Christoph Reichenbach

Discovering Documentation for Java Container Classes

Modern programs make extensive use of reusable software libraries. For example, we found that 17 percent to 30 percent of the classes in a number of large Java applications use the container classes from the java.util package. Given this extensive code reuse in Java programs, it is important for the reusable interfaces to have clear and unambiguous documentation. Unfortunately, most documentation is expressed in English and, therefore, does not always satisfy these requirements. Worse yet, there is no way of checking that the documentation is consistent with the associated code. Formal specifications present an alternative that does not suffer from these problems; however, formal specifications are notoriously hard to write. To alleviate this difficulty, we have implemented a tool that automatically derives documentation in the form of formal specifications. Our tool probes Java classes by invoking them on dynamically generated tests and captures the information observed during their execution as algebraic axioms. Although the tool is not complete or correct from a formal perspective, we demonstrate that it discovers many useful axioms when applied to container classes. These axioms then form an initial formal documentation of the class they describe.

What can the GC compute efficiently?: a language for heap assertions at GC time

We present the DeAL language for heap assertions that are efficiently evaluated during garbage collection time. DeAL is a rich, declarative, logic-based language whose programs are guaranteed to be executable with good whole-heap locality, i.e., within a single traversal over every live object on the heap and a finite neighborhood around each object. As a result, evaluating DeAL programs incurs negligible cost: for simple assertion checking at each garbage collection, the end-to-end execution slowdown is below 2%. DeAL is integrated into Java as a VM extension and we demonstrate its efficiency and expressiveness with several applications and properties from the past literature. Compared to past systems for heap assertions, DeAL is distinguished by its very attractive expressiveness/efficiency tradeoff: it o ers a significantly richer class of assertions than what past systems could check with a single traversal. Conversely, past systems that can express the same (or more) complex assertions as DeAL do so only by su ering orders-of-magnitude higher costs.

Developing and debugging algebraic specifications for Java classes

Modern programs make extensive use of reusable software libraries. For example, a study of a number of large Java applications shows that between 17% and 30% of the classes in those applications use container classes defined in the java.util package. Given this extensive code reuse in Java programs, it is important for the interfaces of reusable classes to be well documented. An interface is well documented if it satisfies the following requirements: (1) the documentation completely describes how to use the interface; (2) the documentation is clear; (3) the documentation is unambiguous; and (4) any deviation between the documentation and the code is machine detectable. Unfortunately, documentation in natural language, which is the norm, does not satisfy the above requirements. Formal specifications can satisfy them but they are difficult to develop, requiring significant effort on the part of programmers. To address the practical difficulties with formal specifications, we describe and evaluate a tool to help programmers write and debug algebraic specifications. Given an algebraic specification of a class, our interpreter generates a prototype that can be used within an application like a regular Java class. When running an application that uses the prototype, the interpreter prints error messages that tell the developer in which way the specification is incomplete or inconsistent with a hand-coded implementation of the class. We use case studies to demonstrate the usefulness of our system.

Residual investigation: predictive and precise bug detection

We introduce the concept of “residual investigation” for program analysis. A residual investigation is a dynamic check installed as a result of running a static analysis that reports a possible program error. The purpose is to observe conditions that indicate whether the statically predicted program fault is likely to be realizable and relevant. The key feature of a residual investigation is that it has to be much more precise (i.e., with fewer false warnings) than the static analysis alone, yet significantly more general (i.e., reporting more errors) than the dynamic tests in the programs test suite pertinent to the statically reported error. That is, good residual investigations encode dynamic conditions that, when taken in conjunction with the static error report, increase confidence in the existence of an error, as well as its severity, without needing to directly observe a fault resulting from the error. We enhance the static analyzer FindBugs with several residual investigations, appropriately tuned to the static error patterns in FindBugs, and apply it to 7 large open-source systems and their native test suites. The result is an analysis with a low occurrence of false warnings (“false positives”) while reporting several actual errors that would not have been detected by mere execution of a programs test suite.

PQL: a purely-declarative java extension for parallel programming

The popularization of parallelism is arguably the most fundamental computing challenge for years to come. We present an approach where parallel programming takes place in a restricted (sub-Turing-complete), logic-based declarative language, embedded in Java. Our logic-based language, PQL, can express the parallel elements of a computing task, while regular Java code captures sequential elements. This approach offers a key property: the purely declarative nature of our language allows for aggressive optimization, in much the same way that relational queries are optimized by a database engine. At the same time, declarative queries can operate on plain Java data, extending patterns such as map-reduce to arbitrary levels of nesting and composition complexity. We have implemented PQL as extension to a Java compiler and showcase its expressiveness as well as its scalability compared to competitive techniques for similar tasks (Java + relational queries, in-memory Hadoop, etc.).

Opinion Polarity Identification of Movie Reviews

One approach to the assessment of overall opinion polarity (OvOP) of reviews, a concept defined in this paper, is the use of supervised machine learning mechanisms. In this paper, the impact of lexical feature selection and feature generalization, applied to reviews, on the precision of two probabilistic classifiers (Naive Bayes and Markov Model) with respect to OvOP identification is observed. Feature generalization based on hypernymy as provided by WordNet, and feature selection based on part-ofspeech (POS) tags are evaluated. A ranking criterion is introduced, based on a function of the probability of having positive or negative polarity, which makes it possible to achieve 100% precision with 10% recall. Movie reviews are used for training and testing the probabilistic classifiers, which achieve 80% precision.

Java wildcards meet definition-site variance

Variance is concerned with the interplay of parametric polymorphism (i.e., templates, generics) and subtyping. The study of variance gives answers to the question of when an instantiation of a generic class can be a subtype of another. In this work, we combine the mechanisms of use-site variance (as in Java) and definition-site variance (as in Scala and C#) in a single type system, based on Java. This allows maximum flexibility in both the specification and use of generic types, thus increasing the reusability of code. Our VarJ calculus achieves a safe synergy of def-site and use-site variance, while supporting the full complexities of the Java realization of variance, including F-bounded polymorphism and wildcard capture. We show that the interaction of these features with definition-site variance is non-trivial and offer a full proof of soundness--the first in the literature for an approach combining variance mechanisms.

Analysis of imperative XML programs

The widespread adoption of XML has led to programming languages that support XML as a first class construct. In this paper, we present a method for analyzing and optimizing imperative XML processing programs. In particular, we present a program analysis, based on a flow-sensitive type system, for detecting both redundant computations and redundant traversals in XML processing programs. The analysis handles declarative queries over XML data and imperative loops that traverse XML values explicitly in a uniform framework. We describe two optimizations that take advantage of our analysis: one merges queries that traverse the same set of XML nodes, and the other replaces an XPath expression by a previously computed result. We show the effectiveness of our method by providing performance measurements on XMark benchmark queries and XLinq sample queries.

Errata for "Discovering Documentation for Java Container Classes" [Aug 07 526-543]

In the above titled paper (ibid., vol. 33, no. 8, pp. 526-543, Aug 07), there were several mistakes. The corrections are presented here.