Live Heap Space Analysis for Languages with Garbage Collection

The peak heap consumption of a program is the maximum size of the live data on the heap during the execution of the program, i.e., the minimum amount of heap space needed to run the program without exhausting the memory. It is well-known that garbage collection (GC) makes the problem of predicting the memory required to run a program difficult. This paper presents, the best of our knowledge, the first live heap space analysis for garbage-collected languages which infers accurate upper bounds on the peak heap usage of a program’s execution that are not restricted to any complexity class, i.e., we can infer exponential, logarithmic, polynomial, etc., bounds. Our analysis is developed for an (sequential) object-oriented bytecode language with a scoped-memory manager that reclaims unreachable memory when methods return. We also show how our analysis can accommodate other GC schemes which are closer to the ideal GC which collects objects as soon as they become unreachable. The practicality of our approach is experimentally evaluated on a prototype implementation.We demonstrate that it is fully automatic, reasonably accurate and efficient by inferring live heap space bounds for a standardized set of benchmarks, the JOlden suite

From Object Fields to Local Variables: A Practical Approach to Field-Sensitive Analysis

Static analysis which takes into account the value of data stored in the heap is typically considered complex and computationally intractable in practice. Thus, most static analyzers do not keep track of object fields (or fields for short), i.e., they are field-insensitive. In this paper, we propose locality conditions for soundly converting fields into local variables. This way, field-insensitive analysis over the transformed program can infer information on the original fields. Our notion of locality is context-sensitive and can be applied both to numeric and reference fields. We propose then a polyvariant transformation which actually converts object fields meeting the locality condition into variables and which is able to generate multiple versions of code when this leads to increasing the amount of fields which satisfy the locality conditions. We have implemented our analysis within a termination analyzer for Java bytecode

Parametric Inference of Memory Requirements for Garbage Collected Languages

The accurate prediction of program's memory requirements is a critical component in software development. Existing heap space analyses either do not take deallocation into account or adopt specific models of garbage collectors which do not necessarily correspond to the actual memory usage. We present a novel approach to inferring upper bounds on memory requirements of Java-like programs which is parametric on the notion of object lifetime, i.e., on when objects become collectible. If objects lifetimes are inferred by a reachability analysis, then our analysis infers accurate upper bounds on the memory consumption for a reachability-based garbage collector. Interestingly, if objects lifetimes are inferred by a heap liveness analysis, then we approximate the program minimal memory requirement, i.e., the peak memory usage when using an optimal garbage collector which frees objects as soon as they become dead. The key idea is to integrate information on objects lifetimes into the process of generating the recurrence equations which capture the memory usage at the different program states. If the heap size limit is set to the memory requirement inferred by our analysis, it is ensured that execution will not exceed the memory limit with the only assumption that garbage collection works when the limit is reached. Experiments on Java bytecode programs provide evidence of the feasibility and accuracy of our analysis

A Termination Analyzer for Java Bytecode based on Path-Length

It is important to prove that supposedly terminating programs actuallyterminate, particularly if those programs must berun on critical systems or downloaded into a client such as a mobile phone.Although termination of computer programs is generally undecidable,it is possible and useful to provetermination of a large, non-trivial subset of the terminating programs.In this paper we present our termination analyser for sequential Java bytecode,based on a program property called path-length. We describe theanalyses which are needed before the path-length can be computed, such assharing, cyclicity and aliasing. Then weformally define the path-length analysis and prove it correct wrt areference denotational semantics of the bytecode. We show that a constraintlogic program P_CLPcan be built from the result of the path-length analysisof a Java bytecode program P andformally prove that if P_CLP terminates then also P terminates.Hence a termination prover for constraint logic programs can be appliedto prove the termination of P. We conclude with some discussion of thepossibilities and limitations of our approach.Ours is the first existing termination analyser for Java bytecodedealing with any kind of data structures dynamically allocated on the heapand which does not require any help or annotation on the part of the user

Formal Translation of Bytecode into BoogiePL

Many modern program verifiers translate the program to be verified and its specification into a simple intermediate representation and then compute verification conditions on this representation. Using an intermediate language improves the interoperability of tools and facilitates the computation of small verification conditions. Even though the translation into an intermediate representation is critical for the soundness of a verifier, this step has not been formally verified. In this paper, we formalize the translation of a small subset of Java bytecode into an imperative intermediate language similar to BoogiePL. We prove soundness of the translation by showing that each bytecode method whose BoogiePL translation can be verified, can also be verified in a logic that operates directly on bytecode

From abstract programs to precise asymptotic closed-form bounds

Tesis inédita de la Universidad Complutense de Madrid, Facultad de Informática, Departamento de Sistemas Informáticos y Computación, leída el 29-05-2014.Depto. de Sistemas Informáticos y ComputaciónFac. de InformáticaTRUEunpu