of the C standard's restrictions on memory accesses; describes an implementation of SafeType in the IBM XL C compiler, with flow‐sensitive and context‐sensitive queries to handle variables with typevoid *; evaluates that implementation, showing that it scales to programs with hundreds of thousands of lines of code; and uses SafeType to identify a previously unreported violation in the470.lbmbenchmark in SPEC CPU2006. Copyright © 2015 John Wiley & Sons, Ltd.

This paper describes Memory-Pooling-Assisted Data Splitting (MPADS), a framework that combines data structure splitting with memory pooling --- Although it MPADS may call to mind memory padding, a distintion of this framework is that is does not insert padding. MPADS relies on pointer analysis to ensure that splitting is safe and applicable to type-unsafe language. MPADS makes no assumption about type safety. The analysis can identify cases in which the transformation could lead to incorrect code and thus MPADS abandons those cases.

This article presents Forma , a practical, safe, and automatic data reshaping framework that reorganizes arrays to improve data locality. Forma splits large aggregated data-types into smaller ones to improve data locality. Arrays of these large data types are then replaced by multiple arrays of the smaller types. These new arrays form natural data streams that have smaller memory footprints, better locality, and are more suitable for hardware stream prefetching. Forma consists of a field-sensitive alias analyzer, a data type checker, a portable structure reshaping planner, and an array reshaper. An extensive experimental study compares different data reshaping strategies in two dimensions: (1) how the data structure is split into smaller ones ( maximal partition × frequency-based partition × affinity-based partition ); and (2) how partitioned arrays are linked to preserve program semantics ( address arithmetic-based reshaping × pointer-based reshaping ). This study exposes important characteristics of array reshaping. First, a practical data reshaper needs not only an inter-procedural analysis but also a data-type checker to make sure that array reshaping is safe. Second, the performance improvement due to array reshaping can be dramatic: standard benchmarks can run up to 2.1 times faster after array reshaping. Array reshaping may also result in some performance degradation for certain benchmarks. An extensive micro-architecture-level performance study identifies the causes for this degradation. Third, the seemingly naive maximal partition achieves best or close-to-best performance in the benchmarks studied. This article presents an analysis that explains this surprising result. Finally, address-arithmetic-based reshaping always performs better than its pointer-based counterpart.